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The Role of Being Technical in Technical Leadership

Sasha Rezvina
Nov 15, 2017
7 min read

In July, we hosted the first annual Code Climate Summit, a one-day conference for leaders of engineering organizations who want to better themselves, their processes, and their teams.

Today we’re sharing The Role of being Technical in Technical Leadership, by Camille Fournier, Managing Director at Two Sigma.

Transcript of talk

Camille Fournier: Hi everyone, I am excited to be here at this Code Climate Summit. We were customers of Code Climate when I was at Rent the Runway, so I’m a huge fan of the product and I was very honored to be invited to come speak.

This is a talk about engineering management, which I think is pretty important for building effective engineering teams and building good products. We’re going to talk about what actually what it means to put the engineer in engineering management.

Before I begin, of course, I must give a pitch to Two Sigma, so I am as of about four months ago, the head of platform engineering at Two Sigma. Two Sigma is a financial company here in New York. Our engineers and modelers harness data at tremendous skill, use machine learning, distributed computing, and other technologies to build powerful predictive models. If you are interested in that world, twosigma.com/careers, check it out.

Okay. So. Let’s get this really started. “You either die an engineer or live long enough to see yourself become the business person.” This something my friend Cliff Moon at some point said or tweeted, probably both, and I like this quote not just because it’s kind of funny, but also because I think it really summarizes the struggle that many people have when they think about engineering management. “Am I still an engineer, or have I suddenly become a business person?”

I personally have struggled with this, so this is how I have a lot of empathy with this. I started out my career as a hands-on engineer, I guess as most people do. I was hands-on for a really long time, building lots of different kinds of systems, mostly distributed systems.

I actually just got photographed for something called Faces of Open Source, it’s facesofopensource.com, which is taking pictures of various people in the open source community. It was a cool experience and this is the photo that came out of that.

So, I’ve spent a long time as a hands-on engineer. At some point in my career I was like, “Oh, I want to do more, I want more power, I want more authority.” Lots of bad reasons, but I decided that I wanted to go into management, so I joined a startup as a director of engineering, and I was still actually writing a lot of code for the first year or so I was there.

As the startup grew – and that startup was, of course, Rent the Runway – as that startup grew and was successful, and I was fortunate to be growing and be successful along with it, I hit that dreaded cliff of no more coding, where I really had to stop coding.

We tell managers that this will happen. Sometimes we tell them a little too early in my opinion. I actually think it’s okay for you to write some code when you have a small team, but there is certainly a point where if you are writing code as a manager, you’re probably avoiding doing more important work, like talking to people, and planning things, and other kinds of things that make teams successful.

It’s still hard. It’s really hard if you’ve been a programmer for a long time, if you’ve been a hands-on person for a long time, hitting that cliff of no coding is really painful. I remember, it probably took me like a year of angst before I finally got over it.

We say a lot of things about management, we call it a career change and now that you’re a manager, you’re no longer an engineer anymore. I have probably said this myself, and while I think it’s kind of true, I also really love the language that we use when we say this, because it’s also kind of a negative way to frame things.

I wrote a book and you all have copies of it, which is cool. I’m very flattered that they decided to give my book as a giveaway here. This book is about being an engineering manager. It’s about the various stages of engineering management.

Part of the reason that I wrote this book was that I felt that there was not a lot out there that really walked the path of being all the way from a mentor and early career leader, but definitely still a hands-on engineer, all the way through to being something like a CTO or a VP of engineering or a senior executive.

I also wrote this book because I have a thesis that is, among other things, while the people side of management is really important, managers also need to be technical. I think that there is a reason that we tend to promote technical people into management roles. It’s not just because we want to punish them.

Engineering management is the intersection of engineering and management.


It’s that, engineering management is the intersection of engineering and management. It is not just managing a bunch of people who happen to be engineers. It is important that you, to be a really successful engineering manager, understand the way that people do their work. You are able to guide their technical decisions.

This doesn’t mean you’re making decisions for them. In fact, most of the time, I don’t really make all that many decisions. I try to ask good questions and guide my teams, but I’m not actually making decisions for them. The hands-on people who are doing the work are making the decisions, but I still need to understand the context in which they are operating. That context includes what it is like to be an engineer.

This talk is going to cover three traits that I believe are overlapping traits that you tend to find in great senior engineers, and the way that these traits translate into what makes good engineering managers. I’m going to talk about debugging, I’m going to talk about empathy, and I’m going to talk about judgment.

Debugging

Let’s start with debugging. I love debugging. I don’t know about all of you, I’m sure some of you do and some of you don’t. It’s definitely not the thing that every single engineer loves to do, but it’s something we all have to do because

I’m sure you’ve probably forgot a semi-colon the first time you wrote hello world.

We’re always debugging all the time. Things are always breaking and you’re always having to debug, and as you become more and more of a senior engineer, you experience more, new, interesting ways that things can fail. You start to sense the vast possibility of causes behind failures.

Part of the reason that I went into management is actually the same reason that I love debugging. I wanted to understand why things were happening. I started asking why a lot. Why is this happening? Why are we doing this? Why do we do this process this way? Why didn’t we fix this? Why didn’t we make this choice? Why, why, why, why?

Asking why too much, it turns out, is a not uncommon way that people end up becoming managers, because they want to know. They want to know not just about what is causing systems to behave in a certain way, but they also want to know what’s causing us to make decisions this way in the first place.

At the end of the day, this skill set overlap is what a lot of people call “systems thinking”. It’s not my favorite term, but I like the concept. People that are good at seeing the interactions of different kinds of systems that you may not have perfect information into. When you’re talking about looking at the interactions of people, you can’t read people’s minds. You can only go by what they tell you.

You don’t always have perfect insight even into the software systems you’re developing. People who are good at seeing in systems, are good at debugging, and they tend to become good managers for the same reason, because, guess what, as a distributed systems engineer, the system is slow, it’s probably the hardest problem you’ll ever have to debug, and as a manager, the team is slow.

“The team is slow” is the hardest problem you’ll ever debug.

It’s probably the hardest thing you’ll ever need to debug, especially if you happen to be working at a startup for a CEO, especially if the CEO is not technical. But e*ven if the CEO is technical, frankly, they always want to know, “Why aren’t we getting it done faster. Why aren’t we moving faster. Why isn’t this release done? Why haven’t we finished this?”

To figure this out, you have to look across a bunch of different elements. You have to look at the people, sometimes as humans, we move slowly because people are unmotivated for whatever reason. They’re burned out, they’re tired. They don’t get along. The team hasn’t actually gelled all that well. You’ve got somebody that’s very disruptive. They just can’t agree on the way to do something.

Sometimes, of course, the challenge is a process problem. You’ve got this product management team that thinks that they’re mini demi-gods over here, throwing work over the wall to the engineering team and saying, “Behold my brilliance, go implement it.” And most engineering teams don’t really like that, it can be very demotivating, although some of them do. You’ve got to understand what process, what’s the process contributing to the team’s slowness.

And of course, sometimes it’s the systems. Sometimes you really are dealing with really hairy, nasty technical problems that are going to take a long time to figure out. They’re going to take a long time to solve.

You as an engineering manager, have moved beyond the world where you’re thinking about the interactions of software systems all the time, but you’re still looking at system interactions. You’re looking at the interactions of the systems of the humans and the processes that the humans are using and the technology that they’re having to deal with to get their job done every day.

Empathy

The second characteristic is empathy. We talk about empathy a lot. It was already spoken of quite a bit in the last talk. I think it’s a very popular thing to talk about in technical circles these days, which is probably pretty good, because for a long time we had this very robotic approach to technology. Programmers want to go and close the door and be in silence and just thinking about computers. We do realize that to really build effective products, we need to care about our customers and to build effective teams, we need to care about our teammates, and as a manager, we want people who appreciate people. But, there’s a little more to it than that.

There was a study done recently that showed that the number one contributor to workplace happiness that they measured, was actually whether or not they believed their boss was highly competent. Highly competent could mean a few different things. Highly competent could mean the boss could do your job, but highly competent could also mean a domain expert in the field.

It’s very clear though, that people really do want highly competent bosses, and frankly I feel the same way. I get to work for this guy, his name is Alfred Spector, he is the CTO at Two Sigma. He was a professor of computer science for a long time, actually started a company, then became a lead scientist at IBM. He ran Google Research for a very long time before coming to Two Sigma. He’s a very interesting person. He has a really incredible technical computer science background, he’s a good manager, which is amazing, and he’s entrepreneurial. All of those things are awesome, and I’m really excited to get to work for someone like that. I want to work for someone that I believe is highly competent and has shown a track record of doing great things.

That doesn’t mean that I expect him to sit down next to me and pair program. That actually doesn’t mean that you as a manager are going to be spending all of your time actually in the weeds of the technology, coding with your team.

So what does it really mean to say that we want someone who possesses technical empathy? What does this empathy element mean for managers beyond just, you can see how people are feeling?

I think it really means that you want someone who appreciates the work, someone who appreciates the details of the work and why work is good or bad. Your manager is often the person who evaluates you, who is evaluating your work and saying who’s doing well and who’s not doing well, maybe even who’s going to get promoted. You want that person to actually be able to tell the difference between somebody who does high quality work and someone who doesn’t.

You also just want that feeling of the expert appreciation. It means more when you respect someone’s opinion that they have a high opinion of you. We want someone who really appreciates why our work is hard, why our work is done well, maybe even, sometimes is able to give us suggestions about how to do it better. But certainly, we at least want that appreciation.

It’s also good as a manager, to be able to appreciate what your teams are going to be excited about. Different people are excited about different things, but engineering teams tend to get excited about slightly different kinds of problems than marketing teams or sales teams. Engineering is a special discipline with its own rules, with its own challenges and we want managers who can appreciate and identify interesting problems and direct us towards those interesting problems and make us feel like they understand what the wider tech world is excited about and can actually help us get to do some of those exciting things. Even more importantly of course, we want managers who appreciate what frustrates engineers. It’s not obvious to a non-engineer, what parts of the job are stressful. It just isn’t. It’s very hard to understand how stressful it is to get distracted or pulled away from your code every 15 minutes because somebody keeps coming over to talk to you over your shoulder.

That can be a hard thing for people to understand. It’s much easier with a technical manager, at least someone who appreciates what the work is like, to be able to predict those frustrations and therefore cut them off before they start happening.

Technical Judgment

Last but not least, there’s the matter of technical judgment, which is of course, very important in senior engineers. I said before that technical management is often the art of guiding technical decision making. It’s not making the decisions yourself, but even when you have a very strong tech lead or architect or whatever and a great product manager, what you will often find as an engineering manager is that you are the person sitting in the middle of those two and trying to balance those differing viewpoints.

You need to make sure that you are actually taking into account the full context of both the technical and the business side in order to help the team prioritize their work. Because ultimately, the technical decisions that are made will impact the effectiveness of the team, and the effectiveness of the team as a manager is definitely your job.

A lot of the people in their first go round of engineering management try to apply just the process to things. They say, “Oh, I know the process that will solve it.” It can be anything from we’re going to do OKRs, we’re going to have engineers vote on whatever project they want to work on, we’re going to do agile, scrum, kanban, whatever style project management you want to do.

I actually think process is useful and different processes work well for different teams, but there’s a lot of nuance. You have to understand what process is going to work for your team. Moreover, you’ve got to remember that process does not make decisions for you. The best thing process does is provide the context, again, all of the information at your fingertips with the right people in the room, to help you make decisions.

One quote I use in my book is that a good political idea is one that works well in half-baked form, which I believe is from some kind of economics blog. I believe the same is true for a process. Good processes are going to work well in half-baked form. As an engineering manager, you’ve got to understand how to get something that works well for your team, but it’s not going to be the magical decider of all your difficult technical decisions.

Good senior engineers and good engineering managers have a good eye for detail. They can be detail oriented when they need to be, because ultimately, building good software systems is all about the details. It’s all about understanding the details of the problem you’re solving and accounting for those details.

The same is true for making good decisions. Good decision making is all about having the taste and understanding the nuance that makes two decisions that seem about equivalent actually different, and one the right way to go, and one the wrong way to go.

I talked about prioritizing. I’m going to reaffirm that point. You’re at the end of the process, you’re trying to get something shipped. Prioritizing, prioritizing, prioritizing, is the name of the game and good engineering managers are good at being in that end stage and looking at the list of technical features and looking at the list of product features and asking both sides what’s really important here.

“What technical features can we absolutely not ship without. It would be bad for us to ship without having any kind of alerting on this, because this is actually pretty mission critical. But you know what? Actually, this is just an MVP and it’s going out to five people, so maybe we can just ship it without that feature.”

On the product side of course, it’s like, “Hey, product team, I know you love all these features, but which of these do you love the most, because guess what, this beautiful widget that you want the engineering team to build, we’ve talked it over and this is going to be a three week project to get right. Does this really have to be in the critical path of delivery?”

Being able to balance those two concerns and advocate for each side is one of the important characteristics of good engineering management.

Last point here, you have to understand the problems that the team is solving well enough to be able to communicate them with various people.

Manager telephone. Manager telephone happens when your manager goes and sits in a meeting, takes a bunch of notes, comes back to the team, asks the questions they have written down on their sheet that were the questions that were asked in the meeting, writes down your responses, goes back to the other team, reads those responses out and so forth. Zero value add. You want managers who can understand at least well enough to focus and reframe the questions that are being asked from people who aren’t familiar with the work of the team and who are good at actually getting the right information out of the engineering team, and making sense of it.

Nobody wants managers who are going to play telephone. That’s simply a zero value add activity. We want people who are going to appreciate the work that’s going on well enough to actually focus the discussions around it.

Debugging, empathy and judgment. These are pretty important. I think these are important skills to build whether you decide to become a manager or whether you simply want to be a really great hands-on engineer. What else?.

There is a little bit of a risk to this whole “rah rah managers should be technical” and that risk is that you get managers who were once pretty good at being technical, but who have gone hands-off for a long time and lost their touch a little bit. They still think of themselves as really amazing, as one of the people, as it were, but they don’t really remember what it’s like, and frankly, they haven’t even kept up, so they don’t really know what it’s like to write code in JavaScript. They’ve only ever written code in C++, and frankly, that’s just a different world, right? Writing code for the browser’s super different. They have not kept up. They don’t really appreciate what the actual work looks and feels like.

Stay humble.

If you decide to go on this path, it’s very important that you stay humble with your knowledge and your understanding. You can glue this in a bunch of different ways. Some people advocate for going back and forth between big companies and small companies where you can be a manager and then you can be hands-on and that’s an awesome path to take.

Some ways you could do it – frankly, I sometimes write a little bit of code. I work on a lot of open source projects, but realistically, you can keep reading code, you can keep helping debugging. You’re going to get a little hands-off, though.

My advice if you decide to follow this path is to, if nothing else, keep learning, particularly about advances in the way software engineers do their work. That’s things like, “What does it mean to build all your software based on cloud services.”

That’s very different than building everything in house. What does it mean to do a continuous deployment process? What are the major advances in the way people actually do work and deliver software? That’s a really important thing for you to keep in touch with as an engineering manager if you’re managing software engineering.

Okay, so these traits, one more time. Debugging, seeing those symptoms, technical empathy, that technical appreciation, and finally judgment, prioritizing and understanding the problems at hand.

I still consider myself an engineer, even though I don’t write code all that often. I personally hope to die an engineer someday, but whichever of those two paths I end up following, I know that it’s going to require constant learning, constant reading.

You can be like this guy. He used to work for Code Climate and he is the quintessential renaissance man who manages to both be the business jerk and be an engineer, all in one. So read more. You can start with my book, because you all have a copy of it, and thank you all very much. I’m happy to take questions.

Audience 1: Thank you for the talk, it’s great. Disclaimer, I’m not an engineer, I’m a product manager. My question to you as the technology industry veteran that you are today, you see these four engineers that either goes into principal engineers or technical fellow or going to director of engineering, do you see the same trend with product management? Do you have any advice for managers of product manager?

Camille Fournier: Not as much, mostly because the product teams tend to be so small that even as a manager of product managers, you’re not usually managing a lot of people. There’s just a huge difference between … frankly, I think you can be an “individual contributor style” engineer and still manage three or four people, particularly if they’re very senior and they don’t require a lot of mentorship or management.

I think that often product management, because there are just not that many people to be managed, it’s not as much of a fork. I do think that what you see happen with product management is that product managers who become more senior or experienced, tend to be like general managers – perhaps of business lines – and that is a bigger, more complex management job.

I could imagine that for product managers there is a little bit of a split between, I’m going to go be a general manager for a pretty big company and run a large business line and actually have a lot of management accountability or I’m going to stay very focused on just product direction and strategy.

Audience 2: Great talk, thank you so much. In your experience, what is a good management to engineer in ratio, so how many engineers per engineering manager do you think is a right mix. I know it’s different for every company and every field and all that, but just in general.

Camille Fournier: Okay. I do think it’s very hard to effectively be a one-on-one manager for more than eight to ten people. If you’ve got a team of more than ten people directly reporting to you, and frankly for many people it’s less than that, you are probably not serving very well, some of those people.

I know personally that if I have more than about six direct reports, at some point, people are getting less of me than they otherwise might. That helps sort of think about the ratios. I do still believe that you can effectively be managing a small team and acting as an individual contributor. You’re not going to be 100% as effective as you would be if you had no team. You can tweak ratios that way, but I certainly don’t think that it’s a good ratio to have one manager per 20 employees. It’s probably not a good ratio to have one manager per two employees either. It’s going to be somewhere in that.

I would say probably one to six, one to eight is okay, especially if the line managers are still expected to stay fairly technical even if they’re not writing a lot of code there, they’re really thinking about a lot of technical issues.

Audience 3: Hi. You said that team effectiveness is a manager’s primary responsibility or one of them. What are the KPI’s that you use to determine your team’s effectiveness?

Camille Fournier: Okay. A few KPIs that I would see, obviously, retention. Are people quitting? That’s a big one. How are we doing on the deliveries that we’ve committed to? If we’ve committed to deliver certain software or hit certain goals, how effective are we at hitting those goals and are those goals stretch goals? Do we think they’re not the level we would like them to be?

I think overall morale of a team is just generally important, so even if people aren’t quitting, you can still find yourself in a situation where people aren’t quitting, but they’re just not that excited about work. They’re not that engaged and enthusiastic. A lot of team effectiveness, the output is what work gets done, but the side pieces of it are really a lot about morale and retention and engagement from the team.

Audience 4: You talked about show an appreciation for team members. Have you ever been in a situation where you show appreciation of a team member and it’s fostered envy from other members or there’s been resentment as a result?

Camille Fournier: Yeah, absolutely. I think was accused of playing favorites at some point in my career, so I’ve tried to be very aware of that. I think appreciation is one of those core management things that you want to try to do a lot for everyone. It actually is not a bad thing to tell people they’re doing a good job fairly regularly and try to tell everyone on the team.

The way you recognize people, particularly if you do public recognition, you’re definitely shaping your culture when you do that. If you always publicly recognize individuals, and you never publicly recognize teams, your company is going to start to develop a culture of “individual accomplishments are the most important thing and it’s better for me to get the win myself than to bring the whole team along.”

You have to be very careful with thinking about how you recognize those things. Honestly, I think a lot of this appreciation is just in that one on one. Do I feel like my boss really understands the work I’m doing well enough to be like, “Wow, that was a hard thing. That was a really cool set up you did to get that migration to go so smoothly. I’m very impressed with the technical work that you did. I’m impressed you thought through this process in that way.”

I think a lot of appreciation is very effective just in a one-on-one context, not even worrying about big team appreciation.

Audience 5: You mentioned we all want to work on hard problems, fun problems, and maybe direct our team towards those. Often we don’t necessarily have the decision making in where the product goes, where a business wants to go, so what are your strategies for maybe managing upward or convincing them of going towards maybe a more difficult problem but more impactful?

Camille Fournier: I think it depends, so a lot of the times … hard problems is a little bit of a, I don’t think I phrased that as well as I should have. Engineers want to feel like they are having impact, so some engineers are very much driven by solving the hardest problem. I think the best thing you can do in that case is help identify where there are really hard problems and make sure you’re keeping those engineers as close to those as possible.

A lot of the times what you do though as an engineering manager is you also help people find some of the more purely technical problems to solve, and those are not necessarily hard in the theoretical computer science hard way, but they’re often hard in the, “Oh we really need to clean up this particular piece of technical data or this particular system” and you as a manager, are actually explaining the value of spending that technical focus to the rest of the business and saying look, “This is what this is going to enable. This is how this is going to speed us up, or not slow us down in the future.”

And that, I think it’s a matter of really being specific about what the goal in that clean up work is and trying to find measurable things that you can do once you have done that. Some of it’s also just about setting very hard guidelines with “we always spend a certain amount of time on this kind of thing because this is important and this is the way we run our engineering teams.” It’s a combination of those things.

Audience 6: As you become more removed from the day to day delivery of code, do you have any tips for ensuring code quality from your team members?

Camille Fournier: That’s hard. Well, perhaps you can use, a lovely product like Code Climate, a word from our sponsors [laughs]. I do think that letting go actually can be really hard. Some of it is setting standards and being as clear as you can about the standards that you want the software to maintain. That can be anything from someone like me, I’m very passionate about testing, I think testing is really important and so I try to set basic standards like, “Look, we should be very cautious about ever accepting pull requests or whatever that don’t have tests with them. Why isn’t this code tested? Why aren’t we writing tests for this stuff?” I think you can do things like that.

I think also some of it though is about, you hopefully have senior engineers on your team that you’ve trained, that they understand what good code looks like. You want them to be teaching everyone on the team what good code looks like. That is really one of those areas where it’s not really your job as a manager, although you probably still care, but you do want to make sure that senior engineers feel like they have the ability to chime in and say, “Hey, we want to improve the standards in this code. We want to improve the standards in this software, and here’s what we’re going to do to help with that.”

Audience 7: When you first transitioned from coding full time to management, did you experience imposter syndrome and how did you deal with that?

Camille Fournier: I wouldn’t say that it was imposter syndrome exactly. I will say that part of becoming a, especially a senior manager, is developing a certain level of presence and being able to, the body language and the way that you present yourself, and the way that you talk, and the questions that you ask, and the things that you do, are actually important. That’s actually a pretty hard lesson to learn, and so I wouldn’t say that it was exactly imposter syndrome, but there was certainly a level of “why am I not getting the respect that I should get because of my title or whatever” and I think some of that was just, “Oh yeah, I have to learn how to be in a room with my peers and be productive and not undermine people and not be disruptive in certain ways, or make my points in a way that people will hear them and they won’t react negatively. I would say for me, that was the harder lesson than imposter syndrome. I don’t feel like I had too much of that, that’s never been my problem.

Audience 8: Hi. Thanks for speaking with us. Quick question on dealing with promotions, especially as your team size starts to grow. You naturally have to promote people within hopefully, but oftentimes you might find a couple of candidates within your team that when one is a more natural leader, but they both have the same aspirations, how do you generally deal with that? How do you smooth that out?

Camille Fournier: Yeah. I think the best thing that you can do … I think you’re lucky if you know the aspirations. I’ve certainly had people where we did a round of making tech leads, for example, and someone got very upset because they weren’t chosen and it was a shock to everyone involved because nobody had any idea that this person was even interested. And so that was a little bit of a mistake on our part of not actually spending the time to understand what people wanted, to understand people’s aspirations. Part of what you need to do is make sure you understand the aspirations.

Once you understand them, I think then if you think that you’ve got a person who has, frankly, better skills right now, maybe because they just have a natural skill set, that’s okay, but you want to give the other person coaching and try to identify specific opportunities for them to develop some of those skills and to learn some of those things.

Even though they’re not necessarily being promoted to manager, maybe they can be running certain projects. Maybe you can work with the new manager and say, “This person really does want to be in a management role and so we need to be looking for opportunities for them to step up and take some leadership and push themselves out of their comfort zone, maybe give presentations to the team”, whatever those gaps that you think that they might have, giving them a chance to actually practice the job and fill those gaps is a good way to prepare them for when the next opportunity arises. Now they really have the skills and the confidence to do it.

Camille Fournier is a Managing Director and Head of Platform Engineering at Two Sigma. She is the former Chief Technology Officer of Rent The Runway and a former Vice President of Technology at Goldman Sachs.

Fournier earned an undergraduate degree from Carnegie Mellon University and a Master’s degree in Computer Science from the University of Wisconsin–Madison. She is a maintainer of the Apache ZooKeeper open source project, writes the Ask The CTO column for O’Reilly Media, and is a regular public speaker and advocate for greater diversity within technology and leadership. Her book, The Manager’s Path, was published by O’Reilly in early 2017.

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The first step in any successful engineering insights strategy is defining why you're doing this in the first place. If you're rolling out developer productivity metrics or an insights platform, you need to make sure there’s alignment on the purpose across the board.

Too often, organizations dive into this journey without answering the crucial question: Why do we need this data? If you ask five different leaders in your organization, are you going to get five answers, or will they all point to the same objective? If you can’t answer this clearly, you risk chasing a vague, unhelpful path.

One way I recommend approaching this is through the "Five Whys" technique. Ask why you're doing this, and then keep asking "why" until you get to the core of the problem. For example, if your initial answer is, “We need engineering metrics,” ask why. The next answer might be, “Because we're missing deliverables.” Keep going until you identify the true purpose behind the initiative. Understanding that purpose helps avoid unnecessary distractions and lets you focus on solving the real issue.

Step 2: Understand Your People

Once the purpose is clear, the next step is to think about who will be involved in this journey. You have to consider the following:

  1. Who will be using the developer productivity tool/insights platform?
  2. Are these hands-on developers or executives looking for high-level insights?
  3. Who else in the organization might need access to the data, like finance or operations teams?

It’s also crucial to account for organizational changes. Reorgs are common in the enterprise world, and as your organization evolves, so too must your insights platform. If the people responsible for the platform’s maintenance change, who will ensure the data remains relevant to the new structure? Too often, teams stop using insights platforms because the data no longer reflects the current state of the organization. You need to have the right people in place to ensure continuous alignment and relevance.

Step 3: Define Your Process

The next key component is process—a step that many organizations overlook. It's easy to say, "We have the data now," but then what happens? What do you expect people to do with the data once it’s available? And how do you track if those actions are leading to improvement?

A common mistake I see is organizations focusing on metrics without a clear action plan. Instead of just looking at a metric like PR cycle times, the goal should be to first identify the problem you're trying to solve. If the problem is poor code quality, then improving the review cycle times might help, but only because it’s part of a larger process of improving quality, not just for the sake of improving the metric.

It’s also essential to approach this with an experimentation mindset. For example, start by identifying an area for improvement, make a hypothesis about how to improve it, then test it and use engineering insights data to see if your hypothesis is correct. Starting with a metric and trying to manipulate it is a quick way to lose sight of your larger purpose.

Step 4: Program and Rollout Strategy

The next piece of the puzzle is your program and rollout strategy. It’s easy to roll out an engineering insights platform and expect people to just log in and start using it, but that’s not enough. You need to think about how you'll introduce this new tool to the various stakeholders across different teams and business units.
The key here is to design a value loop within a smaller team or department first. Get a team to go through the full cycle of seeing the insights, taking action, and then quantifying the impact of that action. Once you've done this on a smaller scale, you can share success stories and roll it out more broadly across the organization. It’s not about whether people are logging into the platform—it’s about whether they’re driving meaningful change based on the insights.

Step 5: Choose Your Platform Wisely

And finally, we come to the platform itself. It’s the shiny object that many organizations focus on first, but as I’ve said before, it’s the last piece of the puzzle, not the first. Engineering insights platforms like Code Climate are powerful tools, but they can’t solve the problem of a poorly defined strategy.

I’ve seen organizations spend months evaluating these platforms, only to realize they didn't even know what they needed. One company in the telecom industry realized that no available platform suited their needs, so they chose to build their own. The key takeaway here is that your platform should align with your strategy—not the other way around. You should understand your purpose, people, and process before you even begin evaluating platforms.

Looking Ahead

To build a successful engineering insights strategy, you need to go beyond just installing a tool. An insights platform can only work if it’s supported by a clear purpose, the right people, a well-defined process, and a program that rolls it out effectively. The combination of these elements will ensure that your insights platform isn’t just a dashboard—it becomes a powerful driver of change and improvement in your organization.

Remember, a successful software engineering insights strategy isn’t just about the tool. It’s about building a culture of data-driven decision-making, fostering continuous improvement, and aligning all your teams toward achieving business outcomes. When you get that right, the value of engineering insights becomes clear.

Want to build a tailored engineering insights strategy for your enterprise organization? Get expert recommendations at our free insights strategy workshop. Register here.

Andrew Gassen has guided Fortune 500 companies and large government agencies through complex digital transformations. He specializes in embedding data-driven, experiment-led approaches within enterprise environments, helping organizations build a culture of continuous improvement and thrive in a rapidly evolving world.

Most organizations are great at communicating product releases—but rarely do the same for process improvements that enable those releases. This is a missed opportunity for any leader wanting to expand “growth mindset,” as curiosity and innovation is as critical for process improvement as it is product development.

Curiosity and innovation aren’t limited to product development. They’re just as essential in how your teams deliver that product. When engineering and delivery leaders share what they’re doing to find efficiencies and unclog bottlenecks, they not only improve Time to Value — they help their peers level up too.

Create Buzz Around Process Wins

Below is a template leaders can use via email or communication app (Slack, Microsoft Teams) to share process changes with their team. I’ve personally seen updates like this generate the same level of energy as product announcements—complete with clap emojis👏 and follow-up pings like “Tell me more!” Even better, they’re useful for performance reviews and make great resume material for the leads who author them (excluding any sensitive or proprietary content, of course).

Subject: [Experiment update]
[Date]
Experiment Lead: [Name]

Goal: [Enter the longer term goal your experiment was in service of]

Opportunity: [Describe a bottleneck or opportunity you identified for some focused improvement]

Problem: [Describe the specific problem you aimed to solve]

Solution: [Describe the very specific solution you tested]

Metric(s): [What was the one metric you determined would help you know if your solution solved the problem? Were there any additional metrics you kept track of, to understand how they changed as well?]

Action: [Describe, in brief, what you did to get the result]

Result: [What was the result of the experiment, in terms of the above metrics?]

Next Step: [What will you do now? Will you run another experiment like this, design a new one, or will you rollout the solution more broadly?]

Key Learnings: [What did you learn during this experiment that is going to make your next action stronger?]

Please reach out to [experiment lead’s name] for more detail.

Sample Use Case

Subject: PR Descriptions Boost Review Speed by 30%

March 31, 2025
Experiment Lead:
Mary O’Clary

Goal: We must pull a major capability from Q4 2024 into Q2 2025 to increase our revenue. We believe we can do this by improving productivity by 30%.

Opportunity: We found lack of clear descriptions were a primary cause of churn & delay during the review cycle. How might we improve PR descriptions, with information reviewers need?

Problem: Help PR Reviewers more regularly understand the scope of PRs, so they don’t need to ask developers a bunch of questions.

Solution: Issue simple guidelines for what we are looking for PR descriptions

Metric(s): PR Review Speed. We also monitored overall PR Cycle Time, assuming it would also improve for PRs closed within our experiment timeframe.

Action: We ran this experiment over one 2 week sprint, with no substantial changes in complexity of work or composition of the team. We kept the timeframe tight to help eliminate additional variables.

Result: We saw PR Review Speed increase by 30%

Next Step: Because of such a great result and low perceived risk, we will roll this out across Engineering and continue to monitor both PR Review Speed & PR Cycle Time.

Key Learnings: Clear, consistent PR descriptions reduce reviewer friction without adding developer overhead, giving us confidence to expand this practice org-wide to help accelerate key Q2 2025 delivery.

Please reach out to Mary for more detail.

How Make This Process Stick

My recommendation is to appoint one “editor in chief” to issue these updates each week. They should CC the experiment lead on the communication to provide visibility. In the first 4-6 weeks, this editor may need to actively solicit reports and coach people on what to share. This is normal—you’re building a new behavior. During that time, it's critical that managers respond to these updates with kudos and support, and they may need to be prompted to do so in the first couple of weeks.

If these updates become a regular ritual, within ~3 months, you’ll likely have more contributions than you can keep up with. That’s when the real cultural shift happens: people start sharing without prompting, and process improvement becomes part of how your org operates.

I’ve seen this work in large-scale organizations, from manufacturing to healthcare. Whether your continuous improvement culture is just getting started or already mature, this small practice can help you sustain momentum and deepen your culture of learning.

Give it a shot, and don’t forget to celebrate the wins along the way.

Jen Handler is the Head of Professional Services at Code Climate. She’s an experienced technology leader with 20 years of building teams that deliver outcome-driven products for Fortune 50 companies across industries including healthcare, hospitality, retail, and finance. Her specialties include goal development, lean experimentation, and behavior change.


Output is not the same as impact. Flow is not the same as effectiveness. Most of us would agree with these statements—so why does the software industry default to output and flow metrics when measuring success? It’s a complex issue with multiple factors, but the elephant in the room is this: mapping engineering insights to meaningful business impact is far more challenging than measuring developer output or workflow efficiency.

Ideally, data should inform decisions. The problem arises when the wrong data is used to diagnose a problem that isn’t the real issue. Using misaligned metrics leads to misguided decisions, and unfortunately, we see this happen across engineering organizations of all sizes. While many companies have adopted Software Engineering Intelligence (SEI) platforms—whether through homegrown solutions or by partnering with company that specializes in SEI like Code Climate—a clear divide has emerged. Successful and mature organizations leverage engineering insights to drive real improvements, while others collect data without extracting real value—or worse, make decisions aimed solely at improving a metric rather than solving a real business challenge.

From our experience partnering with large enterprises with complex structures and over 1,000 engineers, we’ve identified three key factors that set high-performing engineering organizations apart.

1. Treating Software Engineering Insights as a Product

When platform engineering first emerged, early innovators adopted the mantra of “platform as a product” to emphasize the key principles that drive successful platform teams. The same mindset applies to Software Engineering Intelligence (SEI). Enterprise organizations succeed when they treat engineering insights as a product rather than just a reporting tool.

Data shouldn’t be collected for the sake of having it—it should serve a clear purpose: helping specific users achieve specific outcomes. Whether for engineering leadership, product teams, or executive stakeholders, high-performing organizations ensure that engineering insights are:

  • Relevant – Focused on what each audience actually needs to know.
  • Actionable – Providing clear next steps, not just numbers.
  • Timely – Delivered at the right moment to drive decisions.

Rather than relying on pre-built dashboards with generic engineering metrics, mature organizations customize reporting to align with team priorities and business objectives.

For example, one of our healthcare customers is evaluating how AI coding tools like GitHub Copilot and Cursor might impact their hiring plans for the year. They have specific questions to answer and are running highly tailored experiments, making a custom dashboard essential for generating meaningful, relevant insights. With many SEI solutions, they would have to externalize data into another system or piece together information from multiple pages, increasing overhead and slowing down decision-making.

High-performing enterprise organizations don’t treat their SEI solution as static. Team structures evolve, business priorities shift, and engineering workflows change. Instead of relying on one-size-fits-all reporting, they continuously refine their insights to keep them aligned with business and engineering goals. Frequent iteration isn’t a flaw—it’s a necessary feature, and the best organizations design their SEI operations with this in mind.

2. The Value of Code is Not the Code

Many software engineering organizations focus primarily on code-related metrics, but writing code is just one small piece of the larger business value stream—and rarely the area with the greatest opportunities for improvement. Optimizing code creation can create a false sense of progress at best and, at worst, introduce unintended bottlenecks that negatively impact the broader system.

High-performing engineering organizations recognize this risk and instead measure the effectiveness of the entire system when evaluating the impact of changes and decisions. Instead of focusing solely on PR cycle time or commit activity, top-performing teams assess the entire journey:

  • Idea generation – How long does it take to move from concept to development?
  • Development process – Are teams working efficiently? Are bottlenecks slowing down releases?
  • Deployment & adoption – Once shipped, how quickly is the feature adopted by users?
  • Business outcomes – Did the feature drive revenue, retention, or efficiency improvements?

For example, reducing code review time by a few hours may seem like an efficiency win, but if completed code sits for six weeks before deployment, that improvement has little real impact. While this may sound intuitive, in practice, it’s far more complicated—especially in matrixed or hierarchical organizations, where different teams own different parts of the system. In these environments, it’s often difficult, though not impossible, for one group to influence or improve a process owned by another.

One of our customers, a major media brand, had excellent coding metrics yet still struggled to meet sprint goals. While they were delivering work at the expected rate and prioritizing the right items, the perception of “failed sprints” persisted, creating tension for engineering leadership. After further analysis, we uncovered a critical misalignment: work was being added to team backlogs after sprints had already started, without removing any of the previously committed tasks. This shift in scope wasn’t due to engineering inefficiency—it stemmed from the business analysts' prioritization sessions occurring after sprint commitments were made. A simple rescheduling of prioritization ceremonies—ensuring that business decisions were finalized before engineering teams committed to sprint goals. This small yet system-wide adjustment significantly improved delivery consistency and alignment—something that wouldn’t have been possible without examining the entire end-to-end process.

3. Shifting from Tactical Metrics to Strategy

There are many frameworks, methodologies, and metrics often referenced as critical to the engineering insights conversation. While these can be useful, they are not inherently valuable on their own. Why? Because it all comes down to strategy. Focusing on managing a specific engineering metric or framework (i.e. DORA or SPACE) is missing the forest for the trees. Our most successful customers have a clear, defined, and well-communicated strategy for their software engineering insights program—one that doesn’t focus on metrics by name. Why? Because unless a metric is mapped to something meaningful to the business, it lacks the context to be impactful.

Strategic engineering leaders at large organizations focus on business-driven questions, such as:

  • Is this engineering investment improving customer experience?
  • Are we accelerating revenue growth?
  • Is this new approach or tool improving cross-functional collaboration?

Tracking software engineering metrics like cycle time, PR size, or deployment frequency can be useful indicators, but they are output metrics—not impact metrics. Mature organizations go beyond reporting engineering speed and instead ask: "Did this speed up product releases in a way that drove revenue?"

While challenging to measure, this is where true business value lies. A 10% improvement in cycle time may indicate progress, but if sales remain flat, did it actually move the needle? Instead of optimizing isolated metrics, engineering leaders should align their focus with overarching business strategy. If an engineering metric doesn’t directly map to a key strategic imperative, it’s worth reevaluating whether it’s the right thing to measure.

One of our retail customers accelerated the release of a new digital capability, allowing them to capture additional revenue a full quarter earlier than anticipated. Not only did this directly increase revenue, but the extended timeline of revenue generation created a long-term financial impact—a result that finance teams, investors, and the board highly valued. The team was able to trace their decisions back to insights derived from their engineering data, proving the direct connection between software delivery and business success.

Understanding the broader business strategy isn’t optional for high-performing engineering organizations—it’s a fundamental requirement. Through our developer experience surveys, we’ve observed a significant difference between the highest-performing organizations and the rest as it relates to how well developers understand the business impact they are responsible for delivering. Organizations that treat engineers as task-takers, isolated from business impact, consistently underperform—even if their coding efficiency is exceptional. The engineering leaders at top-performing organizations prioritize alignment with strategy and avoid the distraction of tactical metrics that fail to connect to meaningful business outcomes.

Learn how to shift from micro engineering adjustments to strategic business impact. Request a Code Climate Diagnostic.

Code Climate is Now a Software Engineering Intelligence Solutions Partner for Enterprises

Code Climate is now a Software Engineering Intelligence Solutions Partner for senior engineering leaders at enterprise organizations.
Jan 13, 2025
7 min read

Code Climate has supported thousands of engineering teams of all sizes over the past decade, enhancing team health, advancing DevOps practices, and providing visibility into engineering processes. According to Gartner®, the Software Engineering Intelligence (SEI) platform market is expanding as engineering leaders increasingly leverage these platforms to enhance productivity and drive business value. As pioneers in the SEI space, the Code Climate team has identified three key takeaways from partnerships with our Fortune 100 customers:

  1. Engineering Metrics Are Not Enough
    • Engineering leaders that adopt a Software Engineering Intelligence (SEI) platform without a proper SEI strategy fail to extract value from the data
    • Engineering leaders that adopt quantitative metrics without qualitative measures are missing the full picture
  2. Hands-Off Approach Falls Short
    • Approaching an SEI platform as a traditional turnkey SaaS product does not ensure team success
    • Organizations that lack collaboration with an SEI solutions provider often struggle to drive adoption and understanding of engineering insights
  3. Insights Alone Do Not Drive Outcomes
    • Engineering leaders often struggle to translate insights from an SEI platform into actionable steps
    • Engineering leaders often struggle to align engineering performance to meaningful business outcomes

Empowering Engineering Leaders at Enterprise Organizations

The above takeaways have prompted a strategic shift in Code Climate’s roadmap, now centered on enterprise organizations with complex engineering team structure and workflows. As part of this transition, our flagship Software Engineering Intelligence (SEI) platform, Velocity, is now replaced by an enhanced SEI platform, custom-designed for each leader and their organization. With enterprise-level scalability, Code Climate provides senior engineering leaders complete autonomy over their SEI platform, seamlessly integrating into their workflows while delivering the customization, flexibility, and reliability needed to tackle business challenges.

Moreover, we understand that quantitative metrics from a data platform alone cannot transform an organization, which is why Code Climate is now a Software Engineering Intelligence Solutions Partner—offering five key characteristics that define our approach

  1. Tailored Solutions: We provide engineering solutions via quantitative insights and qualitative workshops that are specifically designed to meet the unique needs of enterprise engineering teams—moving beyond standard, black-box solutions.
  2. Strategic Collaboration: We enable our enterprise customers to build an SEI strategy, engaging with key stakeholders to align Code Climate’s solution and services with their broader business goals.
  3. Long-Term Partnership: Our strategic partnership with our enterprise customers is typically ongoing, focusing on long-term value rather than offering a standard insights platform. As an enterprise-level SEI solutions partner, we are invested in the sustained success of our customers.
  4. Expert Guidance: We offer expert guidance and actionable recommendations to help our enterprise customers navigate challenges, optimize performance, and achieve business goals.
  5. End-to-End Support: We provide comprehensive services, from advisory support and implementation to ongoing support and optimization.

A Message from the New CEO of Code Climate

"During my time at Pivotal Software, Inc., I met with hundreds of engineering executives who consistently asked, “How do I improve my software engineering organization?” These conversations revealed a universal challenge: aligning engineering efforts with business goals. I joined Code Climate because I'm passionate about helping enterprise organizations address these critical questions with actionable insights and data-driven strategies that empower engineering executives to drive meaningful change." - Josh Knowles, CEO of Code Climate

Ready to make data-driven engineering decisions to maximize business impact? Request a consultation.

Today, we’re excited to share that Code Climate Quality has been spun out into a new company: Qlty Software. Code Climate is now focused entirely on its next phase of Velocity, our Software Engineering Intelligence (SEI) solution for enterprise organizations

Qlty logo

How It Started

I founded Code Climate in 2011 to help engineering teams level up with data. Our initial Quality product was a pioneer for automated code review, helping developers merge with confidence by bringing maintainability and code coverage metrics into the developer workflow.

Our second product, Velocity, was launched in 2018 as the first Software Engineering Intelligence (SEI) platform to deliver insights about the people and processes in the end-to-end software development lifecycle.

All the while, we’ve been changing the way modern software gets built. Quality is reviewing code written by tens of thousands of engineers, and Velocity is helping Fortune 500 companies drive engineering transformation as they adopt AI-enabled workflows.

Today, Quality and Velocity serve different types of software engineering organizations, and we are investing heavily in each product for their respective customers.

Where We're Going

To serve both groups better, we’re branching out into two companies. We’re thrilled to introduce Qlty Software, and to focus Code Climate on software engineering intelligence.

Over the past year, we’ve made more significant upgrades to Quality and our SEI platform, Velocity, than ever before. Much of that is limited early access, and we’ll have a lot to share publicly soon. As separate companies, each can double down on their products.

Qlty Software is dedicated to taking the toil out of code maintenance. The new company name represents our commitment to code quality. We’ve launched a new domain, with a brand new, enhanced edition of the Quality product.

I’m excited to be personally moving into the CEO role of Qlty Software to lead this effort. Josh Knowles, Code Climate’s General Manager, will take on the role of CEO of Code Climate, guiding the next chapter as an SEI solutions partner for technology leaders at large, complex organizations.

We believe the future of developer tools to review and improve code automatically is brighter than ever – from command line tools accelerating feedback loops to new, AI-powered workflows – and we’re excited to be on that journey with you.

-Bryan
CEO, Qlty Software


Technology is evolving very quickly but I don't believe it's evolving as quickly as expectations for it. This has become increasingly apparent to me as I've engaged in conversations with Code Climate's customers, who are senior software engineering leaders across different organizations. While the technology itself is advancing rapidly, the expectations placed on it are evolving at an even faster pace, possibly twice as quickly.

New Technology: AI, No-Code/Low-Code, and SEI Platforms

There's Generative AI, such as Copilot, the No-code/Low-code space, and the concept of Software Engineering Intelligence (SEI) platforms, as coined by Gartner®. The promises associated with these tools seem straightforward:

  • Generative AI aims to accelerate, improve quality, and reduce costs.
  • No-code and Low-code platforms promise faster and cheaper software development accessible to anyone.
  • SEI platforms such as Code Climate enhance productivity measurement for informed decisions leading to faster, efficient, and higher-quality outcomes.

However, the reality isn’t as straightforward as the messaging may seem:

  • Adopting Generative AI alone can lead to building the wrong things faster.
  • No-code or Low-code tools are efficient until you hit inherent limitations, forcing cumbersome workarounds that reduce maintainability and create new challenges compared to native code development.
  • As for SEI platforms, as we've observed with our customers, simply displaying data isn't effective if you lack the strategies to leverage it.

When I joined Code Climate a year ago, one recurring question from our customers was, "We see our data, but what's the actionable next step?" While the potential of these technologies is compelling, it's critical to address and understand their practical implications. Often, business or non-technical stakeholders embrace the promises while engineering leaders, responsible for implementation, grapple with the complex realities.

Navigating New Technology Expectations and Realities

Software engineering leaders now face increased pressure to achieve more with fewer resources, often under metrics that oversimplify their complex responsibilities. It's no secret that widespread layoffs have affected the technology industry in recent years. Despite this, the scope of their responsibilities and the outcomes expected from them by the business haven't diminished. In fact, with the adoption of new technologies, these expectations have only increased.

Viewing software development solely in terms of the number of features produced overlooks critical aspects such as technical debt or the routine maintenance necessary to keep operations running smoothly. Adding to that, engineering leaders are increasingly pressured to solve non-engineering challenges within their domains. This disconnect between technical solutions and non-technical issues highlights a fundamental gap that can't be bridged by engineering alone—it requires buy-in and understanding from all stakeholders involved.

This tension isn't new, but it's becoming front-and-center thanks to the promises of new technologies mentioned above. These promises create higher expectations for business leaders, which, in turn, trickle down to engineering leaders who are expected to navigate these challenges, which trickle down to the teams doing the work. Recently, I had a conversation with a Code Climate customer undergoing a significant adoption of GitHub Copilot, a powerful tool. This particular leader’s finance team told her, "We bought this new tool six months ago and you don't seem to be operating any better. What's going on?" This scenario reflects the challenges many large engineering organizations face.

Navigating New Technology Challenges and Taking Action

Here's how Code Climate is helping software engineering leaders take actionable steps to address challenges with new technology:

  1. Acknowledging the disconnect with non-technical stakeholders, fostering cross-functional alignment and realistic expectations. Facilitating open discussions between technology and business leaders, who may never have collaborated before, is crucial for progress.
  2. Clearly outlining the broader scope of engineering challenges beyond just writing code—evaluating processes like approval workflows, backlog management, and compliance mandates. This holistic view provides a foundation for informed discussions and solutions.
  3. Establishing a shared understanding and language for what constitutes a healthy engineering organization is essential.

In addition, we partner with our enterprise customers to experiment and assess the impact of new technologies. For instance, let's use the following experiment template to justify the adoption of Copilot:

We believe offering Copilot to _______ for [duration] will provide sufficient insights to inform our purchasing decision for a broader, organization-wide rollout.

We will know what our decision is if we see ______ increase/decrease.

Let’s fill in the blanks:


We believe offering Copilot to one portfolio of 5 teams for one quarter will provide sufficient insights to inform our purchasing decision for a broader, organization-wide rollout.

We will know what our decision is if we see:

  • An increase in PR Throughput
  • A decrease in Cycle Time
  • No negative impact to Rework
  • No negative impact to Defect Rate

Andrew Gassen leads Code Climate's enterprise customer organization, partnering with engineering leaders for organization-wide diagnostics to identify critical focus areas and provide customized solutions. Request a consultation to learn more.

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