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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.
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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In my post yesterday (“ARM is great, ARM is terrible (and so is RISC-V)), I described my desire to find ARM hardware with AES instructions to support full-disk encryption, and the poor state of the OS ecosystem around the newer ARM boards. I was anticipating buying either a newer ARM SBC or an x86 mini … Continue reading Performant Full-Disk Encryption on a Raspberry Pi, but Foiled by Twisty UARTs →
Debates, at their finest, are about exploring topics together in search for truth. That probably sounds hopelessly idealistic to anyone who've ever perused a comment section on the internet, but ideals are there to remind us of what's possible, to inspire us to reach higher — even if reality falls short. I've been reaching for those debating ideals for thirty years on the internet. I've argued with tens of thousands of people, first on Usenet, then in blog comments, then Twitter, now X, and also LinkedIn — as well as a million other places that have come and gone. It's mostly been about technology, but occasionally about society and morality too. There have been plenty of heated moments during those three decades. It doesn't take much for a debate between strangers on this internet to escalate into something far lower than a "search for truth", and I've often felt willing to settle for just a cordial tone! But for the majority of that time, I never felt like things might escalate beyond the keyboards and into the real world. That was until we had our big blow-up at 37signals back in 2021. I suddenly got to see a different darkness from the most vile corners of the internet. Heard from those who seem to prowl for a mob-sanctioned opportunity to threaten and intimidate those they disagree with. It fundamentally changed me. But I used the experience as a mirror to reflect on the ways my own engagement with the arguments occasionally felt too sharp, too personal. And I've since tried to refocus way more of my efforts on the positive and the productive. I'm by no means perfect, and the internet often tempts the worst in us, but I resist better now than I did then. What I cannot come to terms with, though, is the modern equation of words with violence. The growing sense of permission that if the disagreement runs deep enough, then violence is a justified answer to settle it. That sounds so obvious that we shouldn't need to state it in a civil society, but clearly it is not. Not even in technology. Not even in programming. There are plenty of factions here who've taken to justify their violent fantasies by referring to their ideological opponents as "nazis", "fascists", or "racists". And then follow that up with a call to "punch a nazi" or worse. When you hear something like that often enough, it's easy to grow glib about it. That it's just a saying. They don't mean it. But I'm afraid many of them really do. Which brings us to Charlie Kirk. And the technologists who name drinks at their bar after his mortal wound just hours after his death, to name but one of the many, morbid celebrations of the famous conservative debater's death. It's sickening. Deeply, profoundly sickening. And my first instinct was exactly what such people would delight in happening. To watch the rest of us recoil, then retract, and perhaps even eject. To leave the internet for a while or forever. But I can't do that. We shouldn't do that. Instead, we should double down on the opposite. Continue to show up with our ideals held high while we debate strangers in that noble search for the truth. Where we share our excitement, our enthusiasm, and our love of technology, country, and humanity. I think that's what Charlie Kirk did so well. Continued to show up for the debate. Even on hostile territory. Not because he thought he was ever going to convince everyone, but because he knew he'd always reach some with a good argument, a good insight, or at least a different perspective. You could agree or not. Counter or be quiet. But the earnest exploration of the topics in a live exchange with another human is as fundamental to our civilization as Socrates himself. Don't give up, don't give in. Keep debating.
Although it looks really good, I have not yet tried the Jujutsu (jj) version control system, mainly because it’s not yet clearly superior to Magit. But I have been following jj discussions with great interest. One of the things that jj has not yet tackled is how to do better than git refs / branches / tags. As I underestand it, jj currently has something like Mercurial bookmarks, which are more like raw git ref plumbing than a high-level porcelain feature. In particular, jj lacks signed or annotated tags, and it doesn’t have branch names that always automatically refer to the tip. This is clearly a temporary state of affairs because jj is still incomplete and under development and these gaps are going to be filled. But the discussions have led me to think about how git’s branches are unsatisfactory, and what could be done to improve them. branch merge rebase squash fork cover letters previous branch workflow questions branch One of the huge improvements in git compared to Subversion was git’s support for merges. Subversion proudly advertised its support for lightweight branches, but a branch is not very useful if you can’t merge it: an un-mergeable branch is not a tool you can use to help with work-in-progress development. The point of this anecdote is to illustrate that rather than trying to make branches better, we should try to make merges better and branches will get better as a consequence. Let’s consider a few common workflows and how git makes them all unsatisfactory in various ways. Skip to cover letters and previous branch below where I eventually get to the point. merge A basic merge workflow is, create a feature branch hack, hack, review, hack, approve merge back to the trunk The main problem is when it comes to the merge, there may be conflicts due to concurrent work on the trunk. Git encourages you to resolve conflicts while creating the merge commit, which tends to bypass the normal review process. Git also gives you an ugly useless canned commit message for merges, that hides what you did to resolve the conflicts. If the feature branch is a linear record of the work then it can be cluttered with commits to address comments from reviewers and to fix mistakes. Some people like an accurate record of the history, but others prefer the repository to contain clean logical changes that will make sense in years to come, keeping the clutter in the code review system. rebase A rebase-oriented workflow deals with the problems of the merge workflow but introduces new problems. Primarily, rebasing is intended to produce a tidy logical commit history. And when a feature branch is rebased onto the trunk before it is merged, a simple fast-forward check makes it trivial to verify that the merge will be clean (whether it uses separate merge commit or directly fast-forwards the trunk). However, it’s hard to compare the state of the feature branch before and after the rebase. The current and previous tips of the branch (amongst other clutter) are recorded in the reflog of the person who did the rebase, but they can’t share their reflog. A force-push erases the previous branch from the server. Git forges sometimes make it possible to compare a branch before and after a rebase, but it’s usually very inconvenient, which makes it hard to see if review comments have been addressed. And a reviewer can’t fetch past versions of the branch from the server to review them locally. You can mitigate these problems by adding commits in --autosquash format, and delay rebasing until just before merge. However that reintroduces the problem of merge conflicts: if the autosquash doesn’t apply cleanly the branch should have another round of review to make sure the conflicts were resolved OK. squash When the trunk consists of a sequence of merge commits, the --first-parent log is very uninformative. A common way to make the history of the trunk more informative, and deal with the problems of cluttered feature branches and poor rebase support, is to squash the feature branch into a single commit on the trunk instead of mergeing. This encourages merge requests to be roughly the size of one commit, which is arguably a good thing. However, it can be uncomfortably confining for larger features, or cause extra busy-work co-ordinating changes across multiple merge requests. And squashed feature branches have the same merge conflict problem as rebase --autosquash. fork Feature branches can’t always be short-lived. In the past I have maintained local hacks that were used in production but were not (not yet?) suitable to submit upstream. I have tried keeping a stack of these local patches on a git branch that gets rebased onto each upstream release. With this setup the problem of reviewing successive versions of a merge request becomes the bigger problem of keeping track of how the stack of patches evolved over longer periods of time. cover letters Cover letters are common in the email patch workflow that predates git, and they are supported by git format-patch. Github and other forges have a webby version of the cover letter: the message that starts off a pull request or merge request. In git, cover letters are second-class citizens: they aren’t stored in the repository. But many of the problems I outlined above have neat solutions if cover letters become first-class citizens, with a Jujutsu twist. A first-class cover letter starts off as a prototype for a merge request, and becomes the eventual merge commit. Instead of unhelpful auto-generated merge commits, you get helpful and informative messages. No extra work is needed since we’re already writing cover letters. Good merge commit messages make good --first-parent logs. The cover letter subject line works as a branch name. No more need to invent filename-compatible branch names! Jujutsu doesn’t make you name branches, giving them random names instead. It shows the subject line of the topmost commit as a reminder of what the branch is for. If there’s an explicit cover letter the subject line will be a better summary of the branch as a whole. I often find the last commit on a branch is some post-feature cleanup, and that kind of commit has a subject line that is never a good summary of its feature branch. As a prototype for the merge commit, the cover letter can contain the resolution of all the merge conflicts in a way that can be shared and reviewed. In Jujutsu, where conflicts are first class, the cover letter commit can contain unresolved conflicts: you don’t have to clean them up when creating the merge, you can leave that job until later. If you can share a prototype of your merge commit, then it becomes possible for your collaborators to review any merge conflicts and how you resolved them. To distinguish a cover letter from a merge commit object, a cover letter object has a “target” header which is a special kind of parent header. A cover letter also has a normal parent commit header that refers to earlier commits in the feature branch. The target is what will become the first parent of the eventual merge commit. previous branch The other ingredient is to add a “previous branch” header, another special kind of parent commit header. The previous branch header refers to an older version of the cover letter and, transitively, an older version of the whole feature branch. Typically the previous branch header will match the last shared version of the branch, i.e. the commit hash of the server’s copy of the feature branch. The previous branch header isn’t changed during normal work on the feature branch. As the branch is revised and rebased, the commit hash of the cover letter will change fairly frequently. These changes are recorded in git’s reflog or jj’s oplog, but not in the “previous branch” chain. You can use the previous branch chain to examine diffs between versions of the feature branch as a whole. If commits have Gerrit-style or jj-style change-IDs then it’s fairly easy to find and compare previous versions of an individual commit. The previous branch header supports interdiff code review, or allows you to retain past iterations of a patch series. workflow Here are some sketchy notes on how these features might work in practice. One way to use cover letters is jj-style, where it’s convenient to edit commits that aren’t at the tip of a branch, and easy to reshuffle commits so that a branch has a deliberate narrative. When you create a new feature branch, it starts off as an empty cover letter with both target and parent pointing at the same commit. Alternatively, you might start a branch ad hoc, and later cap it with a cover letter. If this is a small change and rebase + fast-forward is allowed, you can edit the “cover letter” to contain the whole change. Otherwise, you can hack on the branch any which way. Shuffle the commits that should be part of the merge request so that they occur before the cover letter, and edit the cover letter to summarize the preceding commits. When you first push the branch, there’s (still) no need to give it a name: the server can see that this is (probably) going to be a new merge request because the top commit has a target branch and its change-ID doesn’t match an existing merge request. Also when you push, your client automatically creates a new instance of your cover letter, adding a “previous branch” header to indicate that the old version was shared. The commits on the branch that were pushed are now immutable; rebases and edits affect the new version of the branch. During review there will typically be multiple iterations of the branch to address feedback. The chain of previous branch headers allows reviewers to see how commits were changed to address feedback, interdiff style. The branch can be merged when the target header matches the current trunk and there are no conflicts left to resolve. When the time comes to merge the branch, there are several options: For a merge workflow, the cover letter is used to make a new commit on the trunk, changing the target header into the first parent commit, and dropping the previous branch header. Or, if you like to preserve more history, the previous branch chain can be retained. Or you can drop the cover letter and fast foward the branch on to the trunk. Or you can squash the branch on to the trunk, using the cover letter as the commit message. questions This is a fairly rough idea: I’m sure that some of the details won’t work in practice without a lot of careful work on compatibility and deployability. Do the new commit headers (“target” and “previous branch”) need to be headers? What are the compatibility issues with adding new headers that refer to other commits? How would a server handle a push of an unnamed branch? How could someone else pull a copy of it? How feasible is it to use cover letter subject lines instead of branch names? The previous branch header is doing a similar job to a remote tracking branch. Is there an opportunity to simplify how we keep a local cache of the server state? Despite all that, I think something along these lines could make branches / reviews / reworks / merges less awkward. How you merge should me a matter of your project’s preferred style, without interference from technical limitations that force you to trade off one annoyance against another. There remains a non-technical limitation: I have assumed that contributors are comfortable enough with version control to use a history-editing workflow effectively. I’ve lost all perspective on how hard this is for a newbie to learn; I expect (or hope?) jj makes it much easier than git rebase.
I’ve long been interested in new and different platforms. I ran Debian on an Alpha back in the late 1990s and was part of the Alpha port team; then I helped bootstrap Debian on amd64. I’ve got somewhere around 8 Raspberry Pi devices in active use right now, and the free NNCPNET Internet email service … Continue reading ARM is great, ARM is terrible (and so is RISC-V) →
In my first interview out of college I was asked the change counter problem: Given a set of coin denominations, find the minimum number of coins required to make change for a given number. IE for USA coinage and 37 cents, the minimum number is four (quarter, dime, 2 pennies). I implemented the simple greedy algorithm and immediately fell into the trap of the question: the greedy algorithm only works for "well-behaved" denominations. If the coin values were [10, 9, 1], then making 37 cents would take 10 coins in the greedy algorithm but only 4 coins optimally (10+9+9+9). The "smart" answer is to use a dynamic programming algorithm, which I didn't know how to do. So I failed the interview. But you only need dynamic programming if you're writing your own algorithm. It's really easy if you throw it into a constraint solver like MiniZinc and call it a day. int: total; array[int] of int: values = [10, 9, 1]; array[index_set(values)] of var 0..: coins; constraint sum (c in index_set(coins)) (coins[c] * values[c]) == total; solve minimize sum(coins); You can try this online here. It'll give you a prompt to put in total and then give you successively-better solutions: coins = [0, 0, 37]; ---------- coins = [0, 1, 28]; ---------- coins = [0, 2, 19]; ---------- coins = [0, 3, 10]; ---------- coins = [0, 4, 1]; ---------- coins = [1, 3, 0]; ---------- Lots of similar interview questions are this kind of mathematical optimization problem, where we have to find the maximum or minimum of a function corresponding to constraints. They're hard in programming languages because programming languages are too low-level. They are also exactly the problems that constraint solvers were designed to solve. Hard leetcode problems are easy constraint problems.1 Here I'm using MiniZinc, but you could just as easily use Z3 or OR-Tools or whatever your favorite generalized solver is. More examples This was a question in a different interview (which I thankfully passed): Given a list of stock prices through the day, find maximum profit you can get by buying one stock and selling one stock later. It's easy to do in O(n^2) time, or if you are clever, you can do it in O(n). Or you could be not clever at all and just write it as a constraint problem: array[int] of int: prices = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5, 8]; var int: buy; var int: sell; var int: profit = prices[sell] - prices[buy]; constraint sell > buy; constraint profit > 0; solve maximize profit; Reminder, link to trying it online here. While working at that job, one interview question we tested out was: Given a list, determine if three numbers in that list can be added or subtracted to give 0? This is a satisfaction problem, not a constraint problem: we don't need the "best answer", any answer will do. We eventually decided against it for being too tricky for the engineers we were targeting. But it's not tricky in a solver; include "globals.mzn"; array[int] of int: numbers = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5, 8]; array[index_set(numbers)] of var {0, -1, 1}: choices; constraint sum(n in index_set(numbers)) (numbers[n] * choices[n]) = 0; constraint count(choices, -1) + count(choices, 1) = 3; solve satisfy; Okay, one last one, a problem I saw last year at Chipy AlgoSIG. Basically they pick some leetcode problems and we all do them. I failed to solve this one: Given an array of integers heights representing the histogram's bar height where the width of each bar is 1, return the area of the largest rectangle in the histogram. The "proper" solution is a tricky thing involving tracking lots of bookkeeping states, which you can completely bypass by expressing it as constraints: array[int] of int: numbers = [2,1,5,6,2,3]; var 1..length(numbers): x; var 1..length(numbers): dx; var 1..: y; constraint x + dx <= length(numbers); constraint forall (i in x..(x+dx)) (y <= numbers[i]); var int: area = (dx+1)*y; solve maximize area; output ["(\(x)->\(x+dx))*\(y) = \(area)"] There's even a way to automatically visualize the solution (using vis_geost_2d), but I didn't feel like figuring it out in time for the newsletter. Is this better? Now if I actually brought these questions to an interview the interviewee could ruin my day by asking "what's the runtime complexity?" Constraint solvers runtimes are unpredictable and almost always than an ideal bespoke algorithm because they are more expressive, in what I refer to as the capability/tractability tradeoff. But even so, they'll do way better than a bad bespoke algorithm, and I'm not experienced enough in handwriting algorithms to consistently beat a solver. The real advantage of solvers, though, is how well they handle new constraints. Take the stock picking problem above. I can write an O(n²) algorithm in a few minutes and the O(n) algorithm if you give me some time to think. Now change the problem to Maximize the profit by buying and selling up to max_sales stocks, but you can only buy or sell one stock at a given time and you can only hold up to max_hold stocks at a time? That's a way harder problem to write even an inefficient algorithm for! While the constraint problem is only a tiny bit more complicated: include "globals.mzn"; int: max_sales = 3; int: max_hold = 2; array[int] of int: prices = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5, 8]; array [1..max_sales] of var int: buy; array [1..max_sales] of var int: sell; array [index_set(prices)] of var 0..max_hold: stocks_held; var int: profit = sum(s in 1..max_sales) (prices[sell[s]] - prices[buy[s]]); constraint forall (s in 1..max_sales) (sell[s] > buy[s]); constraint profit > 0; constraint forall(i in index_set(prices)) (stocks_held[i] = (count(s in 1..max_sales) (buy[s] <= i) - count(s in 1..max_sales) (sell[s] <= i))); constraint alldifferent(buy ++ sell); solve maximize profit; output ["buy at \(buy)\n", "sell at \(sell)\n", "for \(profit)"]; Most constraint solving examples online are puzzles, like Sudoku or "SEND + MORE = MONEY". Solving leetcode problems would be a more interesting demonstration. And you get more interesting opportunities to teach optimizations, like symmetry breaking. Because my dad will email me if I don't explain this: "leetcode" is slang for "tricky algorithmic interview questions that have little-to-no relevance in the actual job you're interviewing for." It's from leetcode.com. ↩
