Easy Agile Podcast Ep.34 Henrik Kniberg on Team Productivity, Code Quality, and the Future of Software Engineering
TL;DR
Henrik Kniberg, the agile coach behind Spotify's model, discusses how AI is fundamentally transforming software development. Key takeaways: AI tools like Cursor and Claude are enabling 10x productivity gains; teams should give developers access to paid AI tools and encourage experimentation; coding will largely disappear as a manual task within 3–4 years; teams will shrink to 2 people plus AI; sprints will become obsolete in favour of continuous delivery; product owners can now write code via AI, creating pull requests instead of user stories; the key is treating AI like a brilliant intern – when it fails, the problem is usually your prompt or code structure, not the AI. Bottom line: Learn to use AI now, or risk being left behind in a rapidly changing landscape.
Introduction
Artificial intelligence is fundamentally reshaping how software teams work, collaborate, and deliver value. But with this transformation comes questions: How do we maintain team morale when people fear being replaced? What happens to code quality when AI writes most of the code? Do traditional agile practices like sprints still make sense?
In this episode, I sit down with Henrik Kniberg to tackle these questions head-on. Henrik is uniquely positioned to guide us through this transition – he's the agile coach and entrepreneur who pioneered the famous Spotify model and helped transform how Lego approached agile development. Now, as co-founder of Abundly AI, he's at the forefront of helping teams integrate AI into their product development workflows.
This conversation goes deep into the practical realities of AI-powered development: from maintaining code review processes when productivity increases 10x, to ethical considerations around AI usage, to what cross-functional teams will look like in just a few years. Henrik doesn't just theorise – he shares real examples from his own team, where their CEO (a non-coder) regularly submits pull requests, and where features that once took a sprint can now be built during a 7-minute subway ride.
Whether you're a developer wondering if AI will replace you, a product owner looking to leverage these tools, or a leader trying to navigate this transformation, this episode offers concrete, actionable insights for thriving in the AI era.
About Our Guest
Henrik Kniberg is an agile coach, author, and entrepreneur whose work has shaped how thousands of organisations approach software development. He's best known for creating the Spotify model – the squad-based organisational structure that revolutionised how large tech companies scale agile practices. His work at Spotify and later at Lego helped demonstrate how agile methodologies could work at enterprise scale whilst maintaining team autonomy and innovation.
Henrik's educational videos have become legendary in the agile community. His "Agile Product Ownership in a Nutshell" video, created over a decade ago, remains one of the most-watched and shared resources for understanding product ownership, with millions of views. His ability to distil complex concepts into simple, visual explanations has made him one of the most accessible voices in agile education.
More recently, Henrik has turned his attention to the intersection of AI and product development. As co-founder of Abundly AI, he's moved from teaching about agile transformation to leading AI transformation – helping companies and teams understand how to effectively integrate generative AI tools into their development workflows. His approach combines his deep understanding of team dynamics and agile principles with hands-on experience using cutting-edge AI tools like Claude, Cursor, and GitHub Copilot.
Henrik codes daily using AI and has been doing so for over two and a half years, giving him practical, lived experience with these tools that goes beyond theoretical understanding. He creates educational content about AI, trains teams on effective AI usage, and consults with organisations navigating their own AI transformations. His perspective is particularly valuable because he views AI through the lens of organisational change management – recognising that successful AI adoption isn't just about the technology, it's about people, culture, and process.
Based in Stockholm, Sweden, Henrik continues to push the boundaries of what's possible when human creativity and AI capabilities combine, whilst maintaining a pragmatic, human-centred approach to technological change.
Transcript
Note: This transcript has been lightly edited for clarity and readability.
Maintaining Team Morale and Motivation in the AI Era
Tenille Hoppo: Hi there, team, and welcome to this new episode of the Easy Agile Podcast. My name is Tenille Hoppo, and I'm feeling really quite lucky to have an opportunity to chat today with our guest, Henrik Kniberg.
Henrik is an agile coach, author, and entrepreneur known for pioneering agile practices at companies like Spotify and Lego, and more recently for his thought leadership in applying AI to product development. Henrik co-founded Abundly AI, and when he isn't making excellent videos to help us all understand AI, he is focused on the practical application of generative AI in product development and training teams to use these technologies effectively.
Drawing on his extensive experience in agile methodologies and team coaching, Henrik seems the perfect person to learn from when thinking about the intersection of AI, product development, and effective team dynamics. So a very warm welcome to you, Henrik.
Henrik Kniberg: Thank you very much. It's good to be here.
Tenille: I think most people would agree that motivated people do better work. So I'd like to start today by touching on the very human element of this discussion and helping people maintain momentum and motivation when they may be feeling some concern or uncertainty about the upheaval that AI might represent for them in their role.
What would you suggest that leaders do to encourage the use of AI in ways that increase team morale and creativity rather than risking people feeling quite concerned or even potentially replaced?
Henrik: There are kind of two sides to the coin. There's one side that says, "Oh, AI is gonna take my job, and I'm gonna get fired." And the other side says, "Oh, AI is going to give me superpowers and give us all superpowers, and thereby give us better job security than we had before."
I think it's important to press on the second point from a leader's perspective. Pitch it as this is a tool, and we are entering a world where this tool is a crucial tool to understand how to use – in a similar way that everyone uses the Internet. We consider it obvious that you need to know how to use the Internet. If you don't know how to use the Internet, it's going to be hard.
"I encourage people to experiment, give them access to the tools to do so, and encourage sharing. And don't start firing people because they get productive."
I also find that people tend to get a little bit less scared once they learn to use it. It becomes less scary. It's like if you're worried there's a monster under your bed, maybe look under your bed and turn on the lights. Maybe there wasn't a monster there, or maybe it was there but it was kind of cute and just wanted a hug.
Creating a Culture of Safe Experimentation
Tenille: I've read that you encourage experimentation with AI through learning – I agree it's the best way to learn. What would you encourage leaders and team leaders to do to create a strong culture where teams feel safe to experiment?
Henrik: There are some things. One is pretty basic: just give people access to good AI tools. And that's quite hard in some large organisations because there are all kinds of resistance – compliance issues, data security issues. Are we allowed to use ChatGPT or Claude? Where is our data going? There are all these scary things that make companies either hesitate or outright try to stop people.
Start at that hygiene level. Address those impediments and solve them. When the Internet came, it was really scary to connect your computer to the Internet. But now we all do it, and you kind of have to, or you don't get any work done. We're at this similar moment now.
"Ironically, when companies are too strict about restricting people, then what people tend to do is just use shadow AI – they use it on their own in private or in secret, and then you have no control at all."
Start there. Once people have access to really good AI tools, then it's just a matter of encouraging and creating forums. Encourage people to experiment, create knowledge-sharing forums, share your own experiments. Try to role-model this yourself. Say, "I tried using AI for these different things, and here's what I learned." Also provide paths for support, like training courses.
The Right Mindset for Working with AI
Tenille: What would you encourage in team members as far as their mindset or skills go? Certainly a nature of curiosity and a willingness to learn and experiment. Is there anything beyond that that you think would be really key?
Henrik: It is a bit of a weird technology that's never really existed before. We're used to humans and code. Humans are intelligent and kind of unpredictable. We hallucinate sometimes, but we can do amazing things. Code is dumb – it executes exactly what you told it to do, and it does so every time exactly the same way. But it can't reason, it can't think.
Now we have AI and AI agents which are somewhere in the middle. They're not quite as predictable as code, but they're a lot more predictable than humans typically. They're a lot smarter than code, but maybe not quite as smart as humans – except for some tasks when they're a million times smarter than humans. So it's weird.
You need a kind of humble attitude where you come at it with a mindset of curiosity. Part of it is also to realise that a lot of the limitation is in you as a user. If you try to use AI for coding and it wrote something that didn't work, it's probably not the model itself. It's probably your skills or lack of skills because you have to learn how to use these tools. You need to have this attitude of "Oh, it failed. What can I do differently next time?" until you really learn how to use it.
"There can be some aspect of pride with developers. Like, 'I've been coding for 30 years. Of course this machine can't code better than me.' But if you think of it like 'I want this thing to be good, I want to bring out the best in this tool' – not because it's going to replace me, but because it's going to save me a tonne of time by doing all the boring parts of the coding so I can do the more interesting parts – that kind of mindset really helps."
Maintaining Code Quality and Shared Understanding
Tenille: Our team at Easy Agile is taking our steps and trying to figure out how AI is gonna work best for us. I put the question out to some of our teams, and there were various questions around people taking their first steps in using AI as a co-pilot and producing code. There are question marks around consistency of code, maintaining code quality and clean architecture, and even things like maintaining that shared understanding of the code base. What advice do you have for people in that situation?
Henrik: My first piece of advice when it comes to coding – and this is something I do every day with AI, I've been doing for about two and a half years now – is that the models now, especially Claude, have gotten to the level where it's basically never the AI's fault anymore. If it does anything wrong, it's on you.
You need to think about: okay, am I using the wrong tool maybe? Or am I not using the tool correctly?
For example, the current market leader in terms of productivity tools with AI is Cursor. There are other tools that are getting close like GitHub Copilot, but Cursor is way ahead of anything else I've seen. With Cursor, it basically digs through your code base and looks for what it needs.
But if it fails to find what it needs, you need to think about why. It probably failed for the same reason a human might have failed. Maybe your code structure was very unstructured. Maybe you need to explain to the AI what the high-level structure of your code is.
"Think of it kind of like a really smart intern who just joined your team. They're brilliant at coding, but now they got confused about something, and it's probably your code – something in it that made it confused. And now you need to clarify that."
There are ways to do that. In Cursor, for example, you can create something called cursor rules, which are like standing documents that describe certain aspects of your system. In my team, we're always tweaking those rules. Whenever we find that the AI model did something wrong, we're always analysing why. Usually it's our prompt – I just phrased it badly – or I just need to add a cursor rule, or I need to break the problem down a little bit.
It's exactly the same thing as if you go to a team and give them this massive user story that includes all these assumptions – they'll probably get some things wrong. But if you take that big problem and sit down together and analyse it and split it into smaller steps where each step is verifiable and testable, now your team can do really good work. It's exactly the same thing with AI.
Addressing the Code Review Bottleneck
Tenille: One of our senior developers found that he was outputting code at a much greater volume and faster speed, but the handbrake he found was actually their code review processes. They were keeping the same processes they had previously, and that was a bit of a handbrake for them. What kind of advice would you have there?
Henrik: This reminds me of the general issue with any kind of productivity improvement. If you have a value stream, a process where you do different parts – you do some development, some testing, you have some design – whenever you take one part of the process and make it super optimised, the bottleneck moves to somewhere else.
If testing is no longer the bottleneck, maybe coding is. And when coding is instant, then maybe customer feedback – or lack of customer feedback – is the bottleneck. The bottleneck just keeps moving. In that particular case, the bottleneck became code review. So I would just start optimising that. That's not an AI problem. It's a process problem.
Look at it: what exactly are we trying to do when we review? Maybe we could think about changing the way we review things. For example, does all code need to be reviewed? Would it be enough that the human who wrote it and the AI, together with the human, agree that this is fine? Or maybe depending on the criticality of that change, in some cases you might just let it pass or use AI to help in the reviewing process also.
"I think there's value in code review in terms of knowledge sharing in a large organisation. But maybe the review doesn't necessarily need to be a blocking process either. It could be something you go back and look at – don't let it stop you from shipping, but maybe go back once per week and say, 'Let's look at some highlights of some changes we've made.'"
We produce 10 times more code than in the past, so reviewing every line is not feasible. But maybe we can at least identify which code is most interesting to look at.
Ethical Considerations: Balancing Innovation with Responsibility
Tenille: Agile emphasises people over process and delivering value to customers. Now with AI in the mix, there's potential for raising some ethical considerations. I'm interested in your thoughts on how teams should approach these ethical considerations that come along with AI – things like balancing rapid experimentation against concerns around bias, potential data privacy concerns.
Henrik: I would treat each ethical question on its own merits. Let me give you an example. When you use AI – let's say facial recognition technology that can process and recognise faces a lot better than any human – I kind of put that in the bucket of: any tool that is really useful can also be used for bad things. A hammer, fire, electricity.
That doesn't have so much to do with the tool itself. It has much more to do with the rules and regulations and processes around the tool. I can't really separate AI in that sense. Treat it like any other system. Whenever you install a camera somewhere, with or without AI, that camera is going to see stuff. What are you allowed to do with that information? That's an important question. But I don't think it's different for AI really, in that sense, other than that AI is extremely powerful. So you need to really take that seriously, especially when it comes to things like autonomous weapons and the risk of fraud and fake news.
"An important part of it is just to make it part of the agenda. Let's say you're a recruitment company and you're now going to add some AI help in screening. At least raise the question: we could do this. Do we want to do this? What is the responsible way to do it?"
It's not that hard to come up with reasonable guidelines. Obviously, we shouldn't let the AI decide who we're going to hire or not. That's a bad idea. But maybe it can look at the pile of candidates that we plan to reject and identify some that we should take a second look at. There's nothing to lose from that because that AI did some extra research and found that this person who had a pretty weak CV actually has done amazing things before.
We're actually working with a company now where we're helping them build some AI agents. Our AI agents help them classify CVs – not by "should we hire them or not," but more like which region in Sweden is this, which type of job are we talking about here. Just classifying to make it more likely that this job application reaches the right person. That's work that humans did before with pretty bad accuracy.
The conclusion was that AI, despite having biases like we humans do, seemed to have less biases than the human. Mainly things like it's never going to be in a bad mood because it hasn't had its coffee today. It'll process everybody on the same merits.
I think of it like a peer-to-peer thing. Imagine going to a doctor – ideally, I want to have both a human doctor and an AI doctor side by side, just because they both have biases, but now they can complement each other. It's like having a second opinion. If the AI says we should do this and the doctor says, "No, wait a second," or vice versa, having those two different opinions is super useful.
Parallels Between Agile and AI Transformations
Tenille: You're recognised as one of the leading voices in agile software development. I can see, and I'm interested if you do see, some parallels between the agile transformations that you led at Spotify and Lego with the AI transformations that many businesses are looking at now.
Henrik: I agree. I find that when we help companies transition towards becoming AI native, a lot of the thinking is similar to agile. But I think we can generalise that agile transformations are not really very special either – it's organisational change.
There are some patterns involved regardless of whether you're transitioning towards an agile way of working or towards AI. Some general patterns such as: you've got to get buy-in, it's useful to do the change in an incremental way, balance bottom-up with top-down. There are all these techniques that are useful regardless. But as an agilist, if you have some skills and competence in leading and supporting a change process, then that's going to be really useful also when helping companies understand how to use AI.
Tenille: Are you seeing more top-down or bottom-up when it comes to AI transformations?
Henrik: So far it's quite new still. The jury's not in yet. But so far it looks very familiar to me. I'm seeing both. I'm seeing situations where it's pure top-down where managers are like "we got to go full-out AI," and they push it out with mixed results. And sometimes just completely bottom-up, also with mixed results.
Sometimes something can start completely organically and then totally take hold, or it starts organically and then gets squashed because there was no buy-in higher up. I saw all of that with agile as well. My guess is in most cases the most successful will be when you have a bit of both – support and guidance from the top, but maybe driven from the bottom.
"I think the bottom-up is maybe more important than ever because this technology is so weird and so fast-moving. As a leader, you don't really have a chance if you try to control it – you're going to slow things down to an unacceptable level. People will be learning things that you can't keep up with yourself. So it's better to just enable people to experiment a lot, but then of course provide guidance."
AI for Product Owners: From Ideation to Pull Requests
Tenille: You're very well known for your guidance and for your ability to explain quite complex concepts very simply and clearly. I was looking at your video on YouTube today, the Agile Product Ownership in a Nutshell video, which was uploaded about 12 years ago now. Thinking about product owners, there's a big opportunity now with AI for generating ideas, analysing data, and even suggesting new features. What's your advice for product owners and product managers in using AI most effectively?
Henrik: Use it for everything. Overuse it so you can find the limits. The second thing is: make sure you have access to a good AI model. Don't use the free ones. The difference is really large – like 10x, 100x difference – just in paying like $20 per month or something. At the moment, I can particularly strongly recommend Claude. It's in its own category of awesomeness right now. But that of course changes as they leapfrog each other. But mainly: pay up, use a paid model, and then experiment.
For product owners, typical things are what you already mentioned – ideation, creating good backlog items, splitting a story – but also writing code. I would say as a PO, there is this traditional view, for example in Scrum, that POs should not be coding. There's a reason for that: because coding takes time, and then as PO you get stuck in details and you lose the big picture.
Well, that's not true anymore. There are very many things that used to be time-consuming coding that is basically a five-minute job with a good prompt.
"Instead of wasting the team's time by trying to phrase that as a story, just phrase it as a pull request instead and go to the team and demonstrate your running feature."
That happened actually today. Just now, our CEO, who's not a coder, came to me with a pull request. In fact, quite often he just pushes directly to a branch because it's small changes. He wants to add some new visualisation for a graph or something in our platform – typically admin stuff that users won't see, so it's quite harmless if he gets it wrong.
He's vibe coding, just making little changes to the admin, which means he never goes to my team and says, "Hey, can you guys generate this report or this graph for how users use our product?" No, he just puts it in himself if it's simple.
Today we wanted to make a change with how we handle payments for enterprise customers. Getting that wrong is a little more serious, and the change wasn't that hard, but he just didn't feel completely comfortable pushing it himself. So he just made a PR instead, and then we spent 15 minutes reviewing it. I said it was fine, so we pushed it.
It's so refreshing that now anybody can code. You just need to learn the basic prompting and these tools. And then that saves time for the developers to do the more heavyweight coding.
Tenille: It's an interesting world where we can have things set up where anyone could just jump in and with the right guardrails create something. It makes Friday demos quite probably a lot more interesting than maybe they used to be in the past.
Henrik: I would like to challenge any development team to let their stakeholders push code, and then find out whatever's stopping you from doing that and fix that. Then you get to a very interesting space.
Closing the Gap Between Makers and Users
Tenille: A key insight from your work with agile teams in the past has been to really focus on minimising that gap between maker and user. Do you think that AI helps to close that gap, or do you think it potentially risks widening it if teams are focusing too much on AI predictions and stop talking to their customers effectively?
Henrik: I think that of course depends a lot on the team. But from what I've seen so far, it massively reduces the gap. Because if I don't have to spend a week getting a feature to work, I can spend an hour instead. Then I have so much more time to talk to my users and my customers.
If the time to make a clickable prototype or something is a few seconds, then I can do it live in real time with my customers, and we can co-create. There are all these opportunities.
I find that – myself, my teams, and the people I work with – we work a lot more closely with our users and customers because of this fast turnaround time.
"Just yesterday I was teaching a course, and I was going home sitting on the subway. It was a 15-minute subway ride. I finally got a seat, so I had only 7 minutes left. There's this feature that I wanted to build that involved both front-end and back-end and a database schema change. Well, 5 minutes later it was done and I got off the subway and just pushed it. That's crazy."
Of course, our system is set up optimised to enable it to be that fast. And of course not everything will work that well. But every time it does, I've been coding for 30 years, and I feel like I wake up in some weird fantasy every day, wondering, "Can I really be this productive?" I never would have thought that was possible.
Looking Ahead: The Future of Agile Teams
Tenille: I'd like you to put your futurist hat on for a moment. How do you see the future of agile teamwork in, say, 10 to 15 years time? If we would have this conversation again in 2035, given the exponential growth of AI and improvements over the last two to three years, what do you think would be the biggest change for software development teams in how they operate?
Henrik: I can't even imagine 10 years. Even 5 years is just beyond imagination. That's like asking someone in the 1920s to imagine smartphones and the Internet. I think that's the level of change we're looking at.
I would shorten the time a little bit and say maybe 3 or 4 years. My guess there – and I'm already seeing this transfer happen – is that coding will just go away. It just won't be stuff that we humans do because we're too slow and we hallucinate way too much.
But I think engineering and the developer role will still be there, just that we don't type lines of code – in the same way that we no longer make punch cards or we no longer write machine code and poke values into registers using assembly language. That used to be a big part of it, but no longer.
"In the future, as developers, a lot of the work will still be the same. You're still designing stuff, you're thinking about architecture, you're interacting with customers, and you're doing all the other stuff. But typing lines of code is something that we're gonna be telling our kids about, and they're not gonna believe that we used to do that."
The other thing is smaller teams, which I'm already seeing now. I think the idea of a cross-functional team of 5 to 7 people – traditionally that was considered quite necessary in order to have all the different skills needed to deliver a feature in a product. But that's not the case anymore. If you skip ahead 2 or 3 years when this knowledge has spread, I think most teams will be 2 people and an AI, because then you have all the domain knowledge you need, probably.
As a consequence of that, we'll just have more teams. More and smaller teams. Of course, then you need to collaborate between the teams, so cross-team synchronisation is still going to be an issue.
Also, I'm already seeing this now, but this concept of sprints – the whole point is to give a team some peace of mind to build something complex, because typically you would need a week or two to build something complex. But now, when it takes a day and some good prompting to do the same thing that would have taken a whole sprint, then the sprint is a day instead. If the sprint is a day, is there any difference between a sprint planning meeting and a daily standup? Not really.
I think sprints will just kind of shrink into oblivion. What's going to be left instead is something a little bit similar – some kind of synchronisation point or follow-up point. Instead of a sprint where every 2 weeks we sit down and try to make a plan, I think it'll be very much continuous delivery on a day-to-day basis. But then maybe every week or two we take a step back and just reflect a little bit and say, "Okay, what have we been delivering the past couple of weeks? What have we been learning? What's our high-level focus for the next couple of weeks?" A very, very lightweight equivalent of a sprint.
I feel pretty confident about that guess because personally, we are already there with my team, and I think it'll become a bit of a norm.
Final Thoughts: Preparing for the Future
Henrik: No one knows what's gonna happen in the future, and those who say they do are kidding themselves. But there's one fairly safe bet though: no matter what happens in the future with AI, if you understand how to use it, you'll be in a better position to deal with whatever that is. That's why I encourage people to get comfortable with it, get used to using it.
Tenille: I have a teenage daughter who I'm actually trying to encourage to learn how to use AI, because I feel like when I was her age, the Internet was the thing that was sort of coming mainstream. It completely changed the way we live. Everything is online now. And I feel like AI is that piece for her.
Henrik: Isn't it weird that the generation of small children growing up now are going to consider this to be normal and obvious? They'll be the AI natives. They'll be like, "Of course I have my AI agent buddy. There's nothing weird about that at all."
Tenille: I'll still keep being nice to my coffee machine.
Henrik: Yeah, that's good. Just in case, you know.
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Thank you to Henrik Kniberg for joining us on this episode of the Easy Agile Podcast. To learn more about Henrik's work, visit Abundly AI or check out his educational videos on AI and agile practices.
Subscribe to the Easy Agile Podcast on your favourite platform, and join us for more conversations about agile, product development, and the future of work.
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Easy Agile Podcast Ep.12 Observations on Observability
On this episode of The Easy Agile Podcast, tune in to hear developers Angad, Jared, Jess and Jordan, as they share their thoughts on observability.
Wollongong has a thriving and supportive tech community and in this episode we have brought together some of our locally based Developers from Siligong Valley for a round table chat on all things observability.
💥 What is observability?
💥 How can you improve observability?
💥 What's the end goal?

"This was a great episode to be a part of! Jess and Jordan shared some really interesting points on the newest tech buzzword - observability""
Be sure to subscribe, enjoy the episode 🎧
Transcript
Jared Kells:
Welcome everybody to the Easy Agile podcast. My name's Jared Kells, and I'm a developer here at Easy Agile. Before we begin, Easy Agile would like to acknowledge the traditional custodians of the land from which we broadcast today, the Wodiwodi people of the Dharawal nation, and pay our respects to elders past, present and emerging, and extend that same respect to any aboriginal people listening with us today.
Jared Kells:
So today's podcast is a bit of a technical one. It says on my run sheet here that we're here to talk about some hot topics for engineers in the IT sector. How exciting that we've got a couple of primarily front end engineers and Angad and I are going to share some front end technical stuff and Jess and Jordan are going to be talking a bit about observability. So we'll start by introductions. So I'll pass it over to Jess.
Jess Belliveau:
Cool. Thanks Jared. Thanks for having me one as well. So yeah, my name's Jess Belliveau. I work for Apptio as an infrastructure engineer. Yeah, Jordan?
Jordan Simonovski:
I'm Jordan Simonovski. I work as a systems engineer in the observability team at Atlassian. I'm a bit of a jack of all trades, tech wise. But yeah, working on building out some pretty beefy systems to handle all of our data at Atlassian at the moment. So, that's fun.
Angad Sethi:
Hello everyone. I'm Angad. I'm working for Easy Agile as a software dev. Nothing fancy like you guys.
Jared Kells:
Nothing fancy!
Jess Belliveau:
Don't sell yourself short.
Jared Kells:
Yeah, I'll say. Yeah, so my name's Jared, and yeah, senior developer at Easy Agile, working on our apps. So mainly, I work on programs and road maps. And yeah, they're front end JavaScript heavy apps. So that's where our experience is. I've heard about this thing called observability, which I think is just logs and stuff, right?
Jess Belliveau:
Yeah, yeah. That's it, we'll wrap up!
Jared Kells:
Podcast over! Tell us about observability.
Jess Belliveau:
Yeah okay, I'll, yeah. Well, I thought first I'd do a little thing of why observability, why we talk about this and sort of for people listening, how we got here. We had a little chat before we started recording to try and feel out something that might interest a broader audience that maybe people don't know a lot about. And there's a lot of movements in the broad IT scope, I guess, that you could talk about. There's so many different things now that are just blowing up. Observability is something that's been a hot topic for a couple of years now. And it's something that's a core part of my job and Jordan's job as well. So it's something easy for us to talk about and it's something that you can give an introduction to without getting too technical. So we don't want to get down. This is something that you can go really deep into the weeds, so we picked it as something that hopefully we can explain to you both at a level that might interest the people at home listening as well.
Jess Belliveau:
Jordan and I figured out these four bullet points that we wanted to cover, and maybe I can do the little overview of that, and then I can make Jordan cover the first bullet point, just throw him straight under the bus.
Jordan Simonovski:
Okay!
Jess Belliveau:
So we thought we'd try and describe to you, first of all, what is observability. Because that's a pretty, the term doesn't give you much of what it is. It gives you a little hint, but it'll be good to base line set what are we talking about when we say what is observability. And then why would a development team want observability? Why would a company want observability? Sort of high level, what sort of benefits you get out of it and who may need it, which is a big thing. You can get caught up in these industry hot buzz words and commit to stuff that you might not need, or that sort of stuff.
Jared Kells:
Yep.
Jordan Simonovski:
Yep.
Jess Belliveau:
We thought we'd talk about some easy wins that you get with observability. So some of the real basic stuff you can try and get, and what advantages you get from it. And then we just thought because we're no going to try and get too deep, we could just give a few pointers to some websites and some YouTube talks for further reading that people want to do, and go from there. So yeah, Jordan you want to-
Jared Kells:
Sounds good.
Jess Belliveau:
Yeah. I hopefully, hopefully. We'll see how this goes! And I guess if you guys have questions as well, that's something we should, if there's stuff that you think we don't cover or that you want to know more, ask away.
Jordan Simonovski:
I guess to start with observability, it's a topic I get really excited about, because as someone that's been involved in the dev ops and SRE space for so long, observability's come along and promises to close the loop or close a feedback loop on software delivery. And it feels like it's something we don't really have at the moment. And I get that observability maybe sounds new and shiny, but I think the term itself exists to maybe differentiate itself from what's currently out there. A lot of us working in tech know about monitoring and the loading and things like that. And I think they serve their own purpose and they're not in any way obsolete either. Things like traditional monitoring tools. But observability's come along as a way to understand, I think, the overwhelmingly complex systems that we're building at the moment. A lot of companies are probably moving towards some kind of complicated distributed systems architecture, microservices, other buzz words.
Jordan Simonovski:
But even for things like a traditional kind of monolith. Observability really serves to help us ask new questions from our systems. So the way it tends to get explained is monitoring exits for our known unknowns. With seniority comes the ability to predict, almost, in what way your systems will fail. So you'll know. The longer you're in the industry, you know this, like a Java server fails in x, y, z amount of ways, so we should probably monitor our JVM heap, or whatever it is.
Jared Kells:
I was going to say that!
Jordan Simonovski:
I'll try not to get too much into-
Jared Kells:
Runs out of memory!
Jordan Simonovski:
Yeah. So that's something that you're expecting to fail at some point. And that's something that you can consider a known unknown. But then, the promise of observability is that we should be shipping enough data to be able to ask new questions. So the way it tends to get talked about, you see, it's an unknown unknown of our system, that we want to find out about and ask new questions from. And that's where I think observability gets introduced, to answer these questions. Is that a good enough answer? You want me to go any further into detail about this stuff? I can talk all day about this.
Jared Kells:
Is it like a [crosstalk 00:08:05]. So just to repeat it back to you, see if I've understood. Is it kind of like if I've got a, traditionally with a Java app, I might log memories. It's because I know JVM's run out of memory and that's a thing that I monitor, but observability is more broad, like going almost over the top with what you monitor and log so that you can-
Jordan Simonovski:
Yeah. And I wouldn't necessarily say it's going over the top. I think it's maybe adding a bit more context to your data. So if any of you have worked with traces before, observability is very similar to the way traces work and just builds on top of the premise of traces, I guess. So you're creating these events, and these events are different transactions that could be happening in your applications, usually submitting some kind of request. And with that request, you can add a whole bunch of context to it. You can add which server this might be running on, which time zone. All of these additional and all the exciters. You can throw in user agency into there if you want to. The idea of observability is that you're not necessarily constrained by high cardinality data. High cardinality data being data sets that can change quite largely, in terms of the kinds of data they represent, or the combinations of data sets that you could have.
Jordan Simonovski:
So if you want shipping metrics on something, on a per user basis and you want to look at how different users are affected by things, that would be considered a high cardinality metric. And a lot of the time it's not something that traditional monitoring companies or metric providers can really give you as a service. That's where you'll start paying insanely huge bills on things like Datadog or whatever it is, because they're now being considered new metrics. Whereas observability, we try and store our data and query it in a way that we can store pretty vast data sets and say, "Cool. We have errors coming from these kinds of users." And you can start to build up correlations on certain things there. You can find out that users from a particular time zone or a particular device would only be experiencing that error. And from there, you can start building up, I think, better ways of understanding how a particular change might have broken things. Or some particular edge cases that you otherwise couldn't pick up on with something like CPU or memory monitoring.
Angad Sethi:
Would it be fair to say-
Jared Kells:
Yeah. It's [crosstalk 00:11:02].
Angad Sethi:
Oh, sorry Jared.
Jared Kells:
No you can-
Angad Sethi:
Would it be fair to say that, so, observability is basically a set of principles or a way to find the unknown unknowns?
Jordan Simonovski:
Yeah.
Angad Sethi:
Oh.
Jess Belliveau:
And better equip you to find, one of the things I find is a lot of people think, you get caught up in thinking observability is a thing that you can deploy and have and tick a box, but I like your choice of word of it being a set of principles or best practices. It's sort of giving you some guidance around these, having good logging coming out of your application. So structured logs. So you're always getting the same log format that you can look at. Tracing, which Jordan talked a little bit about. So giving you that ability to follow how a user is interacting with all the different microservices and possibly seeing where things are going wrong, and metrics as well. So the good thing with metrics is we're turning things a bit around and trying to make an application, instead of doing, and I don't want to get too technical, black box monitoring, where we're on the outside, trying to peer in with probes and checks like that. But the idea with metrics is the application is actually emitting these metrics to inform us what state it is in, thereby making it more observable.
Jess Belliveau:
Yeah, I like your choice of words there, Angad, that it's like these practices, this sort of guide of where to go, which probably leads into this next point of why would a team want to implement it. If you want to start again, Jordan?
Jordan Simonovski:
Yeah, I can start. And I'll give you a bit more time to speak as well, Jess in this one. I won't rant as much.
Jess Belliveau:
Oh, I didn't sign up for that!
Jordan Simonovski:
I think why teams would want it is because, it really depends on your organization and, I guess, the size of the teams you're working in. Most of the time, I would probably say you don't want to build observability yourself in house. It is something that you can, observability capabilities themselves, you won't achieve it just by buying a thing, like you can't buy dev ops, you can't buy Agile, you can't buy observability either.
Jared Kells:
Hang on, hang on. It says on my run sheet to promote Easy Agile, so that sounds like a good segue-
Jess Belliveau:
Unless you want to buy it. If you do want to buy Agile, the [crosstalk 00:13:55] in the marketplace.
Jared Kells:
Yeah, sorry, sorry, yeah! Go on.
Jordan Simonovski:
You can buy tools that make your life a lot easier, and there are a lot of things out there already which do stuff for people and do surface really interesting data that people might want to look at. I think there are a couple of start ups like LightStep and Honeycomb, which give you a really intuitive way of understanding your data in production. But why you would need this kind of stuff is that you want to know the state of your systems at any given point in time, and to build, I guess, good operational hygiene and good production excellence, I guess as Liz Fong-Jones would put it, is you need to be able to close that feedback loop. We have a whole bunch of tools already. So we have CICD systems in place. We have feature flags now, which help us, I guess, decouple deployments from releases. You can deploy code without actually releasing code, and you can actually give that power to your PM's now if you want to, with feature flags, which is great.
Jordan Simonovski:
But what you can also do now is completely close this loop, and as you're deploying an application, you can say, "I want to canary this deployment. I want to deploy this to 10% of my users, maybe users who are opted in for Beta releases or something of our application, and you can actually look at how that's performing before you release it to a wider audience. So it does make deployments a lot safer. It does give you a better understanding of how you're affecting users as well. And there are a whole bunch of tools that you can use to determine this stuff as well. So if you're looking at how a lot of companies are doing SRE at the moment, or understanding what reliable looks like for their applications, you have things like SLO's in place as well. And SLO's-
Jared Kells:
What's an SLO?
Jordan Simonovski:
They're all tied to user experiences. So you're saying, "Can my user perform this particular interaction?" And if you can effectively measure that and know how users are being affected by the changes you're making, you can easily make decisions around whether or not you continue shipping features or if you drop everything and work on reliability to make sure your users aren't affected. So it's this very user centric approach to doing things. I think in terms of closing the loop, observability gives us that data to say, "Yes, this is how users are being affected. This is how, I guess the 99th percentile of our users are fine, but we have 1% who are having adverse issues with our application." And you can really pinpoint stuff from there and say, "Cool. Users with this particular browser or this particular, or where we've deployed this app to," let's say if you have a global deployment of some kind, you've deployed to an island first, because you don't really care what happens to them. You can say, "Oh, we've actually broken stuff for them." And you can roll it back before you impact 100% of your users.
Jared Kells:
Yeah. I liked what you said about the test. I forgot the acronym, but actually testing the end user behavior. That's kind of exciting to me, because we have all these metrics that are a bit useless. They're cool, "Oh, it's using 1% CPU like it always is, now I don't really care," but can a user open up the app and drag an issue around? It's like-
Jess Belliveau:
Yeah, that's a really great example, right?
Jared Kells:
That's what I really care about.
Jess Belliveau:
The 1% CPU thing, you could look at a CPU usage graph and see a deployment, and the CPU usage doesn't change. Is everything healthy or not? You don't know, whereas if you're getting that deeper level info of the user interactions, you could be using 1% CPU to serve HTTP500 errors to the 80% of the customer base, sort of thing.
Angad Sethi:
How do you do that? The SLO's bit, how do you know a user can log in and drag an issue?
Jordan Simonovski:
Yeah. I think that would come with good instrumenting-
Angad Sethi:
Good question?
Jordan Simonovski:
Yeah, it comes down to actually keeping observability in mind when you are developing new features, the same way you would think about logging a particular thing in your code as you're writing, or writing test for your code, as you're writing code as well. You want to think about how you can instrument something and how you can understand how this particular feature is working in production. Because I think as a lot of Agile and dev ops principles are telling us now is that we do want our applications in production. And as developers, our responsibilities don't end when we deploy something. Our responsibility as a developer ends when we've provided value to the business. And you need a way of understanding that you're actually doing that. And that's where, I guess, you do nee do think about observability with a lot of this stuff, and actually measuring your success metrics. So if you do know that your application is successful if your user can log in and drag stuff around, then that's exactly what you want to measure.
Jared Kells:
I think that we have to build-
Jordan Simonovski:
Yeah?
Jared Kells:
Oh, sorry Jordan.
Jordan Simonovski:
No, you go.
Jared Kells:
I was just going to say we have to build our apps with integration testing in mind already. So doing browser based tests around new features. So it would be about building features with that and the same thing in mind but for testing and production.
Jess Belliveau:
Yeah and the actual how, the actual writing code part, there's this really great project, the open telemetry project, which provides all these sort of API's and SDK's that developers can consume, and it's vendor agnostic. So when you talk about the how, like, "How do I do this? How do I instrument things?" Or, "How do I emit metrics?" They provide all these helpful libraries and includes that you can have, because the last thing you want to do is have to roll this custom solution, because you're then just adding to your technical debt. You're trying to make things easier, but you're then relying on, "Well I need to keep Jared Kells employed, because he wrote our log in engine and no one else knows how it works.
Jess Belliveau:
And then the other thing that comes to mind with something like open telemetry as well, and we talked a bit about Datadog. So Datadog is a SaaS vendor that specializes in observability. And you would push your metrics and your logs and your traces to them and they give you a UI to display. If you choose something that's vendor agnostic, let's just use the example of Easy Agile. Let's say they start Datadog and then in six months time, we don't want to use Datadog anymore, we want to use SignalFx or whatever the Splunk one is now.
Jordan Simonovski:
I think NorthX.
Jess Belliveau:
Yeah. You can change your end point, push your same metrics and all that sort of stuff, maybe with a few little tweaks, but the idea is you don't want to tie in to a single thing.
Jordan Simonovski:
Your data structures remain the same.
Jess Belliveau:
Yeah. So that you could almost do it seamlessly without the developers knowing. There's even companies in the past that I think have pushed to multiple vendors. So you could be consuming vendor A and then you want to do a proof of concept with vendor B to see what the experience is like and you just push your data there as well.
Jared Kells:
Yeah. I think our coupling to Datadog will be I all the dashboards and stuff that we've made. It's not so much the data.
Jess Belliveau:
Yeah. That's sort of the big up sell, right. It's how you interact. That's where they want to get their hooks in, is making it easier for you to interpret that data and manipulate it to meet your needs and that sort of stuff.
Jordan Simonovski:
Observability suggests dashboards, right?
Jess Belliveau:
Yeah, perhaps. You used this term as well, Jordan, "production excellence." And when we talk about who needs observability, I was thinking a bit about that while you were talking. And for me, production excellence, or in Apptio we call it production readiness, operational readiness and that sort of stuff is like we want to deploy something to production like what sort of best practices do we want to have in place before we do that? And I think observability is a real great idea, because it's helping you in the future. You don't know what problems you're going to have down the line, but you're equipping your teams to be able to respond to those problems easily. Whereas, we've all probably been there, we've deployed code of production and we have no observability, we have a huge outage. What went wrong? Well, no one knows, but we know this is the fix, and it's hard to learn from that, or you have to learn from that I guess, and protect the user against future stuff, yeah.
Jess Belliveau:
When I think easy wins for observability, the first thing that really comes to mind is this whole idea of structured logging, which is really this idea that your application is you're logging, first of all. Quite important as a baseline starting point, but then you have a structured log format which lets you programmatically pass the logs as well. If you go back in time, maybe logging just looked like plain text with a line, with a timestamp, an error message. Whatever the developer decided to write to the standard out, or to the error file or something like that. Now I think there's a general move to having JSON, an actual formatted blob with that known structure so you can look into it. Tracing's probably not an easy win. That's a little bit harder. You can implement it with open telemetry and libraries and stuff. Requires a bit more understanding of your code base, I guess, and where you want tracing to fire, and that sort of stuff, parsing context through, things like that.
Jordan Simonovski:
I think Atlassian, when you probably just want to know that everything is okay. At a fairly superficial level. Maybe you just want to do some kind of up time on a trend. And then as, I guess, your code might get more complex or your product gets a bit more complex, you can start adding things in there. But I think actually knowing or surfacing the things you know might break. Those would probably be your quickest wins.
Jess Belliveau:
Well, let's mention some things for further reading. If you want to go get the whole picture of the whole, real observability started to get a lot of movement out of the Google SRE book from a few years ago. The Google SRE stuff covers the whole gamut of their soak reliability engineering practice, and observability is a portion of that, there's some great chapters on that. O'Reilly has an observability book, I think, just dedicated to observability now.
Jordan Simonovski:
I think that's still in early release, if people want to google chapters.
Jess Belliveau:
The open telemetry stuff, we'll drop a link to that I think that's really handy to know.
Angad Sethi:
From [inaudible 00:26:12], which is my perspective, as a developer, say I wanted to introduce cornflake use Datadog at Easy Agile. Not very familiar, I'm not very comfortable with it. I know how to navigate, but what's a quick way for me to get started on introducing observability? Sorry to lock my direct job or at my workplace.
Jordan Simonovski:
I would lean, I could be biased here. Jess correct me or give your opinion on this, I would lean heavily towards SLO's for this. And you can have a quick read in the SRE-
Jess Belliveau:
What does SLO stand for, Jordan?
Jordan Simonovski:
Okay, sorry. Buzz words! SLO is a service level objective, not to be confused with service level agreement. An agreement itself is contractual and you can pay people money if you do breach those. An SLO is something you set in your team and you have a target of reliability, because we are getting to the point where we understand that all systems at any point in time are in some kind of degraded state. And yeah, reliability isn't necessarily binary, it's not unreliable or reliable. Most of the time, it's mostly reliable and this gives us a better shared language, I guess. And you can have a read in the SRE handbook by Google, which is free online, which gives you a pretty good understanding of Datadog.
Jordan Simonovski:
I think the last time I used it had a SLO offering. But I think like I was mentioning earlier, you set an SLO on particular functionalities or features of your application. You're saying, "My user can do this 99% of the time," or whatever other reliability target you might want to set. I wouldn't recommend five nines of reliability. You'll probably burn yourself out trying to get there. And you have this target set for yourself. And you know exactly what you're measuring, you're measuring particular types of functionality. And you know when you do breach these, users are being affected. And that's where you can actually start thinking about observability. You can think about, "What other features are we implementing that we can start to measure?" Or, "What user facing things are we implementing that we can start to measure?"
Jordan Simonovski:
Other things you could probably look at are, I think they're all covered in the book anyway, data freshness in a way. You want to make sure the data users are being displayed is relatively fresh. You don't want them looking at stale data, so you can look at measuring things like that as well. But you can pretty much break it down into most functionalities of a website. It's no longer like a ping check, that you're just saying, "Yes, HTTP, okay. My application is fine." You're saying, "My users are actually being affected by things not working." And you can start measuring things from there. And that should give you a better understanding, or a better idea, at least, of where to start with what you want to measure and ow you want to measure it. That would be my opinion on where to get started with this if you do want to introduce it.
Jared Kells:
We're going to talk a little bit about state and how with some of these, like our very front end heavy applications that we're building, so the applications we build just basically run inside the browser and the traditional state as you would think about it, is just pulling a very simple API that writes some things into the database with some authentication, and that sort of stuff. So in terms of reliability of the services, it's really reliable. Those tiny API's just never have problems, because it's just so simple. And well, they've got plenty of monitoring around it. But all our state is actually, when you say, "Observe the state of the system," for the most part, that's state in a browser. And how do we get observability into that?
Jess Belliveau:
A big thing is really, there's not one thing fits all as well. When we talk about the SLO stuff as well, it's understanding what is important to not so much maybe your company but your team as well. If you're delivering this product, what's important to you specifically? So one SLO that might work for me at Apptio probably isn't going to work for Easy Agile. This is really pushing my knowledge, as well, of front end stuff, but when we say we want to observe the state as well, we don't necessarily mean specifically just the state. You could want to understand with each one of those API's when it's firing, what the request response time is for that API firing. So that might be an important metric. So you can start to see if one of those APIs is introducing latency, and so your user experience is degraded. Like, "Hey when we were on release three, when users were interacting with our service here, it would respond in this percentile latency. We've done a release and since then, now we're seeing it's now in this percentile. Have we degraded performance performance?" Users might not be complaining, but that could be something that the team then can look into, add to a sprint. Hey, I'm using Agile terms now. Watch out!
Jared Kells:
That's a really good example, Jess. Performance issues for us are typically not an API that's performing poorly. It's something in this very complicated front end application is not running in the same order as it used to, or there's some complex interaction we didn't think of, so it's requesting more data than expected. The APIs are returning. They're never slow, for the most part, but we have performance regressions that we may not know about without seeing them or investigating them. The observability is really at the individual user's browser level. That makes sense? I want to know how long did it take for this particular interaction to happen.
Jess Belliveau:
Yeah. I've never done that sort of side of things. As well, the other thing I guess, you could potentially be impacted in as well as then, you're dealing with end user manifestations as well. You could perceive-
Jared Kells:
Yeah sure.
Jess Belliveau:
... Greater performance on their laptop or something, or their ISP or that sort of stuff. It'd be really hard to make sure you're not getting noise from that sort of thing as well.
Jordan Simonovski:
Yeah. There are tools like Sentry, I guess, which do exist to give you a bit more of an understanding what's happening on your front end. The way Sentry tends to work with JavaScript, is you'll upload a minified map of your JS to Sentry, deploy your code and then if something does break or work in a fairly unexpected way, that tends to get surfaced with Sentry will tell you exactly which line this kind of stuff is happening on, and it's a really cool tool for that company stuff. I don't know if it'd give you the right type of insights, I think, in terms of performance or-
Jared Kells:
Yeah, we use a similar tool and it does work for crashes and that sort of thing. And on the observability front, we log actions like state mutations in side the front end, not the actual state change, but just labels that represent that you updated an issue summary or you clicked this button, that sort of thing, and we send those with our crash reports. And it's super helpful having that sort of observability. So I think I know what you guys are talking about. But I'm just [crosstalk 00:35:25], yeah.
Jess Belliveau:
Yeah, that's almost like, I guess, a form of tracing. For me and Jordan, when we talk about tracing, we might be thinking about 12 different microservices sitting in AWS that are all interacting, whereas you're more shifting that. That's sort of all stuff in the browser interacting and just having that history of this is what the user did and how they've ended up-
Jared Kells:
In that state.
Jess Belliveau:
In that state, yeah.
Jordan Simonovski:
I guess even if you don't have a lot of microservices, if you're talking about particular, like you're saying for the most part your API requests are fine but sometimes you have particularly large payloads-
Jared Kells:
We actually have to monitor, I don't know, maybe you can help with this, we actually should be monitoring maybe who we're integrating with. It's actually much more likely that we'll have a performance issue on a Xero API rather than... We don't see it, the browser sees it as well, which is-
Jordan Simonovski:
Yeah, and tracing does solve all of those regressions for you. Most tracing libraries, like if you're running Node apps or whatever on your backend. I can just tell you about Node, because I probably have the most experience writing Node stuff. You pretty much just drop in Didi trace, which is a Datadog library for tracing into your backend and your hook itself into all of, I think, the common libraries that you'll tend to work with, I think. Like if you're working for express or for a lot of just HADP libraries, as well as a few AWS services, it will kind of hook itself into that. And you can actually pinpoint. It will kind of show you on this pretty cool service map exactly which services you're interacting with and where you might be experiencing a regression. And I think traces do serve to surface that information, which is cool. So that could be something worth investigating.
Jess Belliveau:
It's funny. This is a little bit unrelated to observability, but you've just made me think a bit more about how you're saying you're reliant on third party providers as well. And something I think that's really important that sometimes gets missed is so many of us today are relying on third party providers, like AWS is a huge thing. A lot of people writing apps that require AWS services. And I think a lot of the time, people just assume AWS or Jira or whatever, is 100% up time, always available. And they don't write their code in such a way that deals with failures. And I think it's super important. So many times now I've seen people using the AWS API and they don't implement exponential back off. And so they're basically trying to hit the AWS API, it fails or they might get throttled, for example, and then they just go into a fail state and throw an error to the user. But you could potentially improve that user experience, have a retry mechanism automatically built in and that sort of stuff. It doesn't really tie into the observability thing, but it's something.
Jared Kells:
And the users don't care, right? No one cares if it's an AWS problem. It's your problem, right, your app is too slow.
Jess Belliveau:
Well, they're using your app. Exactly right. It reflects on you sort of thing, so it's in your interest to guard against an upstream failure, or at least inform the user when it's that case. Yeah.
Jared Kells:
Well, I think we're going to have to call it, this podcast, because it was an hour ago. We had instructed max 45 minutes.
Jess Belliveau:
We could just keep going. We might need a part two! Maybe we can request [cross talk 00:39:21].
Jared Kells:
Maybe! Yeah.
Jess Belliveau:
Or we'll just start our own podcast! Yeah.
Angad Sethi:
So what were your biggest learnings today, given it's been Angad and I are just learning about observability, Angad what was your biggest learning today about observability? My biggest learning was that observability does not equal Datadog. No, sorry! It was just very fascinating to learn about quantifying the known unknowns. I don't know if that's a good takeaway, but...
Jess Belliveau:
Any takeaway is a good takeaway! What about you, Jared?
Jared Kells:
I think, because I we were going to talk about state management, and part of it was how we have this ability, at the moment to, the way our front ends are architected, we can capture the state of the app and get a customer to send us their state, basically. And we can load it into our app and just see exactly how it was, just the way our state's designed. But what might be even cooler is to build maybe some observability into that front end for support. I'm thinking instead of just having, we have this button to send us out your support information that sends us a bunch of the state, but instead of console logging to the browser log, we could be console logging, logging in our front end somewhere that when they click, "send support information," our customers should be sending us the actions that they performed.
Jared Kells:
Like, "Hey there's a bug, send us your support information." It doesn't have to be a third party service collecting this observability stuff. We could just build into our... So that's what I'm thinking about.
Jess Belliveau:
Yeah, for sure. It'll probably be a lot less intrusive, as well, as some of the third party stuff that I've seen around.
Jared Kells:
Yeah. It's pretty hard with some of these integrations, especially if you're developing apps that get run behind a firewall.
Jess Belliveau:
Yeah
Jared Kells:
You can't just talk to some of these third parties. So yeah, it's cool though. It's really interesting.
Jess Belliveau:
Well, I hope someone out there listening has learned something, and Jordan and I will send some links through, and we can add them, hopefully, to the show notes or something so people can do some more reading and...
Jared Kells:
All thanks!
Jess Belliveau:
Thanks for having us, yeah.
Jared Kells:
Thanks all for your time, and thanks everybody for listening.
Jordan Simonovski:
Thanks everyone.
Angad Sethi:
That was [inaudible 00:41:55].
Jess Belliveau:
Tune in next week!
- Podcast
Easy Agile Podcast Ep.15 The Role of Business in Supporting Sustainability Initiatives with TietoEVRY

"It was amazing to talk with Ida and Ulrika from TietoEVRY, they are truly leading the way in sustainability" - Rebecca Griffith
Rebecca and Caitlin are talking with Ida and Ulrika from TietoEVRY, about big picture sustainability and the role of business in supporting sustainability initiatives.
🌍 Implementing sustainability in daily business operations
🌍 The role of technology in advancing sustainability
🌍 Ensuring your sustainability & DEI report doesn't turn into a stagnant document
🌍 Framing challenge in a way of opportunity
🌍 Getting the whole team on boardAn important listen for everyone, enjoy!
📲 Subscribe/Listen on your favourite podcasting app.
Transcript
Caitlin Mackie:
Hi, everyone. Welcome to the Easy Agile Podcast. I'm Caitlin, marketing coordinator at Easy Agile.
Rebecca Griffith:
And I'm Beck, team and operations assistant at Easy Agile, and we'll be your host for this episode. Before we begin, we'd like to acknowledge the traditional custodians of the land from which we broadcast today, the worthy, worthy people of the Tharawal nation and pay our respects to elders past, present and emerging. We extend that same respect to all aboriginal and Torres Strait Islanders people joining us today.
Caitlin Mackie:
Today, we're joined by Ida and Ulrika from TietoEVRY. Welcome. Thanks for joining us.
Ida Bohman Steenberg:
Thank you so much for having us.
Ulrika Lagerqvist Von Unge:
Thank you.
Rebecca Griffith:
It would be great if we could start with some introductions. Ida and Ulrika, could you tell our listeners a bit about yourselves and your role at TietoEVRY?
Ida Bohman Steenberg:
Yes, of course. I'm Ida and I'm heading up the sustainability team at TietoEVRY since four years back. And Ulrika?
Ulrika Lagerqvist Von Unge:
Yeah. I work within the sustainability team as a sustainability manager also here at TietoEVRY.
Rebecca Griffith:
Excellent. Thank you. Thanks for the introductions. Let's jump in. For our listeners who might not be familiar with TietoEVRY, can you give us a bit of an overview about what the company does?
Ida Bohman Steenberg:
Yes. Sure. We are a company based in the Nordics, like very, very far away from sunny Australia. We are a tech company. We provide different solutions. For instance, in software, cloud and infra and also business consulting. I think nowadays, we are the biggest tech provider in the Nordic, at least.
Caitlin Mackie:
Sustainability is a huge part of TietoEVRY. You really have a robust sustainability game plan and your strategy for 2023, which highlights your key priorities for ethical conduct, climate actions and creating an exciting place to work for your employees. Can you elaborate on the sustainability game plan for 2023?
Ida Bohman Steenberg:
Yeah, we would love to. The sustainability game plan is our long term plan that we created last year. We were actually two companies merging into one last year. We had different legacies. X Tieto were good at some things and X EVRY were good at some things, but of course, we had lots of challenges too. We had to sit down and really try to find out what should be our focus going forward and not only actually to build upon what we already have, but also look at the major challenges out there to see like, where do we want to be and what role do we want to have? We created a game plan that is two-folded. We have like the responsible operations that is the traditional sustainability work that you would find at any organization that takes sustainability seriously.
We have the ethical conduct where we have business, ethics, and the corruption, cyber security, privacy, human rights, responsible sourcing, for instance. Then, we have exciting place to work, which is more like HR related because we're people companies, we have to be very good at this in order to attract the right talent and also to keep the talent that we have. We have major challenges when it comes to bringing in and keeping women in our sector, for instance, so we have to be very good at diversity and inclusion and also employee experience, of course, to make this a fun place to work at. Then, of course, climate action may be the one thing that people think about most when they think about sustainability due to the emerging climate crisis. We work a lot with that, of course, and also circular economy and our take on that.
That is like the foundation for us that we have to be very good at like our license to operate, and we work throughout the value chain with these topics, but then because we are a tech company, we also wanted to see what can we do to not only improve our own sustainability performance, but foremost our customers? What's due, I think, and what really stands out for TietoEVRY now is that we have this really, really strong business focus going forward for this sustainability game plan. I was thinking maybe Ulrika could take over and explain and elaborate a little bit about the upper half of the circle.
Ulrika Lagerqvist Von Unge:
Yeah, exactly. What we identified when we were developing this strategy or long term plan was that some of our biggest impacts also actually resides among our customers. We have a lot of capabilities and we have a lot of customers, so why not combine those and see where do we have the biggest opportunity in terms of actually helping our customers to become more sustainable? We developed a methodology where we investigated our capabilities, our customer pain points, our customer opportunities and landed in four broad impact opportunities. That's where we have business opportunities in making our customers sustainable. Those are new focus areas within our sustainability long term plan, where we engage with our own business to drive these areas and develop together with our customers to create positive impact on people, planet and societies.
Ida Bohman Steenberg:
I think also if I may add to that, Ulrika, so we set the plan to do that, and we had of course, a lot to build upon. We had lots of good reference cases, but of course, we needed to pin it down to get the buy-in from management. Also, of course, get the resourcing. We started with identifying those areas where we think that other people have, or other customers or stakeholders have impact opportunities, which means a business opportunity for us. We must not forget that, but in order to actually deliver in a good way and at the speed that our customers require, we also had to create a consultancy team that could help in the delivery organization because the customer requirements become... The pressure was so high.
For our little team group sustainability, we couldn't really handle everything, so we created something that we call the sustainability hit team, which is a consulting team consisting of consultants that knows data and sustainability within business consulting. Ulrika, you have been given also... You have the role of leading this group, perhaps you would like to say something more about that group?
Ulrika Lagerqvist Von Unge:
Yeah. Yeah. Sure. Well, this is a group of people that, just as Ida said, they have this kind of expertise, combining sustainability knowledge with IT and technology. We work together to identify both ongoing projects that might be related to sustainability in one way or the other that we perhaps can scale and create synergies, but we also work to identify new opportunities, having our ears towards the ground and listening into what do the customers actually want to have. Then, we take in these opportunities and try to see how we can develop them to actually support our customers. Hopefully, this team will just continue to grow and us with our other efforts, become very integrated in all our business operations. That is at least our aim, so the responsibility lies where the responsibility is sort to say.
Rebecca Griffith:
That's wonderful. Now, I think you've kind of touched on this in a broader sense, but in the TietoEVRY annual report, you talk about implementation of sustainability into daily business operations. What are some other key ways that you're doing this?
Ulrika Lagerqvist Von Unge:
Yeah. If I can start, Ida?
Ida Bohman Steenberg:
Sure.
Ulrika Lagerqvist Von Unge:
I think one of the most important things is to involve everyone from the beginning in what we actually should focus on and what are the most important topics in terms of sustainability, both for all our stakeholders, but also for our business, so that we actually give the ownership of sustainability to the organization. Not so that they feel it comes from the side or from above, but it's actually something that is relevant and that the organization owns. That means that each and everyone has the responsibility to also contribute to our joint targets that we also have involved the different business leaders and parts of the organization in setting. I think that ownership is a keyword here to actually enable integration of sustainability in the operations. Ida, do you agree?
Ida Bohman Steenberg:
Yeah. No, but the group sustainability, our group, we are a small team consisting of specialists with long experience, but we are only so many, so we have to have a very integrated way of working in order to make this fly. What we've been focusing on a lot since many years back is to get it integrated. For instance, if we look at responsible sourcing, which is crucial how we handle our supply chain. We work closely together with a chief procurement officer. The sustainability goals that we have that are public and that we disclose every year in our annual report is just as much his goals as it is our goals, so we really get some power behind driving it and we get the results that we need in order to move forward. That is one thing. Then, as Ulrika explained earlier in the last question about the sustainability hit team, how we also now have taken this step further to really approach the business in a more structured way that we have done before. As I said, we had very good reference cases and we have a portfolio of sustainability related services, but now we're doing this in a much more structured manner because of the market, the demands that has increased so much.
Caitlin Mackie:
Yeah. That's great. I think what you mentioned, having that structure helps with that company buy in and getting everybody on board and realizing that it's everybody's commitment and it's like a journey you're all on together. Yeah. I think that's great. Something that's often talked about is the overlap between business and sustainability and the role of the business in addressing some of the major challenges we face as a society. I think so many look to clearly distinguish their responsibility and draw a line somewhere, but I'm not so sure that's the right approach. TietoEVRY certainly recognizes they have an important role to play and really pave the way towards carbon neutrality. What's your approach to this?
Ida Bohman Steenberg:
Okay. First of all, I think there must be an overlap or there must be like, if you are a company like we are, we cannot do things that we don't think also is good for us, like financially long term. That is the beauty of sustainability. If you have good and long term targets, it's also support the growth of the company in financial terms, so we always have both those perspectives in mind, creating strategies going forward. For us, we work both for our own operations when it comes to climate change to decrease our carbon footprint, obviously, so we are changing. We have renewable energy in all our data centers and offices. We are now currently at 80% and approaching 100. It's going to be difficult. The last percent is always the most difficult ones, but we have a good development as for now.Then, of course, we work super hard because this is the, I think number one question that our customers is asking for, ways to manage their own carbon footprints. Here we are strong in data, of course. Do you want to add something around that?
Caitlin Mackie:
No, but I think that the first reflection that you had that we have this financial perspective also when developing the sustainability plan, it's important because I think that what we see is that... Our business is doing business. Yes, of course. But if you don't do it right, there will be no business on a dead planet, right? So that you have to have the long term perspective where you take into account all the different aspects. It's not only the financial, because they're also interlinked. I think that also the risks that are connected to, for example, climate change for business operations, so the inbound risks that the surrounding is posing to us are becoming more and more clear. I think that it's also becoming evident that if you don't have sustainability integrated in your operations, you will no longer have a license to operate in 2021 and beyond. I think it's just a smarter way of doing business, to be honest.
Rebecca Griffith:
We can all acknowledge that climate action is one of the biggest global challenges for our generation. In recognizing that this is one of your key priorities to address, how do we take these challenges and frame them in a way of opportunity?
Ida Bohman Steenberg:
Well, this is the beauty of being a tech company. We have the luxury of not having lots of goods that we need to take care of cotton or food or so, so we can go straight to the point, I think, and start to listen to what our customers need and create services and solutions that support them in their journey to decrease their carbon footprint. It sounds very easy when I say it like this. It's not that easy, of course. It requires a lot of hard work and everything, but that's what we should do. I think that when you look at the crisis that is emerging, the tech industry is also seen by the other industries as the great enablers. I think that we have a key role to play. I think that we have a responsibility to our stakeholders to be there and to be in the forefront.
I think that's what we've been doing. For instance, for the last year, the guest team has been working on a very interesting solution called the sustainability hub, which actually addresses this spot on. Would you like to...
Ulrika Lagerqvist Von Unge:
Yeah. Yeah. Definitely. I totally agree with you, Ida. The tech industry, it's really an enabler and that also means that there's a lot of business opportunities. As you said, the sustainability data hub voice, one of our responses to these kind of business opportunities that we see out there, so what happened was that we were sitting and discussing and realized that one of the biggest obstacles for companies to actually integrate sustainability into decision making, into risk management analysis, et cetera, is the lack of data as you have now produced your own ability report, the big hurdles that comes with actually collecting the data for that report, it sits in shattered data sources.
The collection is often manual. The data might not be in the right shape. Most companies actually collect the non-financial data once a year for their annual sustainability report. That means that when you have that data, you are actually steering through the rear view mirror because you are not steering proactively by taking fresh data into account when you take your decisions or plan your operations. What we did was that we started to develop a solutions, which builds on automating the data collection of sustainability data by helping customers to identify where does the data sit? How can we actually automate it? Is it via automation, via IoT solution? Who will use the data? Which KPIs and metrics do we want to map it against? How often do we want the data to be updated? Then, visualize it in real time? A modern way of an ERP system for ESG data, you could say, so that it is actually possible to equate non-financial inform and with financial information.
That should give the opportunity for companies to treat the data in the same manner and actually integrate sustainability into the decisions that they take. For example, let's think about the impact of us going from working at the offices to now working hybrid. What are the actual impacts? Can we see that the sick leave has increased or decreased? How has the carbon emission been impacted by us not traveling back and forth to the offices? If we have that data, we could also use that to decide whether we should continue with hybrid working, or if we should force our employees to come back to the office, or if everybody should be working from home. If you can get hand of that collective view of the activities that you take, you could also make more holistic and informed decisions. That's one response kind of how we try to treat sustainability as a business opportunity and identify which are the pain points that our customers have in terms of co-creating a sustainable future, and where can we tap in into that? That is the kind of beauty, as you said, our industry.
Ida Bohman Steenberg:
It is.
Rebecca Griffith:
Really interesting looking at it in real time, as you said, as opposed to a retrospective assessment of the data, which really, you can't change.
Ulrika Lagerqvist Von Unge:
Exactly. Yeah.
Ida Bohman Steenberg:
Yeah.
Rebecca Griffith:
What's the point in waiting another 12 months to then look at it again when you have completely done [crosstalk 00:18:32]?
Ida Bohman Steenberg:
Yeah. Both sustainability.... Yeah. Sorry. Both sustainability and tech is moving extremely fast. I think we need to work like this. I think customers are going to require... We see more and more before they wanted us to report once a year, but now so many of our customers, they want us to report different types of data related to the solutions or our delivery to them on a quarter basis. The more we can have real time data, I think it's going to be the new normal very soon.
Ulrika Lagerqvist Von Unge:
Me too. That will be a huge game changer for companies. When the data is there, you can get it black on white. There is no excuse for taking bad decisions, right?
Caitlin Mackie:
Yeah. Yeah.
Rebecca Griffith:
Quite exciting.
Caitlin Mackie:
Exactly. I don't know about you, Beck, but I'm definitely sitting here being like, "Wow," at all, like this would've been super handy 12 months ago.
Ulrika Lagerqvist Von Unge:
Yeah.
Ida Bohman Steenberg:
It's out there. Yeah.
Ulrika Lagerqvist Von Unge:
Yeah.
Ida Bohman Steenberg:
It's on the market, so you're more than welcome.
Caitlin Mackie:
All right.
Ulrika Lagerqvist Von Unge:
I think that's also typical from sustainability that you have to understand that the solutions to all of these kind of complex problems, they can't be solved by any actor. We need to work in ecosystems and everybody will have to bring their expertise to the table. Then, we can get things to actually be solved. I hope that that logic will also impact other areas so that we more try to cooperate instead of having the cake ourselves, because then there will be no cake left over. That would be sad.
Caitlin Mackie:
It's so, so refreshing to hear you say that. I think for so long businesses have always had this idea about, "Oh, competition," and like, "Keep what's yours. Keep it to yourself. We're going to succeed in this area." But moving into this space, it's just not about that anymore. It's about how we can collaborate together to reach those solutions. I think that's so powerful.
Ida Bohman Steenberg:
For sure. No. Sustainability is horizontal work. As an organization, as an entity, as a company, we are not stronger than our closest stakeholders anyway. Our performance is very much reliant on their performance.
Ulrika Lagerqvist Von Unge:
I think it's so interesting also because since we come from that kind of background, Ida and I also always working across all silos, across all kind of company functions. We also get a special role in our company because we don't have the legacy of working in silos, so we just totally break them all the time because we're not aware of them. That's just what is needed to be able to get the job done. I think that it's really interesting to see how the organization actually appreciates that.
Ida Bohman Steenberg:
Yes. Sometimes, they don't.
Ulrika Lagerqvist Von Unge:
Sometimes, they don't. Exactly. Sometimes, they don't. Yeah. That's true. Yeah.
Ida Bohman Steenberg:
But we have our battles internally. If you're a sustainability professional working in a big organization, you must be very prepared to have those tougher discussions as well, but we all get there, not always on time from our perspective, but that's the way it has to be. Fearless and just...
Ulrika Lagerqvist Von Unge:
Stubborn.
Ida Bohman Steenberg:
Stubborn, and don't be too bothered about silos or hierarchies or so, because then you will never get anything done.
Caitlin Mackie:
I wanted to highlight or expand on the idea of opportunity and the fact that we constantly need to be exploring new and better ways of doing things so that we can move forward. It would be great to get your thoughts on the role of technology in advancing sustainability. I know you've touched on it, but it'd be great to elaborate.
Ulrika Lagerqvist Von Unge:
If I start, then you can build on it.
Ida Bohman Steenberg:
Sure.
Ulrika Lagerqvist Von Unge:
I think that some of the business opportunities or the solutions that we can develop are cross industrial. For example, the need for data and the need to get hold of it and to visualize it and to be able to act on it, is of course, something that all companies in all industries could make use of. But then, I think that for many solution, they are industry specific. For example, logistic. They need certain solutions to be able to optimize their logistic, their rooting, or to better pack their lorries and trains, et cetera. But I think that... There are both this industry specific solution and this cross sectional business opportunities stuff that you have, and also one of the hidden gems within the IT sector is the side effects of digitalizing services or solutions.
It's also important to understand that even though a solution might not be developed and deployed for the use of mitigating or climate change, for example, the actual impact of its implementation might lead to less carbon emission. Let's think about we have a solution that is called patient engagement. It means that you could engage with your doctors and nurses over your phone, which means that you don't have to take the public transportation or your own car to the hospital or to the medical clinic, which of course saves that transportation and in turn, saves carbon emissions if you travel with something except for an electric car. Many of the digital solutions actually have that positive hand print impact or effect, I would say. Of course, the opportunity of expanding on those is also massive and to identify them, perhaps it's the possibility. If you have a patient engagement app, could you use it for other purposes for other users to increase the impact.
Rebecca Griffith:
At Easy Agile, one of our goals was to establish a baseline and publish our very first sustainability and diversity report, which I believe we've shared with you. We'll also share that report as well as the TietoEVRY annual report in the show notes for our listeners. But what advice would you give to organizations to ensure that these kind of documents don't turn into a stagnant document or a mere check of the box exercise? How do we use these reports to encourage conversation and continually seek ways to improve?
Ida Bohman Steenberg:
Okay. I get so many thoughts now. First of all, keep up with an upcoming frameworks. Don't get stuck in all the good old GRI for instance. In the European Union, so we are now approaching the taxonomy reporting or TCFD or so on. Go for those new ones. Also, of course, everybody has to do the ground work. You have to do your stakeholder engagement, the dialogues, the materiality analysis in order to know that you focus on the right things and so on, and you have to have really concrete goals and action plans and KPIs and everything, so you can measure your performance against the goals that ultimately what sustainability reporting is about. But then, I think the opportunity with reporting, because reporting can be a little bit boring too, in a sense, and it can feel stagnant in a way. It is that it's such an important tool in the strategy work.
This is where you get the attention from the leaders like, "What goals are we going to have and how did we do and so on?" That's where you can have the good discussions or you can also raise the ambition level as you go along. That I think is really crucial. Use it as a strategy tool as well, and then never get stuck in like, "Oh, yeah. It's good. We met our targets. We moved 3% forward or whatever." Don't think so much about that. Think about lie what are the major challenges right now? What is your role as an organization? No matter what organization you are, find your way to be part of the solution instead. We have that discussion sometimes internally. People are like, "Oh, but you're doing so good. You have a good results and so on."
But for me and Ulrika and our sustainability professionals, we're like, "Yeah. Okay. We move forward. That's good." But from a greater perspective where we are reaching the tipping point for the planet, so we feel other pressure in order to move forward faster. Don't end up in like, "Yeah. We move forward. We're keeping the pace." Full on power ahead, and speed is of essence going forward.
Ulrika Lagerqvist Von Unge:
Yeah. No, I fully agree. I think that's really good reflections to hook the sustainability reporting up on the challenges to understand. What are the purposes? What are we actually trying to achieve by this report? We are trying to contribute to minimize the negative impact and to increase the positive impact, and the sustainability report is a tool for that. I think another thing that is really important is to actually also engage with the organization to get them define their own targets and their own metrics to report on, so that they feel ownership. For some of the areas that we have in our sustainability report, when we have an engaged partner within the organization that themselves have ideas on targets, we develop their own KPIs.
They feel that, "I really believe in this. I want to work with this." Then, the follow up and the continuous reporting is much easier than while we have perhaps other parts of the organization where there isn't so much clear targets internally, so that the sustainability report is more felt like something that is done on an annual basis just collecting the data, but not making use of it actually. Just create that commitment and build on the company's own targets and own KPIs that are useful. Then, of course, sometimes if you do report according to a sustainability framework such as the GRI standards, which is commonly used in Europe, then you, of course, need to report according to some of the metrics in that standard, but then add your own key guides, your own metrics, because that will make the organization feel engaged, I could say.
Ida Bohman Steenberg:
Yeah. Yeah. Basically to summarize that, so three things, do the groundwork according to the upcoming and fresh frameworks, and then two, use it as a strategic tool to have those important discussions with management and make it a part of the overall strategy, so you don't end up with the sustainability strategy and an overall strategy. Then, three, be bold. Look at the challenges and not only what's doable or keeping the trend or whatever. Those three things, I think is important to have in mind.
Rebecca Griffith:
Spot on.
Caitlin Mackie:
Yeah. I love that. I think that's great advice, especially the idea of you're mapping out what you're doing internally and what that looks like, but being able to take that step back and say, "Okay. But what does this contribute to in the big picture? What are we actually helping and what are we doing to move in the right direction?" Something that I often think about is things like the UN sustainable development goals and looking at those and being like, "Well, what can we do to of map where we are at and where can we offer? What can we be doing in this space that helps reach those targets?" Yeah. Great advice. I love it. But I think just to wrap us up, our last question for both of you is looking forward, what keeps you hopeful?
Ida Bohman Steenberg:
It keeps me hopeful. Well...
Ulrika Lagerqvist Von Unge:
For me, I think the younger generation, to be honest. I think that seeing my brothers' daughters that are teenagers, or to see [inaudible 00:31:19] and the commitment that she's able to steer up, I think that gives me hope that things will move faster in the future. I think that's positive.
Ida Bohman Steenberg:
Yeah. I also second that. I think I visited the school last week with students like 18, 19 years old, and I've been doing that every year for a couple of years now and I always ask them, "What do you know about sustainable? What do you think about it?" Before, it was like, "Yeah. The environment or recycling maybe," but now they were like, "Yeah. The UN SDGs..." So the level of knowledge has increased so much. There is huge interest and when I gave them, "What can you do on a practical level if you want to live a more sustainable life?" They were like, "Yeah. Don't buy a new party cup for the Friday night. Borrow from your friends, or there are these sites. I can text you these sites where you can borrow dresses and stuff like that." They are doing it in real life in such a good way where they combine technology and sustainability, so they're much more tech savvy than we are. I was very inspired by that.
Ulrika Lagerqvist Von Unge:
They're also willing to actually sacrifice stuff. It's like, "No, we don't fly. We don't do this because we would like to have a future to live in." I think that that is something which we are so comfortable and so used to having a certain lifestyle, but they are perhaps not and they are challenging that lifestyle that we have been having, which has also led to where we are today.
Ida Bohman Steenberg:
I think also to add to that, I think that finally the leaders of our countries are getting it, at least getting close to getting it. I think things are changing, so that's good, but my hope stands to the young ones still.
Rebecca Griffith:
It's nice to feel that it's becoming a normal part of consciousness for the newer generations where it's something that we had to learn to appreciate and respect and to take action on, but it seems to be a part of their upbringing and a way of life now, which is great.
Caitlin Mackie:
Well, I think that's great. I think it's great to leave the episode on such a high and leave the audience with a bit of inspiration moving forward. Thank you both for taking the time to chat with us and sharing your expertise with the Easy Agile audience.
Ida Bohman Steenberg:
Thank you so much for having us. It was fun to talk to you, and it's nice also to talk about the perspectives from the Nordics and from the tech industry. Thank you very much.
Rebecca Griffith:
Thank you.
- Podcast
Easy Agile Podcast Ep.20 The importance of the Team Retrospective
"It was great chatting to Caitlin about the importance of the Team Retrospective in creating a high performing cross-functional team" - Chloe Hall
In this episode, I was joined by Caitlin Mackie - Content Marketing Coordinator at Easy Agile.
In this episode, we spoke about;
- Looking at the team retrospective as a tool for risk mitigation rather than just another agile ceremony
- The importance of doing the retrospective on a regular cycle
- Why you should celebrate the wins?
- Taking the action items from your team retrospective to your team sprint planning
- Timeboxing the retrospective
- Creating a psychologically safe environment for your team retrospective
I hope you enjoy today's episode as much as I did recording it.
Transcript
Chloe Hall:
Hi, everyone. Welcome to the Easy Agile Podcast. I'm Chloe, Marketing Coordinator at Easy Agile, and I'll be your host for today's episode. Before we begin, we'd like to acknowledge the traditional custodians of the land from which I am recording today, the Wodi Wodi people of the Dharawal Speaking nation and pay our respects to elders past, present, and emerging. We extend that same respect to all Aboriginal and to Strait Islander peoples who are tuning in today. So today, we have a bit of a different episode for you. I'm going to be talking with Easy Agile's very own Content Marketing Coordinator, Caitlin Mackie. Caitlin is the Product Owner* of our Brand and Conversions Team*. Now this team is a cross-functional team who have only been together for roughly six months. And within their first few months, as a team, mind you they also had two brand new employees, they worked on a company rebrand.
Chloe Hall:
A new team, a huge task, the possibility of the team being high performing was unlikely at this point in time. So, the team was too new to have already formed that trust, strong relationships, and psychological safety, but somehow they came together and managed to work together, creating a flow of continuous improvement and ship this rebrand. So, I've brought for you today Caitlin onto the podcast to discuss the team's secret for success. Welcome to the podcast, Caitlin.
Caitlin Mackie:
Thanks, Chloe. It's a bit different sitting on this side. I'm used to being in your shoes. I feel [inaudible 00:01:45]. I feel uncomfortable. [inaudible 00:01:46].
Chloe Hall:
Yeah. It's my first time hosting as well, so very strange. Isn't it? How are you feeling today?
Caitlin Mackie:
Yeah. Good. I'm excited. I'm excited to chat about our experience coming together as a cross-functional Agile team, and hopefully share some of the things that worked for us with our listeners.
Chloe Hall:
Yes, I know myself, and I'm sure our audience is very excited to hear what your team's secret to success was. Did you want to start off by telling us what was this big secret that really helped you work together as a team?
Caitlin Mackie:
That's a great question, Chloe. And that's a big question. I'm not sure if there's one key thing, I suppose, it is that ultimate secret source or that one thing that led to the success. I'm sure we all want to hear what that is. I would also love to know if there's just this one key ingredient, but I think something for us, and probably one of the most memorable things that really worked for us, and there was a lot for us to benefit from doing this, was actually doing our retrospectives. So that's probably the first thing that comes to mind when it comes to what led to our success.
Chloe Hall:
Okay. Yeah. In the beginning, why did you start doing the retrospectives?
Caitlin Mackie:
So, we were a new forming team, like you mentioned before, and we seen retrospectives as another Agile ceremony, and we saw other teams doing it and they were having a lot of success from it, so we became to jump on that bandwagon. And I think with being a new forming team, there are so many things that come into play. So, you're trying to figure each other out, how we all like to work and communicate with each other, all of that. And we were the first ever team dedicated to owning and improving our website. And we also knew it was likely that we'd be responsible for designing and launching a rebrand.
Caitlin Mackie:
So when you try and stitch all of that together, and then consider all those elements, we knew that we needed to reserve some time to be able to quickly iterate and call out what works and what doesn't. And what we did understand is that retrospectives are a great opportunity for the whole team to get together and uncover any problematic issues and have an open discussion aimed at really identifying room for improvement, or calling out what's working well, so we can continue to do that. So, I think retros allowed us to understand where we can have the most impact and how to be a really effective cross-functional Agile team.
Chloe Hall:
Wow. That is already so insightful. Yeah, it sounds like the retrospectives really helped you to gain that momentum into finding who your team is, becoming a well-working, high-performing cross-functional team. So, how often were you doing the retro? Were you doing this on a regular cycle, or was it just, "Okay. We have a problem. Some blockers have come up, we need to do a retro"?
Caitlin Mackie:
Yeah. I think initially retro, we kind of viewed retros as this thing where like, "Oh, we've done a few sprints now. We should probably do a retro and just reflect on how those few sprints went." It was kind of like this thing. It was always back of our mind. And we knew we needed to do it, but weren't really sure about the cadence and the way to go about it. So now, we do retros on a Friday morning, which is the last day of our weekly sprint. And then we jump into sprint planning after that. So after bio break as well, so let the team digest everything we talked about in retrospectives. And then we come into sprint planning with all the topics that we're discussed, and we will have a really nice, fresh perspective.
Chloe Hall:
Yeah.
Caitlin Mackie:
So, I think this works really well for us because everything is happening in a timely manner. We've just had a discussion about the best things that happened in the sprint or what worked really well, so you want to make sure you can practice the same behavior in the following, and vice versa for the improvements that you want to make. So, that list of action items that come out of a retrospective provide a really nice contact, context, sorry. And you have them all in mind during sprint planning.
Caitlin Mackie:
So for example, in the previous sprint, it might have come up that you underestimated your story points or there wasn't enough detail on your user stories. So, with each story or task that you are bringing into the sprint, you're then asking the question, is everyone happy with the level of detail? What are we missing? Or we've only story pointed this or two, is it more likely to be a five? So, everything is really fresh in your mind, and I definitely think that helps create momentum. When you've got the whole team working to figure out how you can be more effective with every sprint.
Chloe Hall:
That's such a great point that you just made Caitlin. And I love how going from doing the team retrospective, that you actually can take those action items and go into your sprint and put them into place straight away. It's really good. Otherwise, I feel like if you do the sprint retrospective on the Friday, and you're like, "Okay, these are our action items," get to Monday sprint planning and you're just thinking of the weekend. That [inaudible 00:07:20]
Caitlin Mackie:
Yeah, a hundred percent. Yeah. They're super fresher mind for everyone. So, it might not work for every team, but we find it works really well for us, because we're being really deliberate with how we approach sprint planning.
Chloe Hall:
Yeah. And then with that, I could see how doing the retro, how it could easily go over time, but then your team has sprint planning scheduled after. So, it's like you can't go over time. How have you managed to kind of time box that retrospective?
Caitlin Mackie:
Yeah, that's a really, really good question. And it is on purpose as well that they are scheduled closely together. Som as mentioned above, the discussion you've had in the retrospectives provides a nice momentum going to the sprint planning, but it does mean we have to watch the clock. And initially, this can be quite awkward, because you want to make sure that everyone feels heard and that everybody has the same opportunity to contribute. And I think this responsibility falls on the scrum master, or the product owner, or whoever's facilitating the retrospective to call it out and make sure everyone has the chance to be heard. You'll naturally have people tell the longer story or add a lot of extra context before getting to the point. And then you'll have others that will be a lot more direct. And I'm a lot like the latter. I struggle to get to the point, which doesn't work well when you're trying to time box a retrospective, right?
Chloe Hall:
And I can relate, same personality.
Caitlin Mackie:
Yes. So with this, I think it really comes down to communicating the expectation and the priority from the get go. With our team and with any team, you will want to figure out who you can perform really well and continually improve to exceed expectations and be better and learn and grow together. And I think if you all share that same mindset going into the retrospective and acknowledging that it's a safe
space to have difficult conversations. And as long as you're communicating with empathy, the team knows that it's never anything personal, and it's all in the best interest of the team. And that then helps the less direct communicators, like myself, address their point more concisely and really forces them to be more deliberate and succinct with their communication style.Caitlin Mackie:
And that's really key to being able to stick to that time box, I think. And it does take practice, because it comes down to creating that psychological safety in your team. But once that's there, it's so much easier to call out when someone's going down a windy track, and bring the focus back and sort of say, "I hear you, what's the action item?" And just become a lot more deliberate.
Chloe Hall:
Wow. I couldn't even imagine like how hard it would be, with the personalities that yourself and I have, just trying to be so direct and get rid of all the fluffy stuff. I mean, look at what it's done to form such an amazing team that we have. So, you mentioned that aspect of psychological safety before. And how do you think being in a new cross-functional team... Only six months together, you had those new employees, do you think you were able to create a psychological safety space at any point?
Caitlin Mackie:
That's another fantastic question. And I feel like, honestly, it would be best to have a team discussion around this. It'd be interesting to hear everybody's perspectives around what contributes to that element of psychological safety and if everybody feels the same. So, I can't speak for the team, but my personal opinion on this or personal experience is that creating an environment of psychological safety really comes down to a mutual trust and respect. And at the end of the day, we all share the same goal. So, we all really, really respect what each other brings to the table and understand how all of these moving parts that we are working on individually all come together to achieve the goal. So, when we're having these open discussions in retros, or not even in retros, just communicating in general really, it's clear that we're asking questions in the best interest of the team and individual motives never come into play, or people aren't just offering their opinion when it's unwarranted or providing feedback, or being overly critical when they weren't asked to do so.
Caitlin Mackie:
So, none of those toxic behaviors happen, because we all respect that whatever piece of work is in question or the topic of discussion, the person owning that work, at the end of the day, is the expert. And we trust them, and we don't doubt each other for a second. And I think the other half of that is that we're also really lucky that if something doesn't go as we planned, we're all there to pick each other up and go again. So, this ties quite nicely into actually one of our values at Easy Agile is commit as a team. And this is all about acknowledging that we grow and succeed when we do it together, and to look after one another and engage with authenticity and courage. Som I may be biased, but I wholeheartedly believe that our team completely embraces that. And there's just such an admiration for what we all bring to the table, and I think that's really key to creating the psychological safety.
Chloe Hall:
I love that your team is really embracing our value, commit as a team and putting it into place, because that's what we're all about at Easy Agile, and it's just so great to see it as well. I think the other thing that
I wanted to address was... So again, during this cross functional team, and you've got design and dev, how do you think retros assisted you in allowing to work out what design and dev needed from each other?Caitlin Mackie:
For sure. So, for some extra context for our listeners as well, so in our team, we've got two developers, Haley and David, and a designer, Matt and myself, who's in the marketing. So, we're very much a cross-functional little mini team. So, we all have the same goal and that same focus, but we also are all working on these little individual components that we then stitch together. So,, I think... We doing retros regularly. What we were able to identify was a really effective design and development cycle. So, we figured out a rhythm for what one another needed at certain points. For example, something we discovered really early was making sure that we didn't bring design and dev work into the same sprint. We needed to have a completely finished design file before dev starts working on it. And that might sound really obvious, but initially we thought, "Oh, well, if you have a half finished design file, dev can start working on that. And by the time that's done, the rest of the design file will be done."
Caitlin Mackie:
But what we failed to acknowledge is that by doing that, we weren't leaving enough capacity to iterate or address any issues or incorporate feedback on the first part of that design file, or if dev started working on it and design then gets told, "Oh, this part right here, it's not possible," so the designer is back working on the first part. And it just creates a lot of these roadblocks. So in retros, this came up and we were able to raise it and understand that what design needed from dev and what dev needed from design in order to make sure we weren't blockers for each other. And the action item out of the retro is that we all agreed that a design file had to be completely finished before dev picks up the work.
Chloe Hall:
I think it's so great that you were able to identify these blockers early on. Do you think like doing the retro on a weekly reoccurring basis was able to bring up those blockers quickly, or do you think it wouldn't have made a difference?
Caitlin Mackie:
No, definitely. I, a hundred percent, think that retros allowed us to address the blockers in a way more timely and effective manner. And we kind of touched on that before, but yeah, retros let you address the blockers, unpack them, understand why they're happening and what we need to do to make sure they don't happen again. So, for sure.
Chloe Hall:
Yeah. Yeah. I guess I want to talk a little bit now about the wins, the very exciting part of the retro, the part that we all love. So, how important do you think the wins are within the retro?
Caitlin Mackie:
So important. So, so, so important. It's like, when you achieve something epic as a team, you have to call it out. Celebrate all the wins, big, small. Some weeks will be better than others, but embrace that glass half full mentality. And there's always something to be proud of and celebrate, so call it out amongst
each other, share it with the whole company, publicly recognize it. Yeah, I think it's so important to embrace the wins. It just sort of creates a really positive atmosphere when you're in the team, makes everybody feel heard and recognized for their really positive contribution that they're making. And I think a big thing here as well is that if you've achieved something epic as a team, it's helpful for other teams to hear that as well, right? You figured out a cool new way to do something, share it. If it helped you as a team, it's most likely going to help another team.Caitlin Mackie:
So I think celebrating the wins isn't even just reserved for work stuff either, right? If somebody's doing something amazing outside of work or hit a personal goal, get behind it.
Chloe Hall:
Yeah.
Caitlin Mackie:
To celebrate all the wins always.
Chloe Hall:
Yeah. And I think it's so good how you mentioned that it's vital to celebrate the wins of someone's personal life as well, because at the end of the day, we're all human beings. Yes,, we come to work, but we do have that personal element. And knowing what someone's like outside of work as well is an element to creating that psychological safe space and team bonding, which is so vital to having a good team at the end of the day. Yeah.
Caitlin Mackie:
Yeah, a hundred percent. Yeah, you hit the nail in the head with that. We talked about psychological safety before, and I definitely think incorporating that, acknowledging that, yeah, we are ourselves at work, but we also have a whole other life outside of that too, so just being mindful of that and just cheering each other on all the time. That's what we got to do, be each other's biggest cheerleaders.
Chloe Hall:
Yeah, exactly. That's the real key to success. Isn't it?
Caitlin Mackie:
Yeah, that's it. That's the key.
Chloe Hall:
So, you've been working really well as a new cross functional, high performing Agile team. How do you think... What is your future process for retros?
Caitlin Mackie:
We will for sure continue to do them weekly. It's part of the Agile manifesto, but we want to focus on responding to change, and I think retros really allow us to do that. It's beneficial and really valuable for
the team. And when you can set the team up for success, you're going to see that positive impact that has across the organization as a whole. So yeah, we've found a nice cadence and a rhythm that works for us. So, if it ain't broke, don't fix it.Chloe Hall:
Yeah.
Caitlin Mackie:
Is that what they say? Is that the saying?
Chloe Hall:
I don't know. I think so, but let's just go with it. [inaudible 00:19:02], don't fix it.
Caitlin Mackie:
There we go. Yeah.
Chloe Hall:
You can quote Caitlin Mackie on that one.
Caitlin Mackie:
Quote me on that.
Chloe Hall:
Okay, Caitlin. Well, there's just one final thing that I want to address today. I thought end of the podcast, let's just have a little bit of fun, and we're going to do a little snippet of Caitlin's hot tip. So, for the audience listening, I want you to think of something that they can take away from this episode, an action item that they can start doing within their teams today. Take it away.
Caitlin Mackie:
Okay. Okay. All right. I would say always have the retrospective. Don't skip it. Even if there's minimal items to discuss, new things will always come up. And you have to regularly provide ways for the team to share their thoughts. And I'll leave you with, always promote positive dialogue and show value and appreciation for team ideas and each other. That's my-
Chloe Hall:
I love that.
Caitlin Mackie:
That's my hot tip.
Chloe Hall:
Thanks, Caitlin. Thanks for sharing. I really like how you said always promote positive dialogue. I think that is so great. Yeah. Well, thanks, Caitlin. Thanks for jumping on the podcast today and-Caitlin Mackie:
Thanks, Chloe.
Chloe Hall:
Yeah. Sharing your team's experience with retrospectives and new cross functional team. It's been really nice hearing from you, and there's so much that our audience can take away from what you've shared with us today. And I hope that we've truly inspired everybody listening to get out there and implement the team retrospective on a regular basis. So, yeah, thank you.
Caitlin Mackie:
Thank you so much, Chloe. Thanks for having me. It was fun, fun to be on this side. And I hope everyone enjoys this episode.
Chloe Hall:
Thanks, Caitlin.
Caitlin Mackie:
Thanks. Bye.



