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Many (most?) engineers go from university to a sizable company significantly distancing them from the actual value their code creates. They labour under the delusion that they’re paid to write code. In fact, they’re paid to make money, and writing code is probably the most expensive way that they can do that. They will often say things like “We should scrap this entirely and re-write it, it will only take 8 months” – often about code that generates 8 figures in revenue and employs several dozen people. Code that pays for their smartwatches. But, of course: Engineers are hired to create business value, not to program things – Don’t Call Yourself A Programmer, And Other Career Advice In my estimate it takes about a decade of experience before engineers start to really internalize this. This can be significantly sped up by having a shorter feedback loop between the code written and the value realized by the engineer. There are two ways to do this: Freelancing Founding Freelancing By freelancing, and doing it well, the reward, is very directly tied to the code written. The best way to do freelance, for the sake of learning, would be to work on fixed cost contracts – which isn’t great freelancing advice, but is excellent for the longterm career. Delivering to someone elses specs makes engineers focused on delivery only the necessary and sufficient code to make that happen. All the correct decisions result in an improvement of the engineers earnings per hour and all mistakes in a reduction. That feedback loop very quickly teaches: The importance of quality and automated testing Architecture and keeping options open Communication and requirements gathering, asking the right questions All of these are factors that come into play once an engineer is breaking the barrier from Senior to management or Staff. Founding a company Founding a company, where the code that you produced secures your salary, teaches those lessons, plus a few others: Understanding the importance tradeoffs that companies make betwen velocity and tech debt It is also an opportunity to learn how to make those tradeoffs well, something engineers aren’t always great at Experience creating the most value possible with the least code Very few enginers pre-emtively suggest ways to test product hyptheses using cheaper appoaches Pragmatism and bias towards shipping and avoidingg gold-plating functionality that is immature Plus you very quickly start to understand why “We should re-write it” is almost never the right business decision. All software engineers should freelance or found a business was originally published by Ognjen Regoje at Ognjen Regoje • ognjen.io on April 18, 2025.
In The Innovator’s Dilemma Christensen talks about how when acquiring a company you might either be acquiring its product or its processes. Depending on which it is, you need to handle the integration differently. I’ve realized that hiring a new manager follows a similar pattern: either they’re expected to integrate into the organization, or be independent and create some change. That expectation depends on whether the team, and possibly the wider organization, function well. If the team is high-performing, why would adding or overhauling processes make sense over fine-tuning existing ones? But new managers often join and immediately start suggesting ways to fix things. In many of these cases, they aren’t suggesting some best practices but are simply trying to have the new company function in a similar way to their previous one. But they never have enough context to justify these changes. What they should do is take a step back and understand why they were hired and what already works. Are they there to run the team as it is and perhaps look for marginal gains in efficiency and effectiveness? Or are they there because things are fundamentally broken and they need to overhaul the organization? In 9 out of 10 cases, it’s the first one. They’re there to ensure the continuity of the team. Therefore in 9 out of 10 cases the objective should be to integrate into the processes as quickly as possible and help iterate. Why are you here, manager? was originally published by Ognjen Regoje at Ognjen Regoje • ognjen.io on April 18, 2025.
I love Ben Brode’s Design Lessons from Improv talk. It presents techniques that we could all use more frequently. I particularly took the “Yes, and…“ to heart. It is an excellent technique, or attitude really, that keeps the conversation going. Conversations often start slow but get progressively more interesting the deeper you go. And “Yes, and…” makes it possible to get there. One of my favorite uses of “Yes, and…” is when someone sends you an article that you’ve already read or a video you’ve already watched. The typical response might be 👍 seen it (A whole site is named after the fact that you’ve already read it) If the other person is interested in having a conversation, you’ve just stopped it in its tracks expecting them to put in all the effort to keep it going. A “Yes, and…” response such as “Yes, I’ve read it, and something you found interesting” opens up the conversation. Even if the other person just wanted to share something they thought you might find interesting, you’ve: a) created an opportunity to exchange opinions and b) put in slightly above the bare minimum of effort to acknowledge that what they shared with you was indeed interesting At work At work, specifically, it is useful in all manner of discussions. Conversations about product, or code, or architecture, or team activities, or customer service all get better when you don’t dismiss but build on top of each other. The value of "Yes, and..." was originally published by Ognjen Regoje at Ognjen Regoje • ognjen.io on April 17, 2025.
One of the best pieces of advice I’ve ever gotten is to take a minute, or a week, after you’ve had a difficult conversation. By and large, people are not unreasonable. They’re not out to get you. They’re not trying to make your life miserable. They’re probably trying to do what they think is right. But tough conversations happen and when they do it’s important to take time to process the information and formulate a more nuanced opinion. To take a work example: picture a conversation where you’re being some particularly heavy feedback You’re confused, you’re sad, you’re angry. You disagree. You want to protest, defend yourself, argue, explain. Doing so, however, would accomplish nothing in the immediate, and probably set you back in the long-term. The other person is probably also upset and stressed about having to have the conversation. Getting defensive would get make them to do the same and the conversation would quickly devolve into one run by emotions. Instead, listen and gather as much information as possible. If possible, try to write as much as you can down. Don’t say much except ask questions and then politely ask for a follow-up meeting in a few days. That will give you the time to process all the information and figure out if they were right, if it might not have been a big deal at all, if there is nuance in the situation or if you were indeed right. Or, as is most likely, some combination of all of the above. You’ll be able to formulate a cohesive model of the situation in your head, which will help you make a better decision or counter-argument if needed. It’ll also give you, and the others, time to cool down and prevent anyone from reacting too emotionally. Come to the follow-up meeting with humility and a willingness to compromise. Recap the previous meeting and make sure that everyone is on the same page. Then explain your understanding of the situation and present your opinion. The end result should be a much more amicable outcome without the need for a third meeting. And while my example is in the context of work, the same is true for personal conversations. So, take a minute. Or a week. It’ll help you make better decisions. During a difficult conversation, remember to take a minute was originally published by Ognjen Regoje at Ognjen Regoje • ognjen.io on April 17, 2025.
There is nothing as inevitable as a re-org when a new VP joins. When a new executive joins they’re often overwhelmed by the amount of context they need to absorb to start being effective. The more seasoned ones aren’t pertrubed by this: they understand that gathering this context is their full-time job for the next several weeks or months. There’s even a book about this period. The less savvy ones, on the other hand, often reach for one of the following coping strategies, depending on the type of role they occupy. This organization makes no sense, we must re-organize it immediately Spoken by a newly joined VP who needs to assess the organization and understand why it is set up the way it is. It results in several workshops about boundaries, Conway’s law and team topologies result in a slightly different, but not materially significant organization. And a VP with a much better understanding of their people, the culture, the product and the challenges. We must document/map it Spoken by a product manager getting to grips with the features they’ll be working on before having read the abundant sales, technical and product reference materials. This usually results in several workshops where there is a lot of “discovery” and “mapping”. In reality, the product manager is getting an in-person crash course. It rarely results in any new discoveries or documentation or maps being produced but always results in a much more confident product manager. We must have a process for that Spoken by a new engineering manager who’s not yet familiar with the existing processes and ways of working. This usually results in the engineering manager starting to write a Confluence page on how the process should work, until one of the team members sends them an existing, but finished, Confluence page on exactly that, but with slight differences. The new page gets a link to the existing ones and is promptly forgotten. Does this process really work for anyone? A sub-category of the above then the process in place is different from their previous employer. This code is so bad, we must re-write it entirely Spoken by a senior but not yet quite staff engineer who’s just getting to grips with a new codebase – often about code that generates 7 or 8 digits in revenue. It results in the engineer spending several hours on an alternative architecture and running it by their team several times. Eventually, they understand that what they’re suggesting is quite similar to what is actually in place, that there is some refactoring and improvements to be done, but it’s nowhere near as tragic as they imagined it to be. Why does this happen? A week or two after joining, depending on how generous the company is, the engineer gets a ticket to work on, the PM is asked about the backlog priority and the EM why their bug injection rate is so high and what they’re doing about it. And they naturally feel lost. The problem is that most companies don’t set an expected timeline for having a person become effective in their position. How to do better? The amount of context required to be effective increases with seniority. But everyone needs a couple of weeks outside of the default onboarding programme to read through their team’s wiki space, to look through the backlog, to pair with their colleagues, to get an understanding of the work the team is doing, to be present at the retrospectives to listen and not have to lead and facilitate. Only after they get the lay of the land can they start contributing in a meaningful way. The managerial fear of the unknown was originally published by Ognjen Regoje at Ognjen Regoje • ognjen.io on April 17, 2025.
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We received over 2,200 applications for our just-closed junior programmer opening, and now we're going through all of them by hand and by human. No AI screening here. It's a lot of work, but we have a great team who take the work seriously, so in a few weeks, we'll be able to invite a group of finalists to the next phase. This highlights the folly of thinking that what it'll take to land a job like this is some specific list of criteria, though. Yes, you have to present a baseline of relevant markers to even get into consideration, like a great cover letter that doesn't smell like AI slop, promising projects or work experience or educational background, etc. But to actually get the job, you have to be the best of the ones who've applied! It sounds self-evident, maybe, but I see questions time and again about it, so it must not be. Almost every job opening is grading applicants on the curve of everyone who has applied. And the best candidate of the lot gets the job. You can't quantify what that looks like in advance. I'm excited to see who makes it to the final stage. I already hear early whispers that we got some exceptional applicants in this round. It would be great to help counter the narrative that this industry no longer needs juniors. That's simply retarded. However good AI gets, we're always going to need people who know the ins and outs of what the machine comes up with. Maybe not as many, maybe not in the same roles, but it's truly utopian thinking that mankind won't need people capable of vetting the work done by AI in five minutes.
Recently I got a question on formal methods1: how does it help to mathematically model systems when the system requirements are constantly changing? It doesn't make sense to spend a lot of time proving a design works, and then deliver the product and find out it's not at all what the client needs. As the saying goes, the hard part is "building the right thing", not "building the thing right". One possible response: "why write tests"? You shouldn't write tests, especially lots of unit tests ahead of time, if you might just throw them all away when the requirements change. This is a bad response because we all know the difference between writing tests and formal methods: testing is easy and FM is hard. Testing requires low cost for moderate correctness, FM requires high(ish) cost for high correctness. And when requirements are constantly changing, "high(ish) cost" isn't affordable and "high correctness" isn't worthwhile, because a kinda-okay solution that solves a customer's problem is infinitely better than a solid solution that doesn't. But eventually you get something that solves the problem, and what then? Most of us don't work for Google, we can't axe features and products on a whim. If the client is happy with your solution, you are expected to support it. It should work when your customers run into new edge cases, or migrate all their computers to the next OS version, or expand into a market with shoddy internet. It should work when 10x as many customers are using 10x as many features. It should work when you add new features that come into conflict. And just as importantly, it should never stop solving their problem. Canonical example: your feature involves processing requested tasks synchronously. At scale, this doesn't work, so to improve latency you make it asynchronous. Now it's eventually consistent, but your customers were depending on it being always consistent. Now it no longer does what they need, and has stopped solving their problems. Every successful requirement met spawns a new requirement: "keep this working". That requirement is permanent, or close enough to decide our long-term strategy. It takes active investment to keep a feature behaving the same as the world around it changes. (Is this all a pretentious of way of saying "software maintenance is hard?" Maybe!) Phase changes In physics there's a concept of a phase transition. To raise the temperature of a gram of liquid water by 1° C, you have to add 4.184 joules of energy.2 This continues until you raise it to 100°C, then it stops. After you've added two thousand joules to that gram, it suddenly turns into steam. The energy of the system changes continuously but the form, or phase, changes discretely. Software isn't physics but the idea works as a metaphor. A certain architecture handles a certain level of load, and past that you need a new architecture. Or a bunch of similar features are independently hardcoded until the system becomes too messy to understand, you remodel the internals into something unified and extendable. etc etc etc. It's doesn't have to be totally discrete phase transition, but there's definitely a "before" and "after" in the system form. Phase changes tend to lead to more intricacy/complexity in the system, meaning it's likely that a phase change will introduce new bugs into existing behaviors. Take the synchronous vs asynchronous case. A very simple toy model of synchronous updates would be Set(key, val), which updates data[key] to val.3 A model of asynchronous updates would be AsyncSet(key, val, priority) adds a (key, val, priority, server_time()) tuple to a tasks set, and then another process asynchronously pulls a tuple (ordered by highest priority, then earliest time) and calls Set(key, val). Here are some properties the client may need preserved as a requirement: If AsyncSet(key, val, _, _) is called, then eventually db[key] = val (possibly violated if higher-priority tasks keep coming in) If someone calls AsyncSet(key1, val1, low) and then AsyncSet(key2, val2, low), they should see the first update and then the second (linearizability, possibly violated if the requests go to different servers with different clock times) If someone calls AsyncSet(key, val, _) and immediately reads db[key] they should get val (obviously violated, though the client may accept a slightly weaker property) If the new system doesn't satisfy an existing customer requirement, it's prudent to fix the bug before releasing the new system. The customer doesn't notice or care that your system underwent a phase change. They'll just see that one day your product solves their problems, and the next day it suddenly doesn't. This is one of the most common applications of formal methods. Both of those systems, and every one of those properties, is formally specifiable in a specification language. We can then automatically check that the new system satisfies the existing properties, and from there do things like automatically generate test suites. This does take a lot of work, so if your requirements are constantly changing, FM may not be worth the investment. But eventually requirements stop changing, and then you're stuck with them forever. That's where models shine. As always, I'm using formal methods to mean the subdiscipline of formal specification of designs, leaving out the formal verification of code. Mostly because "formal specification" is really awkward to say. ↩ Also called a "calorie". The US "dietary Calorie" is actually a kilocalorie. ↩ This is all directly translatable to a TLA+ specification, I'm just describing it in English to avoid paying the syntax tax ↩
While Stripe is a widely admired company for things like its creation of the Sorbet typer project, I personally think that Stripe’s most interesting strategy work is also among its most subtle: its willingness to significantly prioritize API stability. This strategy is almost invisible externally. Internally, discussions around it were frequent and detailed, but mostly confined to dedicated API design conversations. API stability isn’t just a technical design quirk, it’s a foundational decision in an API-driven business, and I believe it is one of the unsung heroes of Stripe’s business success. This is an exploratory, draft chapter for a book on engineering strategy that I’m brainstorming in #eng-strategy-book. As such, some of the links go to other draft chapters, both published drafts and very early, unpublished drafts. Reading this document To apply this strategy, start at the top with Policy. To understand the thinking behind this strategy, read sections in reverse order, starting with Explore. More detail on this structure in Making a readable Engineering Strategy document. Policy & Operation Our policies for managing API changes are: Design for long API lifetime. APIs are not inherently durable. Instead we have to design thoughtfully to ensure they can support change. When designing a new API, build a test application that doesn’t use this API, then migrate to the new API. Consider how integrations might evolve as applications change. Perform these migrations yourself to understand potential friction with your API. Then think about the future changes that we might want to implement on our end. How would those changes impact the API, and how would they impact the application you’ve developed. At this point, take your API to API Review for initial approval as described below. Following that approval, identify a handful of early adopter companies who can place additional pressure on your API design, and test with them before releasing the final, stable API. All new and modified APIs must be approved by API Review. API changes may not be enabled for customers prior to API Review approval. Change requests should be sent to api-review email group. For examples of prior art, review the api-review archive for prior requests and the feedback they received. All requests must include a written proposal. Most requests will be approved asynchronously by a member of API Review. Complex or controversial proposals will require live discussions to ensure API Review members have sufficient context before making a decision. We never deprecate APIs without an unavoidable requirement to do so. Even if it’s technically expensive to maintain support, we incur that support cost. To be explicit, we define API deprecation as any change that would require customers to modify an existing integration. If such a change were to be approved as an exception to this policy, it must first be approved by the API Review, followed by our CEO. One example where we granted an exception was the deprecation of TLS 1.2 support due to PCI compliance obligations. When significant new functionality is required, we add a new API. For example, we created /v1/subscriptions to support those workflows rather than extending /v1/charges to add subscriptions support. With the benefit of hindsight, a good example of this policy in action was the introduction of the Payment Intents APIs to maintain compliance with Europe’s Strong Customer Authentication requirements. Even in that case the charge API continued to work as it did previously, albeit only for non-European Union payments. We manage this policy’s implied technical debt via an API translation layer. We release changed APIs into versions, tracked in our API version changelog. However, we only maintain one implementation internally, which is the implementation of the latest version of the API. On top of that implementation, a series of version transformations are maintained, which allow us to support prior versions without maintaining them directly. While this approach doesn’t eliminate the overhead of supporting multiple API versions, it significantly reduces complexity by enabling us to maintain just a single, modern implementation internally. All API modifications must also update the version transformation layers to allow the new version to coexist peacefully with prior versions. In the future, SDKs may allow us to soften this policy. While a significant number of our customers have direct integrations with our APIs, that number has dropped significantly over time. Instead, most new integrations are performed via one of our official API SDKs. We believe that in the future, it may be possible for us to make more backwards incompatible changes because we can absorb the complexity of migrations into the SDKs we provide. That is certainly not the case yet today. Diagnosis Our diagnosis of the impact on API changes and deprecation on our business is: If you are a small startup composed of mostly engineers, integrating a new payments API seems easy. However, for a small business without dedicated engineers—or a larger enterprise involving numerous stakeholders—handling external API changes can be particularly challenging. Even if this is only marginally true, we’ve modeled the impact of minimizing API changes on long-term revenue growth, and it has a significant impact, unlocking our ability to benefit from other churn reduction work. While we believe API instability directly creates churn, we also believe that API stability directly retains customers by increasing the migration overhead even if they wanted to change providers. Without an API change forcing them to change their integration, we believe that hypergrowth customers are particularly unlikely to change payments API providers absent a concrete motivation like an API change or a payment plan change. We are aware of relatively few companies that provide long-term API stability in general, and particularly few for complex, dynamic areas like payments APIs. We can’t assume that companies that make API changes are ill-informed. Rather it appears that they experience a meaningful technical debt tradeoff between the API provider and API consumers, and aren’t willing to consistently absorb that technical debt internally. Future compliance or security requirements—along the lines of our upgrade from TLS 1.2 to TLS 1.3 for PCI—may necessitate API changes. There may also be new tradeoffs exposed as we enter new markets with their own compliance regimes. However, we have limited ability to predict these changes at this point.
I like the job title “Design Engineer”. When required to label myself, I feel partial to that term (I should, I’ve written about it enough). Lately I’ve felt like the term is becoming more mainstream which, don’t get me wrong, is a good thing. I appreciate the diversification of job titles, especially ones that look to stand in the middle between two binaries. But — and I admit this is a me issue — once a title starts becoming mainstream, I want to use it less and less. I was never totally sure why I felt this way. Shouldn’t I be happy a title I prefer is gaining acceptance and understanding? Do I just want to rebel against being labeled? Why do I feel this way? These were the thoughts simmering in the back of my head when I came across an interview with the comedian Brian Regan where he talks about his own penchant for not wanting to be easily defined: I’ve tried over the years to write away from how people are starting to define me. As soon as I start feeling like people are saying “this is what you do” then I would be like “Alright, I don't want to be just that. I want to be more interesting. I want to have more perspectives.” [For example] I used to crouch around on stage all the time and people would go “Oh, he’s the guy who crouches around back and forth.” And I’m like, “I’ll show them, I will stand erect! Now what are you going to say?” And then they would go “You’re the guy who always feels stupid.” So I started [doing other things]. He continues, wondering aloud whether this aversion to not being easily defined has actually hurt his career in terms of commercial growth: I never wanted to be something you could easily define. I think, in some ways, that it’s held me back. I have a nice following, but I’m not huge. There are people who are huge, who are great, and deserve to be huge. I’ve never had that and sometimes I wonder, ”Well maybe it’s because I purposely don’t want to be a particular thing you can advertise or push.” That struck a chord with me. It puts into words my current feelings towards the job title “Design Engineer” — or any job title for that matter. Seven or so years ago, I would’ve enthusiastically said, “I’m a Design Engineer!” To which many folks would’ve said, “What’s that?” But today I hesitate. If I say “I’m a Design Engineer” there are less follow up questions. Now-a-days that title elicits less questions and more (presumed) certainty. I think I enjoy a title that elicits a “What’s that?” response, which allows me to explain myself in more than two or three words, without being put in a box. But once a title becomes mainstream, once people begin to assume they know what it means, I don’t like it anymore (speaking for myself, personally). As Brian says, I like to be difficult to define. I want to have more perspectives. I like a title that befuddles, that doesn’t provide a presumed sense of certainty about who I am and what I do. And I get it, that runs counter to the very purpose of a job title which is why I don’t think it’s good for your career to have the attitude I do, lol. I think my own career evolution has gone something like what Brian describes: Them: “Oh you’re a Designer? So you make mock-ups in Photoshop and somebody else implements them.” Me: “I’ll show them, I’ll implement them myself! Now what are you gonna do?” Them: “Oh, so you’re a Design Engineer? You design and build user interfaces on the front-end.” Me: “I’ll show them, I’ll write a Node server and setup a database that powers my designs and interactions on the front-end. Now what are they gonna do?” Them: “Oh, well, we I’m not sure we have a term for that yet, maybe Full-stack Design Engineer?” Me: “Oh yeah? I’ll frame up a user problem, interface with stakeholders, explore the solution space with static designs and prototypes, implement a high-fidelity solution, and then be involved in testing, measuring, and refining said solution. What are you gonna call that?” [As you can see, I have some personal issues I need to work through…] As Brian says, I want to be more interesting. I want to have more perspectives. I want to be something that’s not so easily definable, something you can’t sum up in two or three words. I’ve felt this tension my whole career making stuff for the web. I think it has led me to work on smaller teams where boundaries are much more permeable and crossing them is encouraged rather than discouraged. All that said, I get it. I get why titles are useful in certain contexts (corporate hierarchies, recruiting, etc.) where you’re trying to take something as complicated and nuanced as an individual human beings and reduce them to labels that can be categorized in a database. I find myself avoiding those contexts where so much emphasis is placed in the usefulness of those labels. “I’ve never wanted to be something you could easily define” stands at odds with the corporate attitude of, “Here’s the job req. for the role (i.e. cog) we’re looking for.” Email · Mastodon · Bluesky
I've been biking in Brooklyn for a few years now! It's hard for me to believe it, but I'm now one of the people other bicyclists ask questions to now. I decided to make a zine that answers the most common of those questions: Bike Brooklyn! is a zine that touches on everything I wish I knew when I started biking in Brooklyn. A lot of this information can be found in other resources, but I wanted to collect it in one place. I hope to update this zine when we get significantly more safe bike infrastructure in Brooklyn and laws change to make streets safer for bicyclists (and everyone) over time, but it's still important to note that each release will reflect a specific snapshot in time of bicycling in Brooklyn. All text and illustrations in the zine are my own. Thank you to Matt Denys, Geoffrey Thomas, Alex Morano, Saskia Haegens, Vishnu Reddy, Ben Turndorf, Thomas Nayem-Huzij, and Ryan Christman for suggestions for content and help with proofreading. This zine is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, so you can copy and distribute this zine for noncommercial purposes in unadapted form as long as you give credit to me. Check out the Bike Brooklyn! zine on the web or download pdfs to read digitally or print here!
