Thou shalt not suffer a flaky test to live, because it’s annoying, counterproductive, and dangerous: one day it might fail for real, and you won’t notice. Here’s what to do.

While I frequently hear engineers bemoan a missing strategy, they rarely complete the thought by articulating why the missing strategy matters. Instead, it serves as more of a truism: the economy used to be better, children used to respect their parents, and engineering organizations used to have an engineering strategy. This chapter starts by exploring something I believe quite strongly: there’s always an engineering strategy, even if there’s nothing written down. From there, we’ll discuss why strategy, especially written strategy, is such a valuable opportunity for organizations that take it seriously. We’ll dig into: Why there’s always a strategy, even when people say there isn’t How strategies have been impactful across my career How inappropriate strategies create significant organizational pain without much compensating impact How written strategy drives organizational learning The costs of not writing strategy down How strategy supports personal learning and developing, even in cases where you’re not empowered to “do strategy” yourself By this chapter’s end, hopefully you will agree with me that strategy is an undertaking worth investing your–and your organization’s–time in. 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 As such, some of the links go to other draft chapters, both published drafts and very early, unpublished drafts. There’s always a strategy I’ve never worked somewhere where people didn’t claim there as no strategy. In many of those companies, they’d say there was no engineering strategy. Once I became an executive and was able to document and distribute an engineering strategy, accusations of missing strategy didn’t go away, they just shfited to focus on a missing product or company strategy. This even happened at companies that definitively had engineering strategies like Stripe in 2016 which had numerous pillars to a clear engineering strategy such as: Maintain backwards API compatibilty, at almost any cost (e.g. force an upgrade from TLS 1.2 to TLS 1.3 to retain PCI compliance, but don’t force upgrades from the /v1/charges endpoint to the /v1/payment_intents endpoint) Work in Ruby in a monorepo, unless it’s the PCI environment, data processing, or data science work Engineers are fully responsible for the usability of their work, even when there are product or engineering managers involved Working there it was generally clear what the company’s engineering strategy was on any given topic. That said, it sometimes required asking around, and over time certain decisions became sufficiently contentious that it became hard to definitively answer what the strategy was. For example, the adoptino of Ruby versus Java became contentious enough that I distributed a strategy attempting to mediate the disagreement, Magnitudes of exploration, although it wasn’t a particularly successful effort (for reasons that are obvious in hindsight, particularly the lack of any enforcement mechanism). In the same sense that William Gibson said “The future is already here – it’s just not very evenly distributed,” there is always a strategy embedded into an organization’s decisions, although in many organizations that strategy is only visible to a small group, and may be quickly forgotten. If you ever find yourself thinking that a strategy doesn’t exist, I’d encourage you to instead ask yourself where the strategy lives if you can’t find it. Once you do find it, you may also find that the strategy is quite ineffective, but I’ve simply never found that it doesn’t exist. Strategy is impactful In “We are a product engineering company!”, we discuss Calm’s engineering strategy to address pervasive friction within the engineering team. The core of that strategy is clarifying how Calm makes major technology decisions, along with documenting the motivating goal steering those decisions: maximizing time and energy spent on creating their product. That strategy reduced friction by eliminating the cause of ongoing debate. It was successful in resetting the team’s focus. It also caused several engineers to leave the company, because it was incompatible with their priorities. It’s easy to view that as a downside, but I don’t think it was. A clear, documented strategy made it clear to everyone involved what sort of game we were playing, the rules for that game, and for the first time let them accurately decide if they wanted to be part of that game with the wider team. Creating alignment is one of the ways that strategy makes an impact, but it’s certainly not the only way. Some of the ways that strategies support the creating organization are: Concentrating company investment into a smaller space. For example, deciding not to decompose a monolith allows you to invest the majority of your tooling efforts on one language, one test suite, and one deployment mechanism. Many interesting properties only available through universal adoption. For example, moving to an “N-1 policy” on backfilled roles is a significant opportunity for managing costs, but only works if consistently adopted. As another example, many strategies for disaster recovery or multi-region are only viable if all infrastructure has a common configuration mechanism. Focus execution on what truly matters. For example, Uber’s service migration strategy allowed a four engineer team to migrate a thousand services operated by two thousand engineers to a new provisioning and orchestration platform in less than a year. This was an extraordinarily difficult project, and was only possible because of clear thinking. Creating a knowledge repository of how your organization thinks. Onboarding new hires, particularly senior new hires, is much more effective with documented strategy. For example, most industry professionals today have a strongly held opinion on how to adopt large language models. New hires will have a strong opinion as well, but they’re unlikely to share your organization’s opinion unless there’s a clear document they can read to understand it. There are some things that a strategy, even a cleverly written one, cannot do. However, it’s always been my experience that developing a strategy creates progress, even if the progress is understanding the inherent disagreement preventing agreement. Inappropriate strategy is especially impactful While good strategy can accomplish many things, it sometimes feels that inappropriate strategy is far more impactful. Of course, impactful in all the wrong ways. Digg V4 remains the worst considered strategy I’ve personally participated in. It was a complete rewrite of the Digg V3.5 codebase from a PHP monolith to a PHP frontend and backend of a dozen Python services. It also moved the database from sharded MySQL to an early version of Cassandra. Perhaps worst, it replaced the nuanced algorithms developed over a decade with a hack implemented a few days before launch. Although it’s likely Digg would have struggled to become profitable due to its reliance on search engine optimization for traffic, and Google’s frequently changing search algorithm of that era, the engineering strategy ensured we died fast rather than having an opportunity to dig our way out. Importantly, it’s not just Digg. Almost every engineering organization you drill into will have it’s share of unused platform projects that captured decades of engineering years to the detriment of an important opportunity. A shocking number of senior leaders join new companies and initiate a grand migration that attempts to entirely rewrite the architecture, switch programming languages, or otherwise shift their new organization to resemble a prior organization where they understood things better. Inappropriate versus bad When I first wrote this section, I just labeled this sort of strategy as “bad.” The challenge with that term is that the same strategy might well be very effective in a different set of circumstances. For example, if Digg had been a three person company with no revenue, rewriting from scratch could have the right decision! As a result, I’ve tried to prefer the term “inappropriate” rather than “bad” to avoid getting caught up on whether a given approach might work in other circumstances. Every approach undoubtedly works in some organization. Written strategy drives organizational learning When I joined Carta, I noticed we had an inconsistent approach to a number of important problems. Teams had distinct standard kits for how they approached new projects. Adoption of existing internal platforms was inconsistent, as was decision making around funding new internal platforms. There was widespread agreement that we were decomposing our monolith, but no agreement on how we were doing it. Coming into such a permissive strategy environment, with strong, differing perspectives on the ideal path forward, one of my first projects was writing down an explicit engineering strategy along with our newly formed Navigators team, itself a part of our new engineering strategy. Navigators at Carta As discussed in Navigators, we developed a program at Carta to have explicitly named individual contributor, technical leaders to represent key parts of the engineering organization. This representative leadership group made it possible to iterate on strategy with a small team of about ten engineers that represented the entire organization, rather than take on the impossible task of negotiating with 400 engineers directly. This written strategy made it possible to explicitly describe the problems we saw, and how we wanted to navigate those problems. Further, it was an artifact that we were able to iterate on in a small group, but then share widely for feedback from teams we might have missed. After initial publishing, we shared it widely and talked about it frequently in engineering all-hands meetings. Then we came back to it each year, or when things stopped making much sense, and revised it. As an example, our initial strategy didn’t talk about artificial intelligence at all. A few months later, we extended it to mention a very conservative approach to using Large Language Models. Most recently, we’ve revised the artificial intelligence portion again, as we dive deeply into agentic workflows. A lot of people have disagreed with parts of the strategy, which is great: that’s one of the key benefits of a written strategy, it’s possible to precisely disagree. From that disagreement, we’ve been able to evolve our strategy. Sometimes because there’s new information like the current rapidly evolution of artificial intelligence pratices, and other times because our initial approach could be improved like in how we gated membership of the initial Navigators team. New hires are able to disagree too, and do it from an informed place rather than coming across as attached to their prior company’s practices. In particular, they’re able to understand the historical thinking that motivated our decisions, even when that context is no longer obvious. At the time we paused decomposition of our monolith, there was significant friction in service provisioning, but that’s far less true today, which makes the decision seem a bit arbitrary. Only the written document can consistently communicate that context across a growing, shifting, and changing organization. With oral history, what you believe is highly dependent on who you talk with, which shapes your view of history and the present. With writen history, it’s far more possible to agree at scale, which is the prerequisite to growing at scale rather than isolating growth to small pockets of senior leadership. The cost of implicit strategy We just finished talking about written strategy, and this book spends a lot of time on this topic, including a chapter on how to structure strategies to maximize readability. It’s not just because of the positives created by written strategy, but also because of the damage unwritten strategy creates. Vulnerable to misinterpretation. Information flow in verbal organizations depends on an individual being in a given room for a decision, and then accurately repeating that information to the others who need it. However, it’s common to see those individuals fail to repeat that information elsewhere. Sometimes their interpretation is also faulty to some degree. Both of these create significant problems in operating strategy. Two-headed organizations Some years ago, I started moving towards a model where most engineering organizations I worked with have two leaders: one who’s a manager, and another who is a senior engineer. This was partially to ensure engineering context was included in senior decision making, but it was also to reduce communication errors. Errors in point-to-point communication are so prevalent when done one-to-one, that the only solution I could find for folks who weren’t reading-oriented communicators was ensuring I had communicated strategy (and other updates) to at least two people. Inconsistency across teams. At one company I worked in, promotions to Staff-plus role happened at a much higher rate in the infrastructure engineering organization than the product engineering team. This created a constant drain out of product engineering to work on infrastructure shaped problems, even if those problems weren’t particularly valuable to the business. New leaders had no idea this informal policy existed, and they would routinely run into trouble in calibration discussions. They also weren’t aware they needed to go argue for a better policy. Worse, no one was sure if this was a real policy or not, so it was ultimately random whether this perspective was represented for any given promotion: sometimes good promotions would be blocked, sometimes borderline cases would be approved. Inconsistency over time. Implementing a new policy tends to be a mix of persistent and one-time actions. For example, let’s say you wanted to standardize all HTTP operations to use the same library across your codebase. You might add a linter check to reject known alternatives, and you’ll probably do a one-time pass across your codebase standardizing on that library. However, two years later there are another three random HTTP libraries in your codebase, creeping into the cracks surrounding your linting. If the policy is written down, and a few people read it, then there’s a number of ways this could be nonetheless prevented. If it’s not written down, it’s much less likely someone will remember, and much more likely they won’t remember the rationale well enough to argue about it. Hazard to new leadership. When a new Staff-plus engineer or executive joins a company, it’s common to blame them for failing to understand the existing context behind decisions. That’s fair: a big part of senior leadership is uncovering and understanding context. It’s also unfair: explicit documentation of prior thinking would have made this much easier for them. Every particularly bad new-leader onboarding that I’ve seen has involved a new leader coming into an unfilled role, that the new leader’s manager didn’t know how to do. In those cases, success is entirely dependent on that new leader’s ability and interest in learning. In most ways, the practice of documenting strategy has a lot in common with succession planning, where the full benefits accrue to the organization rather than to the individual doing it. It’s possible to maintain things when the original authors are present, appreciating the value requires stepping outside yourself for a moment to value things that will matter most to the organization when you’re no longer a member. Information herd immunity A frequent objection to written strategy is that no one reads anything. There’s some truth to this: it’s extremely hard to get everyone in an organization to know something. However, I’ve never found that goal to be particularly important. My view of information dispersal in an organization is the same as Herd immunity: you don’t need everyone to know something, just to have enough people who know something that confusion doesn’t propagate too far. So, it may be impossible for all engineers to know strategy details, but you certainly can have every Staff-plus engineer and engineering manager know those details. Strategy supports personal learning While I believe that the largest benefits of strategy accrue to the organization, rather than the individual creating it, I also believe that strategy is an underrated avenue for self-development. The ways that I’ve seen strategy support personal development are: Creating strategy builds self-awareness. Starting with a concrete example, I’ve worked with several engineers who viewed themselves as extremely senior, but frequently demanded that projects were implemented using new programming languages or technologies because they personally wanted to learn about the technology. Their internal strategy was clear–they wanted to work on something fun–but following the steps to build an engineering strategy would have created a strategy that even they agreed didn’t make sense. Strategy supports situational awareness in new environments. Wardley mapping talks a lot about situational awareness as a prerequisite to good strategy. This is ensuring you understand the realities of your circumstances, which is the most destructive failure of new senior engineering leaders. By explicitly stating the diagnosis where the strategy applied, it makes it easier for you to debug why reusing a prior strategy in a new team or company might not work. Strategy as your personal archive. Just as documented strategy is institutional memory, it also serves as personal memory to understand the impact of your prior approaches. Each of us is an archivist of our prior work, pulling out the most valuable pieces to address the problem at hand. Over a long career, memory fades–and motivated reasoning creeps in–but explicit documentation doesn’t. Indeed, part of the reason I started working on this book now rather than later is that I realized I was starting to forget the details of the strategy work I did earlier in my career. If I wanted to preserve the wisdom of that era, and ensure I didn’t have to relearn the same lessons in the future, I had to write it now. Summary We’ve covered why strategy can be a valuable learning mechanism for both your engineering organization and for you. We’ve shown how strategies have helped organizations deal with service migrations, monolith decomposition, and right-sizing backfilling. We’ve also discussed how inappropriate strategy contributed to Digg’s demise. However, if I had to pick two things to emphasize as this chapter ends, it wouldn’t be any of those things. Rather, it would be two themes that I find are the most frequently ignored: There’s always a strategy, even if it isn’t written down. The single biggest act you can take to further strategy in your organization is to write down strategy so it can be debated, agreed upon, and explicitly evolved. Discussions around topics like strategy often get caught up in high prestige activities like making controversial decisions, but the most effective strategists I’ve seen make more progress by actually performing the basics: writing things down, exploring widely to see how other companies solve the same problem, accepting feedback into their draft from folks who disagree with them. Strategy is useful, and doing strategy can be simple, too.

The ware for January 2025 is shown below. Thanks to brimdavis for contributing this ware! …back in the day when you would get wares that had “blue wires” in them… One thing I wonder about this ware is…where are the ROMs? Perhaps I’ll find out soon! Happy year of the snake!

I occasionally receive emails asking me to look at the writer's new language/library/tool. Sometimes it's in an area I know well, like formal methods. Other times, I'm a complete stranger to the field. Regardless, I'm generally happy to check it out. When starting out, this is the biggest question I'm looking to answer: What does this technology make easy that's normally hard? What justifies me learning and migrating to a new thing as opposed to fighting through my problems with the tools I already know? The new thing has to have some sort of value proposition, which could be something like "better performance" or "more secure". The most universal value and the most direct to show is "takes less time and mental effort to do something". I can't accurately judge two benchmarks, but I can see two demos or code samples and compare which one feels easier to me. Examples Functional programming What drew me originally to functional programming was higher order functions. # Without HOFs out = [] for x in input { if test(x) { out.append(x) } } # With HOFs filter(test, input) We can also compare the easiness of various tasks between examples within the same paradigm. If I know FP via Clojure, what could be appealing about Haskell or F#? For one, null safety is a lot easier when I've got option types. Array Programming Array programming languages like APL or J make certain classes of computation easier. For example, finding all of the indices where two arrays differ. Here it is in Python: x = [1, 4, 2, 3, 4, 1, 0, 0, 0, 4] y = [2, 3, 1, 1, 2, 3, 2, 0, 2, 4] >>> [i for i, (a, b) in enumerate(zip(x, y)) if a == b] [7, 9] And here it is in J: x =: 1 4 2 3 4 1 0 0 0 4 y =: 2 3 1 1 2 3 2 0 2 4 I. x = y 7 9 Not every tool is meant for every programmer, because you might not have any of the problems a tool makes easier. What comes up more often for you: filtering a list or finding all the indices where two lists differ? Statistically speaking, functional programming is more useful to you than array programming. But I have this problem enough to justify learning array programming. LLMs I think a lot of the appeal of LLMs is they make a lot of specialist tasks easy for nonspecialists. One thing I recently did was convert some rst list tables to csv tables. Normally I'd have to do write some tricky parsing and serialization code to automatically convert between the two. With LLMs, it's just Convert the following rst list-table into a csv-table: [table] "Easy" can trump "correct" as a value. The LLM might get some translations wrong, but it's so convenient I'd rather manually review all the translations for errors than write specialized script that is correct 100% of the time. Let's not take this too far A college friend once claimed that he cracked the secret of human behavior: humans do whatever makes them happiest. "What about the martyr who dies for their beliefs?" "Well, in their last second of life they get REALLY happy." We can do the same here, fitting every value proposition into the frame of "easy". CUDA makes it easier to do matrix multiplication. Rust makes it easier to write low-level code without memory bugs. TLA+ makes it easier to find errors in your design. Monads make it easier to sequence computations in a lazy environment. Making everything about "easy" obscures other reason for adopting new things. That whole "simple vs easy" thing Sometimes people think that "simple" is better than "easy", because "simple" is objective and "easy" is subjective. This comes from the famous talk Simple Made Easy. I'm not sure I agree that simple is better or more objective: the speaker claims that polymorphism and typeclasses are "simpler" than conditionals, and I doubt everybody would agree with that. The problem is that "simple" is used to mean both "not complicated" and "not complex". And everybody agrees that "complicated" and "complex" are different, even if they can't agree what the difference is. This idea should probably expanded be expanded into its own newsletter. It's also a lot harder to pitch a technology on being "simpler". Simplicity by itself doesn't make a tool better equipped to solve problems. Simplicity can unlock other benefits, like compositionality or tractability, that provide the actual value. And often that value is in the form of "makes some tasks easier".

Ask an engineering leader about their incident response protocol and they’ll tell you about their severity scale. “The first thing we do is we assign a severity to the incident,” they’ll say, “so the right people will get notified.” And this is sensible. In order to figure out whom to get involved, decision makers need … Continue reading Incident SEV scales are a waste of time