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Leitura de 26 min

The Meta-Habit of High Performers: How Outer Loops Unlock Growth (Career Growth Accelerator)

Summary

In this episode of Developer Tea, host Jonathan Cottrell introduces the concept of “loops” as a mental model for understanding recurring behaviors and systems in our professional lives. He explains that everyone operates within various loops—patterns of behavior triggered by conditions—whether it’s daily routines, meeting protocols, or career decisions. These loops can become automatic and suboptimal without conscious evaluation.

Cottrell distinguishes between “inner loops” (the specific behaviors we engage in) and “outer loops” (the meta-level evaluation of those behaviors). High-performing senior engineers and managers excel at creating outer loops that allow them to step back and assess whether their current systems are effective. This enables them to make informed adjustments rather than reacting linearly to single outcomes.

He connects this concept to James Clear’s idea that “we fall to the level of our systems” rather than rising to our ambitions. By consciously designing outer loops, professionals can create experimental frameworks where they test behaviors over multiple iterations before deciding whether to adopt or discard them. This prevents burnout from linear effort without proportional returns.

The episode emphasizes that career growth at senior levels requires moving beyond simple linear investment. Instead of just working harder, professionals need to evaluate their systems and make strategic adjustments. Outer loop thinking allows for longer-term evaluation, helping individuals break through plateaus by optimizing how they spend their energy and time.

Recommendations

Books

  • Atomic Habits by James Clear — Referenced when discussing how habits are systems we fall to rather than aspirations we rise to, emphasizing that our systems (habits) determine our outcomes.

Tools

  • Unblocked AI Code Review — Sponsored tool that provides AI-powered code review with decision-grade context (prior PRs, design discussions, documentation). Teams report fewer comments, higher signal, and automated reviews they actually trust.

Topic Timeline

  • 00:00:00 — Introduction to the meta-habit concept — Jonathan introduces the episode’s focus on a common habit among high-performing managers and senior engineers. He describes it as a “meta-habit”—a way of thinking about work that’s simple enough to write on a napkin. He frames this within the Career Growth Accelerator series, targeting engineers feeling stagnant or headed for burnout despite putting in energy.
  • 00:04:53 — Defining loops as mental models — Jonathan introduces the core concept of “loops” as mental models for understanding recurring behaviors. He explains that everyone has multiple loops in their life—from daily routines (wake up, work, sleep) to career patterns (while happy at job, stay at job). These loops are shaped by decisions, pressures, biases, and incentives, and they operate like conditional while-loops in programming.
  • 00:11:22 — Connecting loops to habits and useful defaults — Jonathan connects the loop concept to previous discussions about “useful defaults” and James Clear’s “Atomic Habits.” He explains that habits are behaviors requiring little conscious effort, while loops are more conditional states that continue until termination. He provides examples like “what do you do when you run out of work?” or “what do you do when there’s too much to do?” as starting points for loop design.
  • 00:16:54 — Applying loops to career growth and introducing outer loops — Jonathan shifts the focus from tactical loops (like coding workflows) to strategic loops for career growth. He introduces the “outer loop” concept as a meta-observation layer that evaluates inner loops. For example, an outer loop might recognize the need for transparent communication culture, then adjust inner loops (like setting Slack status during holidays) to instill that culture.
  • 00:20:48 — Outer loops as experimental frameworks — Jonathan explains that outer loops create experimental frameworks where you can make informed adjustments to inner loops. This allows you to test behaviors over multiple iterations, gather information, and evaluate longer-term outcomes. Without outer loops, adjustments tend to be linear and reactive, making it hard to understand overall direction or set up longer-term conditionals.
  • 00:23:28 — Key takeaway: evaluating recurring behaviors — Jonathan clarifies that the core takeaway isn’t about having exactly two loops, but about developing the ability to evaluate recurring behaviors from a higher level. The fundamental behavior of high performers is “being able to step up a level and evaluate the system, not just the single behavior and the single outcome.” He contrasts this with reactive thinking (“one meeting went poorly, so never have meetings again”) versus outer loop thinking (“run the experiment for five iterations, then decide”).

Episode Info

  • Podcast: Developer Tea
  • Author: Jonathan Cutrell
  • Category: Technology Business Careers Society & Culture
  • Published: 2026-02-03T08:00:00Z
  • Duration: 00:25:54

References

Podcast Info

Transcript

[00:00:00] Hey everyone and welcome to today’s episode of Developer Tea. In today’s episode we’re going to

[00:00:10] be talking about one of the most common habits that I see in high-performing managers and

[00:00:17] high-performing senior engineers. This is and it’s not just a single habit it’s not something that

[00:00:24] you would you know just go and do this one thing over and over. It is kind of a meta habit it’s a

[00:00:30] way of thinking about the world and a way of thinking about your work but it’s so simple

[00:00:36] that you could write it down on the back of a napkin. My name is Jonathan Cottrell and my goal

[00:00:40] on the show is to help driven developers like you find clarity perspective and purpose in their

[00:00:45] careers and we’ve been doing this career growth accelerator series. What is the point of the

[00:00:51] career growth accelerator series? It is to help

[00:00:53] senior engineers. It is to help you know high to mid-level engineers who are trying to go to

[00:01:01] senior right. It’s to help people who are stuck in the mid-management levels and are not getting

[00:01:08] the recognition. Maybe you’ve gotten you know a straight three on your one to five rating in your

[00:01:14] performance reviews for the past year, two years, three years, four. You feel stagnant. You feel

[00:01:23] like you’ve lost your career and you keep on putting more energy in but not getting anything

[00:01:29] extra out. Many of you you may not realize this but many of you are headed for burnout. If I just

[00:01:35] described you if you’re putting a bunch of energy in and you’re not getting something out you will

[00:01:41] eventually run out. You will eventually hit a wall. You’re eventually going to burn out and so in

[00:01:48] today’s episode we’re going to talk about a way of thinking about how to spend your energy,

[00:01:53] in the most productive way, more often right. The goal of this is not to you know fix a particular

[00:02:03] problem but to give you the tools to think about how you spend your energy, how you spend your time

[00:02:10] and to constantly improve that right. And this is why I say it’s a meta

[00:02:16] habit. It’s not really one specific. It’s not hey every morning you wake up and do x.

[00:02:23] Right. You meditate for six and a half minutes and then skip coffee and emails until 9 27. That’s

[00:02:32] not what this is about. All right. There’s no single trick that’s going to get you to break

[00:02:37] through your walls to get you to break through to the next level. There’s no specific trick

[00:02:44] that’s going to suddenly cause your career to grow overnight. You may run into certain things

[00:02:52] that have a lot of untapped energy. You may run into certain things that have a lot of untapped

[00:02:53] potential for you. Right. If you haven’t been investing anything for example in self-review.

[00:02:59] If you haven’t been investing anything in cross-functional relationship building.

[00:03:04] Those are areas where you might find a ton of potential. But most of the time the things that

[00:03:11] matter in our lives the things that really are rewarding the things we care about doing

[00:03:15] the things we care about accomplishing you know the the kind of resources that we care about

[00:03:23] earning.

[00:03:23] Right. These things take work. They take a lot of focus. They take a lot of effort. It is not easy.

[00:03:30] And if you’re here to make it easy then you’re doing the wrong thing. Right. But that’s not the

[00:03:36] same thing. That’s I’m not saying the same thing as you know you can’t make it more efficient.

[00:03:44] You can’t spend your time in a better way. So so really what we’re talking about in this episode

[00:03:50] is not just to tell you to keep grinding.

[00:03:53] Right. That’s not a smart way to spend your time. You will burn out. You will run out of steam

[00:04:00] especially if you’re not seeing commensurate gains. Right. If you’re not especially if you’re

[00:04:05] seeing sublinear in other words you’re putting in X and you’re getting back less than X. You should

[00:04:12] at least be seeing some kind of return on your investment that you would consider equivalent

[00:04:17] to what you’ve invested. Right. But the goal for career growth.

[00:04:23] For most seniors you’ve kind of done as much linear investment as you can. In other words

[00:04:28] you’re just getting X about back out of an X investment. Just meeting that is not going to

[00:04:36] be how you break through to the next level in your career because you’ve probably already reached your

[00:04:41] limit or you’re close to reaching your limit. So giving much more is not going to be a significant

[00:04:48] jump up. We have to think differently. We’ve got to change the way we’re thinking. All right.

[00:04:53] So what is this meta this meta concept. We’re going to talk about loops today. All right. And not to

[00:05:02] spoil it because we’re going to kind of paint the picture of what your life looks like without

[00:05:07] thinking about this automatically. Whether you know it or not whether you know it or not you are

[00:05:12] engaged in some loop or multiple loops. Everyone has multiples of these in your life. Right. So

[00:05:21] these are not like a scientifically valid.

[00:05:23] Construct. This is more. Think about it as a mental model a way of understanding the world.

[00:05:29] Your loop. Is is defined. Or you know the shape of it. Is determined. By default kind of

[00:05:42] automatically. Right. So the decisions you’ve made up to this point the kinds of pressures the

[00:05:49] kinds of biases the kinds of you know incentives that you have.

[00:05:53] Those kind of define your loop. Right. So everybody has heuristics for example. When you wake up.

[00:06:02] What is the first thing that you do. And so the most obvious example of a loop is wake up do a

[00:06:09] bunch of stuff sleep start over. Right. This is a loop that you go through. You may also have

[00:06:15] certain loops that play through when you’re in meetings. Right. So when something happens you do X.

[00:06:23] Then something else happens. You do Y. Then something else happens you do Z. And then the thing that

[00:06:30] triggers X starts back over. You keep doing this same kind of loop over and over. The loops are

[00:06:36] not necessarily repetitive. They can be complex. Right. If you were to think about this in terms of

[00:06:43] code a while loop doesn’t necessarily have to you know repeat the same thing over and over. It can

[00:06:49] have multiple conditionals. So you know while loop.

[00:06:53] you have no meetings, you will work on code, right? But if a meeting shows up, you’re going

[00:06:59] to run a different loop for your meeting, right? So think about this as the heuristics that are

[00:07:05] kind of built into your brain, you know, and you can kind of zoom way in on a very small version

[00:07:11] of a loop, or you can go much larger. In fact, very large. For example, if you are, if you’re

[00:07:18] like me, you tend to have loops that define the way that your career will play out. So you have a

[00:07:25] while happy at job, stay at job kind of loop, right? So this is kind of the default. We have

[00:07:32] a lot of things that inform our decision making loops. And the reason why I say they’re loops

[00:07:39] is because we very rarely move on from these behaviors. We rarely, you know, do

[00:07:48] work on code. We rarely move on from these behaviors. We rarely, you know, do work on code.

[00:07:48] We rarely, you know, do work on code. We rarely, you know, do work on code. We rarely, you know, do

[00:07:48] something once and never again, right? It is a behavior that we look for some kind of condition

[00:07:56] and we respond to that condition and then conditions change and then we’re looking for

[00:08:00] a condition and we’re responding to the condition again. So it is a, in that particular way, it’s a

[00:08:05] loop. So what we’re going to talk about today after our sponsor break, we’re going to talk

[00:08:11] about designing an inner and an outer. Today’s episode is sponsored by Unblocked. I’m happy to

[00:08:25] have Unblocked back as a sponsor. There’s a good chance that you’ve probably tried a few AI code

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[00:08:59] they’re directionally correct. AI is incredibly good at understanding code and finding bugs even.

[00:09:08] But it’s really,

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[00:09:11] limited by whether or not it has enough context. Most AI reviewers focus on surface level issues

[00:09:17] that don’t have enough context. Things like style knits, you know, obvious refactors, things that

[00:09:23] you would catch pretty easily if you were to go and just take a quick glance.

[00:09:28] You know, this is something that’s pretty much clear from the diff in the PR. Meanwhile,

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[00:11:10] dot com slash developer team. Thank you again to unblocked for sponsoring today’s episode.

[00:11:22] So we’re talking about loops today, and I want to kind of step back for a second and explain why

[00:11:30] this is so important in past episodes. In fact, uh, maybe as, as long ago as a decade on this show,

[00:11:38] we talked about things like useful,

[00:11:40] defaults. And the concept here is, uh, you know, much like I believe it’s James Clear who says that

[00:11:49] we, uh, we don’t rise to our level of aspiration, I think is, is the word he uses or rise to the

[00:11:56] level of our ambition maybe, but we fall to the level of our systems. And when he uses the word

[00:12:02] systems here, uh, you can kind of read that as habits. And he’s kind of famous for this,

[00:12:10] uh,

[00:12:10] for, for his book, Atomic Habits, right? So, um, our habits are the things that we do with very

[00:12:19] little conscious effort. It doesn’t take a lot of mental strain. It doesn’t take a lot of changing

[00:12:25] our behavior, you know, going out of our way. It’s something that we’re well set up to do with very

[00:12:33] little, uh, strain, very little effort. That doesn’t mean that the thing that we’re doing

[00:12:38] takes very little effort. For example, if you are,

[00:12:40] in the habit of, uh, you know, working out with intensity, the workout itself certainly takes

[00:12:47] effort, but the choice to do that, right? The, uh, the cognitive leap to make it to that habit,

[00:12:56] um, for some people that may be much harder than others, right? This kind of activation energy

[00:13:02] concept. And so when we talked about useful defaults in the past, we’re really talking about

[00:13:07] developing good habits and, and having,

[00:13:10] um, you know, an answer, an easy answer to what do I do when I don’t know what to do?

[00:13:18] What do I do if, uh, you know, I think that I’m done for the day, but it’s only halfway through

[00:13:25] the day. That’s a good, a good question. If you’re a manager, by the way, that’s a pretty

[00:13:29] good question to talk through with a junior report of yours, right? What do you do when you feel like

[00:13:36] maybe you’ve run out of work, right? Uh, you’ve kind of burned through the list of things that

[00:13:40] you have to do. This is kind of rare, right? Usually we have more work than we know what to do

[00:13:45] with. Um, and so you can ask, you can also ask the same question, uh, in that scenario, what do you

[00:13:52] do when there’s too much to do? Okay. So these are the beginning, uh, parts of loops. We’re kind

[00:14:00] of asking, what is your loop? When you get to the end of your list, what is the next thing that your

[00:14:10] loop? And you could call this a habit, but it doesn’t necessarily even have to be a habit.

[00:14:14] You could consciously choose to do this thing without it happening automatically, right?

[00:14:20] The useful defaults concept is, okay, what is the default thing that I fall back to? What is the

[00:14:26] thing that I do, uh, when, when I don’t know what else to do? What is the, the default behavior

[00:14:32] that I choose whenever I have too much to do, right? What is the default behavior, uh, you know,

[00:14:40] when I’m not doing it? What is the default behavior that I choose whenever I have too much to do?

[00:14:40] And I, um, and am interviewing someone, right? If you’re a, if you’re a manager, what is the

[00:14:46] default behavior when I’m reviewing someone’s code? How do I set myself up for success by having all

[00:14:54] of this, this long stack of useful defaults, right? Uh, for myself. All right. So, so then I want to

[00:15:03] talk a little bit about loops now, because they are sort of like useful defaults. Um, but they’re

[00:15:10] a little bit more of a conditional state, right? So a loop is something that you will do until some

[00:15:18] termination, right? This is, this is when we, when we talk about loops in code, that is, you know,

[00:15:25] you break out of a loop, right? And the loop is something that you’ll do while something else is

[00:15:30] true. And you may have multiple conditionals in a loop. You may have, you know, uh, while X and Y

[00:15:36] and Z, I will take these actions.

[00:15:40] All right. So, uh, this is especially interesting, um, as a mental model, as we continue to, uh,

[00:15:49] adopt new AI tools into our tool belt, because we’re designing these loops, right? The, the

[00:15:55] literal, uh, you know, loop in this case, um, so that they can repeat with some kind of, uh, uh,

[00:16:07] you know, process that happens over and over.

[00:16:10] And, uh, this is where we get the, the phrase human in the loop, right? So, uh, AI goes and

[00:16:19] does a thing. The human, uh, is asked a question. Maybe we’re asked for verification for, uh, you

[00:16:27] know, affirmation of a particular step. You know, maybe we’re asked to confirm that a, a, a, a

[00:16:32] particular kind of command that our AI agent wants to run is acceptable, right? So, so human in the

[00:16:40] loop is one tactic that we use to make the loop more effective. Okay. So, so that’s the mental

[00:16:47] model that we’re using here. Now I want you to think about this as an abstract concept in your

[00:16:54] career. Don’t think about this as, okay, how do I get my, you know, my coding work done? Think

[00:17:00] instead about this as what are the different loops that you engage in for your career growth?

[00:17:08] So for example,

[00:17:10] while it is a normal working week, I will continue to have recurring one-on-ones with all of my

[00:17:20] teammates. This is an example of a loop, right? While it is, uh, you know, while it is a holiday

[00:17:27] week, I will make it a point to, uh, put an out of office emoji on my Slack, uh, you know, status.

[00:17:37] That seems simple, right?

[00:17:40] So then hopefully with that last one, you’re asking, asking the question, why would you do

[00:17:44] that? What, what, why does that, why is that loop useful? And this is where we introduce the idea

[00:17:51] of an outer loop. Okay. The outer loop is kind of a meta observation. So it’s going to say, okay,

[00:18:01] I’m going to run a particular loop based on something else, right? And I’m going to look

[00:18:10] at that loop and I’m going to decide something about that loop. So for example, I may recognize

[00:18:17] with my outer loop that, uh, you know, I want to instill on my team, a culture of, uh, transparent

[00:18:26] communication and a culture, and this is for managers, right? Um, and, and it could also be

[00:18:32] a senior engineer, uh, that, that chooses to do something like this, uh, a culture of transparent

[00:18:38] communication and, uh, and, and, and, and, and, and, and, and, and, and, and, and, and, and,

[00:18:40] we want to make sure that people are taking the rest that they need. And so I’m going to set an

[00:18:45] example and therefore, right? So that’s the outer loop kind of reasoning. I’m looking at the

[00:18:53] behaviors of the team that I have. I have a bunch of other loops running, like we’re going to keep

[00:18:58] working. We’re going to keep doing our standups. We’re going to, you know, every, uh, every two

[00:19:03] weeks, we’re going to review the work that we’ve done and all of these things, right? We’re going

[00:19:07] to, uh, have retro. That’s part of a, another

[00:19:10] loop. So I’m looking at all of this information that’s coming out. My outer loop is saying,

[00:19:15] what does all this information mean? And what can I do? How can I respond to this by changing,

[00:19:23] adjusting my inner loops, right? And by the way, there’s not just two of these, right? And there’s,

[00:19:30] of course, you can have multiples of these that are larger and larger. And, um, you know,

[00:19:34] the further out you go, the more abstract you get, the closer to your personal values, probably you

[00:19:40] begin to, uh, you know, to, to get out away from the tactics of your work. So why would you do

[00:19:47] these things? For example, maybe an outer loop question. And so if you have this, this setup

[00:19:54] where you’re constantly evaluating, right? You’re evaluating on a loop. That is your,

[00:20:03] that outer loop behavior. And then on the inner loop, you recognize that this is not,

[00:20:10] this thing, uh, you know, this inner loop is not the whole picture. We’re going to perform these

[00:20:16] things. We’re going to stick with the inner loop. We’re going to do it as if it’s a protocol

[00:20:22] so that we have information that we can evaluate with the outer loop,

[00:20:26] right? So then we can adjust, we can sub, sub in, sub out. And what this allows you to do,

[00:20:33] if you, if you have this mental model and you’re approaching this with, uh, intention,

[00:20:40] you can actually make more informed adjustments to your behaviors, right? You can, you can adjust

[00:20:48] those, those, uh, inner loops in a way that, um, you know, provides more information about what

[00:20:57] the adjustment brought on. So this is essentially an experimental method, right? You know, you’re,

[00:21:05] you’re changing few variables. You’re having some kind of observation.

[00:21:10] And you’re doing this habitually. And so eventually, eventually you get to the place

[00:21:15] where your inner loop has been, uh, clarified and it’s been changed enough times that you

[00:21:26] can kind of view it as a default behavior. And so now your outer loop is helping you define

[00:21:33] your useful defaults, right? So if you’re not using this idea,

[00:21:40] if you’re not, um, if you don’t already have this set up, uh, as like a mental model for yourself,

[00:21:47] then most likely what you’re doing is you’re running one big loop. You’re trying something,

[00:21:53] you’re evaluating whatever happened when you tried it. And then you make an adjustment and

[00:21:57] you try something else. And this has worked for humans for a very long time, right? But if you

[00:22:04] can’t step out away and evaluate the system,

[00:22:10] and set yourself up for long-term success, then each of those efforts are going to be linear in,

[00:22:15] in their impact, right? You’re going to have a little change and then another little change.

[00:22:21] And it’s very hard to determine, you know, what the, what the overall direction is. It’s very hard

[00:22:27] to understand this as a recurring behavior, right? Uh, you can’t set up longer term conditionals that

[00:22:35] you care about. For example, I’m going to try this until I’m going to try this particular

[00:22:40] behavior until, right? That would be the until part is defined by that outer loop thinking,

[00:22:46] right? So the inner loop might be, I’m going to go to the gym. All right. But the outer loop is

[00:22:53] saying, I’m going to go to the gym for X amount of time until I determine whether it’s working.

[00:23:00] If this particular, you know, uh, uh, workout program is, is getting me the results that I want.

[00:23:08] And so if you don’t have that outer,

[00:23:10] you’re going to run into these problems where, uh, you can’t evaluate something

[00:23:17] on a longer term horizon because you don’t have anything governing the experiment, right?

[00:23:24] This is what I want you to take away from this is not necessarily that you need two loops.

[00:23:28] That’s kind of the bro, a broken way of thinking about it. It’s that we have these default loops.

[00:23:34] We have these responding opportunities, right? The, the,

[00:23:39] that we’re,

[00:23:40] that we’re kind of set up with. And if we can start to think about evaluating the recurring

[00:23:46] behavior, getting to an outer loop, right? It doesn’t have to be that you have, you know,

[00:23:53] some long list of loops that I run in your, in your obsidian, you know, your second brain or

[00:23:58] something. I, I say that because I’ve considered doing something like that myself. It’s probably

[00:24:03] not very useful. The behavior that the senior engineers that the, the most effective senior

[00:24:10] engineers, they may not even call it a loop, right? This is, this is just a mental model for

[00:24:13] you to capture this behavior. The core fundamental behavior here is being able to evaluate,

[00:24:21] right? Being able to step up a level and evaluate the system, not just the, the single behavior and

[00:24:29] the single outcome, but the system, the recurring behavior and the longer term trajectory outcomes,

[00:24:37] right? Uh, I, you know, I had one,

[00:24:39] one meeting and it went poorly. Now I’m never going to have a meeting again. That would be

[00:24:44] an example of not outer loop thinking, right? I had a meeting, it went poorly,

[00:24:49] but I’m going to run the experiment for five iterations and then we’ll decide what to do

[00:24:54] from there, right? That is outer loop thinking. Thank you so much for listening to today’s

[00:24:59] episode of Developer Tea. Thank you again to Unblocked for sponsoring today’s episode.

[00:25:04] Remember, you can get three weeks for free, uh, three weeks of Unblocked for free.

[00:25:09] And,

[00:25:09] uh, critically, um, if you are currently using other AI review tools and you’re,

[00:25:16] you’re about to write them off, uh, try Unblocked because it’s going to give you

[00:25:20] higher context in your reviews, like a senior engineer would have. This is one of those,

[00:25:25] an example of a system that you can evaluate from the outside looking in. You got three weeks to try

[00:25:29] it out for free. That’s, uh, getunblocked.com slash developer tea. Thank you so much for listening.

[00:25:34] If you enjoyed this episode, you can find us on Apple podcasts. You can find us on any podcast

[00:25:39] player.

[00:25:39] Of course, you can also now find us on YouTube with developer tea channel on YouTube. Thanks

[00:25:45] so much for listening. And until next time, enjoy your tea.

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