U.S. government takes 10% stake in Intel (cnbc.com)
605 points by givemeethekeys 7d ago 718 comments
Claude Sonnet will ship in Xcode (developer.apple.com)
471 points by zora_goron 22h ago 384 comments
Do the simplest thing that could possibly work
235 dondraper36 115 8/29/2025, 7:05:09 PM seangoedecke.com ↗
Anyone proclaiming simplicity just hasnt worked at scale. Even rewrites that have a decade old code base to be inspired from, often fail due to the sheer amount of things to consider.
A classic, Chesterton's Fence:
"There exists in such a case a certain institution or law; let us say, for the sake of simplicity, a fence or gate erected across a road. The more modern type of reformer goes gaily up to it and says, “I don’t see the use of this; let us clear it away.” To which the more intelligent type of reformer will do well to answer: “If you don’t see the use of it, I certainly won’t let you clear it away. Go away and think. Then, when you can come back and tell me that you do see the use of it, I may allow you to destroy it.”"
We can even just look at the title here: Do the simplest thing POSSIBLE.
You can't escape complexity when a problem is complex. You could certainly still complicate it even more than necessary, though. Nowhere in this article is it saying you can avoid complexity altogether, but that many of use complicate problems for no good reason.
If the software base is full of gotchas and unintended side-effects then the source of the problem is in unclean separation of concerns and tight coupling. Of course, at some point refactoring just becomes an almost insurmountable task, and if the culture of the company does not change more crap will be added before even one of your refactorings land.
Believe me, it's possible to solve complex problems by clean separation of concerns and composability of simple components. It's very hard to do well, though, so lots of programmers don't even try. That's where you need strict ownership of seniors (who must also subscribe to this point of view).
Sometimes the problem is in the edges—the way the separate concerns interact—not in the nodes. This may arise, for example, where the need for an operation/interaction between components doesn't need to be idempotent because the need for it to be never came up.
Again, wrong design. Like I said, it's very difficult to do well. Consider alternate architecture: one component adds the bulk data to request, the second component modifies it and adds other data, then the data is sent to transaction manager that commits or fails the operation, notifying both components of the result.
Now, if the first component is one k8s container already writing to the database and second is then trying to modify the database, rearchitecting that could be a major pain. So, I understand that it's difficult to do after the fact. Yet, if it's not done that way, the problem will just become bigger and bigger. In the long run, it would make more sense to rearchitect as soon as you see such a situation.
The guy is full of shit.
Look at his other blog spam
The formula for prioritizing is literally this simple: Am I working on the most important thing right now? If not, drop what I’m doing and go do that
Utter trash.
Look at his CV. Tiny (but impactful) features ///building on existing infrastructure which has already provably scaled to millions and likely has never seen beneath what is a rest api and a react front end///
I know this type. I AM him. Exaggerating my way through roles saying the right things through self promotion at the right times.
> I’ve also written Python and C in production
Absolute miss truth. A single line edit to existing applications/a pet project CGI server.
This is EXACTLY what I do.
Appreciate the hustle, but don’t assume “because github + writes blog = knows things”
> Look at his CV. Tiny (but impactful) features ///building on existing infrastructure which has already provably scaled to millions and likely has never seen beneath what is a rest api and a react front end///
Off the top of my head he wrote the socket monitoring infrastructure for Zendesk’s unicorn workers, for example.
I certainly don’t agree with everything Sean says and admit that “picking the most important work” is a naive thing to say in most scenarios.
But writing Python in production is trivial. Why would anyone lie about that? C is different OTOH. But just because you do a single config change and get paid for that doesn’t mean it’s true for everyone.
Also, staff at GitHub requires a certain bar of excellence. So I wouldn’t blindly dismiss everything just out of spite.
The complexity comes from the fact that at scale, the state space of any problem domain is thoroughly (maybe totally) explored very rapidly.
That’s a way bigger problem than system complexity and pretty much any system complexity is usually the result of edge cases that need to be solved, rather than bad architecture, infrastructure or organisational issues - these problems are only significant at smaller, inexperienced companies, by the time you are at post scale (if the company survives that long) then state space exploration in implementation (features, security, non-stop operations) is where the complexity is.
At the scale you are mentioning, even "simple" solutions must be very sophisticated and nuanced. How does this transformation happen naturally from an engineer at a startup where any mainstream language + Postgres covers all your needs, to someone who can build something at Google scale?
Let's disregard the grokking of system design interview books and assume that system design interviews do look at real skills instead of learning common buzzwords.
I built a hobby system for anonymously monitoring BitTorrent by scraping the DHT, in doing this, I learned how to build a little cluster, how to handle 30,000 writes a second (which I used Cassandra for - this was new to me at the time) then build simple analytics on it to measure demand for different media.
Then my interview was just talking about this system, how the data flowed, where it can be improved, how is redundancy handled, the system consisted of about 10 different microservices so I pulled the code up for each one and I showed them.
Interested in astronomy? Build a system to track every star/comet. Interested in weather? Do SOTA predictions, interested in geography? Process the open source global gravity maps, interested in trading? Build a data aggregator for a niche.
It doesn’t really matter that whatever you build “is the best in the world or not” - the fact that you build something, practiced scaling it with whatever limited resources you have, were disciplined to take it to completion, and didn’t get stuck down some rabbit hole endlessly re-architecting stuff that doesn’t matter, this is what they’re looking for - good judgement, discipline, experience.
Also attitude is important, like really, really important - some cynical ranter is not going to get hired over the “that’s cool I can do that!” person, even if the cynical ranter has greater engineering skills, genuine enthusiasm and genuine curiosity is infectious.
Most projects don't operate at scale. And before "at scale", simple, rewritable code will always evolve better, because it's less dense, and less spread out.
There is indeed a balance between the simplest code, and the gradual abstractions needed to maintain code.
I worked with startups, small and medium sized businesses, and with a larger US airline. Engineering complexity is through the roof, when it doesn't have to be. Not on any of the projects I've seen and worked on.
Now if you're an engineer in some mega corp, things could be very different, but you're talking about the 1% there. If not less.
I think the unspoken part here is “let’s start with…”
It doesn’t mean you won’t have to “do all the things” so much as let’s start with too little so we don’t waste time doing things we end up not needing.
Once you aggregate all the simple things you may end up with a complex behemoth but hopefully you didn’t spend too much time on fruitless paths getting there.
This isn't to say you should never try to refactor or improve things, but make sure that it's going to work for 100% of your use cases, that you're budgeted to finish what you start, and that it can be done iteratively with the result of each step being an improvement on the previous.
See also: Google engineering practices: https://google.github.io/eng-practices/review/reviewer/looki...
And also: https://goomics.net/316
Like yes, everyone knows that if you want to index the whole internet and have tens of thousands of searches a second there are unique challenges and you need some crazy complexity. But if you have a system that has 10 transactions a second...you probably don't. The simple thing will probably work just fine. And the vast majority of systems will never get that busy.
Computers are fast now! One powerful server (with a second powerful server, just in case) can do a lot.
A rewrite of a decade old code base is not the simplest thing that could possibly work.
Simple stuff had tons of long term advantages and benefits - its easy to ramp up new folks on it compared to some over-abstracted hypercomplex system because some lead dev wanted to try new shiny stuff for their cvs or out of boredom. Its easy to debug, migrate, evolve and just generally maintain, something pure devs often don't care much for unless they become more senior.
Complex optimizations are for sure required for extreme performance or massive public web but that's not the bulk of global IT work done out there.
What is far more likely is the proverbial "JS framework problem:" gah, this technology that I read about (or encounter) is too complex, I just want 1/10th that I understand from casually reading about it, so we should replace it with this simple thing. Oh, right, plus this one other thing that solves a problem. Oh, plus this other thing that solves this other problem. Gah, this thing is too complex!
It’s not the same as introducing complexity to keep yourself employed, but the result is the same and so is the cause - incentive structures aren’t aligned at most companies to solve problems simply and move on.
They were cognizant of the limitations that are touched on in this article. The example they gave was of coming to a closed door. The simplest thing might be to turn the handle. But if the door is locked, then the simplest thing might be to find the key. But if you know the key is lost, the simplest thing might be to break down the door, and so on. Finding the simplest thing is not always simple, as the article states
IIRC, they were aware that this approach would leave a patchwork of technical debt (a term coined by Cunningham), but the priority on getting code working overrode that concern at least in the short term. This article would have done well to at least touch on the technical debt aspect, IMHO.
It's interesting you gave that example. Before my first use of a wiki I was on a team that used Lotus Notes and did project organization in a team folder. I loved that Notes would highlight which documents had been updated since the last time I read them.
In the next project, that team used a wiki. It's simpler. But, the fact it didn't tell me which documents had been updated effectively made it useless. People typed new project designs into the wiki but no one saw them since they couldn't, at a glance, know which of the hundreds of pages had been updated since they last read them.
It was too simple
“Just because it works doesn’t mean it isn’t broken.” Is an aphorism that seems to click for people who are also handy in the physical world but many software developers think doesn’t sound right. Every handyman has at some time used a busted tool to make a repair. They know they should get a new one, and many will make an excuse to do so at the next opportunity (hardware store trip, or sale). Maybe 8 out of ten.
In software it’s probably more like 1 out of ten who will do the equivalent effort.
Then the executives would be stunned that it was done so quickly. The prototype team would pass it off to another team and then move on to the next prototype.
The team that took over would open the project and discover that it was really a proof of concept, not a working site. They wouldn't include basic things like security, validation, error messages, or any of the hundred things that a real working product requires before you can put it online.
So the team that now owned it would often have to restart entirely, building it within the structures used by the rest of our products. The executives would be angry because they saw it "work" with their own eyes and thought the deployment team was just complicating things.
Those are the worst because you don’t have done criteria you can reasonably write down. It’s whenever QA stops finding fakes in the code, plus a couple months for stragglers you might have missed.
> It's not enough for a program to work – it has to work for the right reasons
I guess that’s basically the same statement, from a different angle.
Until recently I would say such programs are extremely rare, but now AI makes this pretty easy. Want to do some complicated project-wide edit? I sometimes get AI to write me a one-off script to do it. I don't even need to read the script, just check the output and throw it away.
But I'm nitpicking, I do agree with it 99% of the time.
By the time you’ve done something five times, it’s probably part of your actual process, and you should start treating it as normal instead of exceptional. Even if admitting so feels like a failure.
So I staple something together that works for the exact situation, then start removing the footguns I’m likely to hit, then I start shopping it to other people I see eye to eye with, fix the footguns they run into. Then we start trying to make it into an actual project, and end game is for it to be a mandatory part of our process once the late adopters start to get onboard.
On a recent project I fixed our deployment and our hotfix process and it fundamentally changed the scope of epics the team would tackle. Up to that point we were violating the first principle of Continuous: if it’s painful, do it until it isn’t. So we would barely deploy more often than we were contractually (both in the legal and internal cultural sense) obligated to do, and that meant people were very conservative about refactoring code that could lead to regressions, because the turnaround time on a failing feature toggle was a fixed tempo. You could turn a toggle on to analyze the impact but then you had to wait until the next deployment to test your fixes. Excruciating with a high deviation for estimates.
With a hotfix process that actually worked worked, people would make two or three times as many iterations, to the point we had to start coordinating to keep people from tripping over each other. And as a consequence old nasty tech debt was being fixed in every epic instead of once a year. It was a profound change.
And as is often the case, as the author I saw more benefit than most. I scooped a two year two man effort to improve response time by myself in three months, making a raft of small changes instead of a giant architectural shift. About twenty percent of the things I tried got backed out because they didn’t improve speed and didn’t make the code cleaner either. I could do that because the tooling wasn’t broken.
If they want to use those resources to prioritize quality, I'll prioritize quality. If they don't, and they just want me to hit some metric and tick a box, I'm happy to do that too.
You get what you measure. I'm happy to give my opinion on what they should measure, but I am not the one making that call.
My second lead role, the CTO and the engineering manager thought I could walk on water and so I had considerable leeway to change things I thought needed changing.
So one of the first things I did was collectively save the team about 40 hours of code-build-test time per week. Which is really underselling it because what I actually did was both build a CI pipeline at a time nobody knew what “CI” meant, and increase the number of cycles you could reliably get through without staying late from 4 to 5 cycles per day. A >20% improvement in iterations per day and a net reduction in errors. That was the job where I learned the dangers of pushing code after 3:30pm. Everyone rationalizes that the error they saw was a glitch or someone else’s bug, and they push and then come in to find the early birds are mad at them. So better to finish what we now call deep work early and do lighter stuff once you’re tired.
Edit: those changes also facilitated us scaling the team to over twice the size of any project I’d worked on before or for some time after, though the EM deserves equal credit for that feat.
Then they fired the EM and Peter Principled by far the worst manager I’ve ever worked for (fuck you Mike, everyone hated your guts), and all he wanted to know was why I was getting fewer features implemented. Because I’m making everyone else faster. Speaking of broken, the biggest performance bottleneck in the entire app was his fault. He didn’t follow the advice I gave him back when he was working in our query system. Discovering it took hiring an Oracle DB contractor (those are always exorbitant). Fixing it after it shipped was a giant pain (as to why I didn’t catch his corner cutting, I was tagged in by another lead who was triple booked, and when I tagged back out he unfortunately didn’t follow up sufficiently on the things I prescribed).
I see people adding unnecessary complexity to things all the time and advocate for keeping things simple on a daily basis probably. Otherwise designers and product managers and customers and architects will let their mind naturally add complexity to solutions which is unnecessary.
Unfortunately, simplicity is complicated. The median engineer in industry is not a reliable judge of which of two designs is less complex.
Further, "simplicity" as an argument has become something people can parrot. So now it's a knee-jerk fallback when a coworker challenges them about the approach they are taking. They quickly say "This is simpler" in response to a much longer, more sincere, and more correct argument. Ideally the team leader would help suss out what's going on, but increasingly the team lead is a less than competent manager, and simplicity is too complicated a topic for them to give a reliable signal. They prefer not to ruffle feathers and let whoever is doing the work make the call; the team bears the complexity.
What you really learn over time and it’s more useful, is to think along these lines: don’t try to solve problems that don’t exist yet.
This is a mantraic, cool headline but useless. The article doesn't develop it properly either in my opinion.
Now the problem with the headline and repeating it is, when "just do a simple thing" becomes mandated from management (technical or not), there comes a certain stress about trying to keep it simple and if you try running with it for a complex problems you easily end up with those hacks that become innate knowledge that's hard to transfer instead of a good design (that seemed complex upfront).
Conversly, I think a lot of "needless complexity" comes from badly planned projects where people being bitten by having to continuously add hacks to handle wild requirements easily end up overdesigning something to catch them, only to end up with no more complexity in that area and then playing catchup with the next area needing ugly hacks (to then try to design that area that stabilized and the cycle repeats).
This is why as developers we do need to inject ourselves into meetings (however boring they are) where things that do land up on our desks are decided.
"real mastery often involves learning when to do less, not more. The fight between an ambitious novice and an old master is a well-worn cliche in martial arts movies: the novice is a blur of motion, flipping and spinning. The master is mostly still. But somehow the novice’s attacks never seem to quite connect, and the master’s eventual attack is decisive".
But also keep in mind the audience: the kinds of people who are tempted to use J2EE (at the time) with event sourcing and Semantic Web, etc.
This is really a counterbalance to that: let's not add sophistication and complexity by default. We really are better off when we bias towards the simpler solutions vs one that's overly complex. It's like what Dan McKinley was talking about with "Choose Boring Technology". And of course that's true (by and large), but many in our industry act like the opposite is the case - that you get rewarded for flexing how novel you can make something.
I've spent much of my career unwinding the bad ideas of overly clever devs. Sometimes that clever dev was me!
So yes ... it's an overly general statement that shouldn't need to be said, and yet it's still useful given the tendency of many to over-engineer and use unnecessarily sophisticated approaches when simpler ones would suffice.
Some generalizations are necessary to formalize the experience we have accumulated in the industry and teach newcomers.
The obvious problem is that, for some strange reason, lots of concepts and patterns that may be useful when applied carefully become a cult (think clean architecture and clean code), which eventually only makes the industry worse.
For example, clean architecture/ports and adapters/hexagonal/whatever, as I see it, is a very sane and pragmatic idea in general. But somehow, all battles are around how to name folders.
Yesterday I had a problem with my XLSX importer (which I wrote myself--don't ask why). It turned out that I had neglected to handle XML namespaces properly because Excel always exported files with a default namespace.
Then I got a file that added a namespace to all elements and my importer instantly broke.
For example, Excel always outputs <cell ...> whereas this file has <x:cell ...>.
The "simplest thing that could possibly work" was to remove the namespace prefix and just assume that we don't have conflicting names.
But I didn't feel right about doing that. Yes, it probably would have worked fine, but I worried that I was leaving a landmine for future me.
So instead I spent 4 hours re-writing all the parsing code to handle namespaces correctly.
Whether or not you agree with my choice here, my point is that doing "the simplest thing that could possible work" is not that easy. But it does get easier the more experience you have. Of course, by then, you probably don't need this advice.
I think the author kind of mentions this: "Figuring out the simplest solution requires considering many different approaches. In other words, it requires doing engineering."
But the irony, in my opinion, is that experienced engineers don't need this advice (they are already "doing engineering"), but junior engineers can't use this advice because they don't have the experience to know what the "simplest thing" is.
Still, the advice is useful as a mantra: to remind us of things we already know but, in the heat of the moment, sometimes forget.
The simplest thing can be very difficult to do. It require thought and understanding the system, which is what he says at the very beginning. But I think most people read the headline and just started spewing personal grievances.
But an experienced engineer already knows this!
I just think it's ironic that this advice is useless to junior engineers but unneeded by senior engineers.
If you had just used a compliant XML parser as intended, you might not even have noticed that different encodings of namespaces was even occurring in the files! It just "doesn't register" when you let the parser handle this for you in the same sense that if you parse HTML (or XML) properly, then you won't notice all of the & and < encodings either. Or CDATA. Or Unicode escapes. Or anything else for that matter that you may not even be aware of.
You may be a few more steps away from making an XLSX importer work robustly. Did you read the spec? The container format supports splitting single documents into multiple (internal) files to support incremental saves of huge files. That can trip developers in the worst way, because you test with tiny files, but XLSX-handling custom code tends to be used to bulk import large files, which will occasionally use this splitting. You'll lose huge blocks of data in production, silently! That's not fun (or simple) to troubleshoot.
The fast, happy path is to start with something like System.IO.Packaging [2] which is the built-in .NET libary for the Open Packaging Conventions (OPC) container format, which is the underlying container format of all Office Open XML (OOXML) formats. Use the built-in XML parser, which handles namespaces very well. Then the only annoyance is that OOXML formats have two groups of namespaces that they can use, the Microsoft ones and the Open "standardised" ones.
[1] Famously! https://stackoverflow.com/questions/8577060/why-is-it-such-a...
[2] https://learn.microsoft.com/en-us/dotnet/api/system.io.packa...
“Simple is robust”
It’s easy to over-design a system up front, and even easier to over-design improvements to said system.
Customer requirements are continually evolving, and you can never really predict what the future requirements will be (even if it feels like you can).
Breaking down the principle, it’s not just that a simple system is less error prone, it’s just as important that a simple architecture is easier to change in the future.
Should you plan for X, Y, and Z?
Yes, but counterintuitively, by keeping doors open for future and building “the simplest thing that could possibly work.”
Complexity adds constraints, these limitations make the stack more brittle over time, even when planned with the best intentions.
https://benoitessiambre.com/entropy.html https://benoitessiambre.com/integration.html
As someone who has strived for this from early on, the problem the article overlooks is not knowing some of these various technologies everyone is talking about out, because I never felt I needed them. Am I missing something I need, but just ignorant, or is that just needless complexity that a lot of people fall for?
I don’t want to test these things out to learn them in actual projects, as I’d be adding needless complexity to systems for my own selfish ends of learning these things. I worked with someone who did this and it was a nightmare. However, without a real project, I find it’s hard to really learn something well and find the sharp edges.
Yeah, let me shoehorn that fishing trip into my schedule without a charge number, along with the one from last week...
Though there was a time when he wanted me to onboard my simple little internal website to a big complicated CICD system, just so we could see how it worked and if it would be useful for other stuff. It wouldn’t have been useful for anything else, and I already had a script that would deploy updates to my site that was simple, fast, and reliable. I simply ignored every request to look into that.
Other times I could tell him his idea wouldn’t work, and he would say “ok” and walk away. That was that. This accounted for about 30% of what he came to me with.
That is what my boss asks us to do =p
Eventually you might start adding more things to it because of needs you haven't anticipated, do it.
If you find yourself building the tool that does "the whole thing" but worse, then now you know that you could actually use the tool that does "the whole thing".
Did you waste time not using the tool right from the start? That's almost a filosofical question, now you know what you need, you had the chance to avoid it if it turned out you didn't, and maybe 9 times out of 10 you will be right.
The in-memory rate-limiting example is a perfect case study. An in-memory solution is only simple for a single server. The moment you scale to two, the logic breaks and your effective rate limit becomes N × limit. You've accidentally created a distributed state problem, which is a much harder issue to solve. That isn't simple.
Compare that to using a managed service like DynamoDB or ElastiCache. It provides a single source of truth that works correctly for one node or a thousand. By the author's own definition that "simple systems are stable" and require less ongoing work, the managed service is the fundamentally simpler choice. It eliminates problems like data loss on restart and the need to reason about distributed state.
Perhaps the definition of "the simplest thing" has just evolved. In 2025, it's often not about avoiding external dependencies. You will often save time by leveraging battle-tested managed services that handle complexity and scale on your behalf.
But all of it comes with tradeoffs and you have to apply judgement. Just as it would be foolish to write almost anything these days in assembly, I think it would be almost as foolish to just default to a managed Amazon service because it scales without considering whether A) you actually need that scale and B) there are other concerns considerations as to why that service might not be the best technical fit (in particular, I've heard regrets due to overzealous adoption of DynamoDB on more than one occasion).
The engineers who most aggressively advocate for bespoke solutions in the name of "simplicity" often have the least experience with their managed equivalents, which can lead to the regrets you mentioned. Conversely, many engineers who only know how to use managed services would struggle to build the simple, self-contained solution the author describes. True judgment requires experience with both worlds.
This is also why I think asking "do we actually need this scale?" is often the wrong question; it requires predicting the future. Since most solutions work at a small scale, a better framework for making a trade-off is:
* Scalability: Will this work at a higher scale if we need it to?
* Operations: What is the on-call and maintenance load?
* Implementation: How much new code and configuration is needed?
For these questions, managed services frequently have a clear advantage. The main caveat is cost-at-scale, but that’s a moot point in the context of the article's argument.
Same, or reliability-tiered separately. But in both aspects I more frequently see the resulting system to be more expensive and less reliable.
As I'm doing the simplest thing that could possibly work, I do not have an edge proxy.
Of course, the author doesn't mean _that_ kind of simplicity. There are always hidden assumptions about which pieces of complexity are assumed, and don't count against your complexity budget.
Sure, try to keep things simple. Unless it doesn't make sense. Then make them less simple. Will you get it wrong sometimes? Yes. Does it matter? Not really. You'll be wrong sometimes no matter what you do, unless you are, in fact, the Flying Spaghetti Monster. You're not, so just accept some failures from time to time and - most importantly - reflect on them, try to learn from them, and expect to be better next time.
As long as you understand that everything is a trade-off and, unfortunately, that the modern field is based on subjective opinions of popular and not necessarily competent people, you will be fine.
IIUC, author is a Staff SWE, so this tracks.
See also "Worse is better" which has been debated a million times by now.
Alas, you do not have infinite money. But you can earn money by becoming this person for other people.
The catch 22 is most people aren't going to hire the guy who bills himself as the guy who does the simplest thing that could possibly work. It turns out the complexities actually are often there for good reason. It's much more valuable to pay someone who has the ability to trade simplicity off for other desirable things.
"It turns out the complexities actually are often there for good reason" - if they're necessary, then it gets folded into the "could possibly work" part.
The vast majority of complexities I've seen in my career did not have to be there. But then you run into Chesterton's Fence - if you're going to remove something you think is unnecessary complexity, you better be damn sure you're right.
The real question is how AI tooling is going to change this. Will the AI be smart enough to realize the unnecessary bits, or are you just going to layer increasingly more levels of crap on top? My bet is it's mostly the latter, for quite a long time.
Dev cycles will feel no different to anyone working on a legacy product, in that case.
I always felt software is like physics: Given a problem domain, you should use the simplest model of your domain that meets your requirements.
As in physics, your model will be wrong, but it should be useful. The smaller it is (in terms of information), the easier it is to expand if and when you need it.
> System design requires competence with a lot of different tools: app servers, proxies, databases, caches, queues, and so on.
Yes! This is where I see so many systems go wrong. Complex software engineering paving over a lack of understanding of the underlying components.
> As they gain familiarity with these tools, junior engineers naturally want to use them.
Hell yea! Understanding how kafka works so you don't build some crazy queue semantics on it. Understanding the difference between headless and clusterIP services in kubernetes so you don't have to build a software solution to the etcd problems you're having.
> However, as with many skills, real mastery often involves learning when to do less, not more. The fight between an ambitious novice and an old master is a well-worn cliche in martial arts movies
Wait what? Surely you mean doing more by writing less code. Are you now saying that learning and using these well tested, well maintained, and well understood components is amateurish?
unicorn, i.e. CGI, i.e. process-per-request, became anachronistic, gosh, more than 20 years ago at this point!
at least, if you're serving any kind of meaningful load -- a bash script in a while loop can serve 100RPS on an ec2.micro, that's (hopefully) not what anyone is talking about
First of all, simplicity is the hardest thing there is. You have to first make something complex, and then strip away everything that isn't necessary. You won't even know how to do that properly until you've designed the thing multiple times and found all the flaws and things you actually need.
Second, you will often have wildly different contexts.
- Is this thing controlling nuclear reactors? Okay, so safety is paramount. That means it can be complex, even inefficient, as long as it's safe. It doesn't need to be simple. It would be great if it was, but it's not really necessary.
- Is the thing just a script to loop over some input and send an alert for a non-production thing? Then it doesn't really matter how you do it, just get it done and move on to the next thing.
- Is this a product for customers intended to solve a problem for them, and there's multiple competitors in the space, and they're all kind of bad? Okay, so simplicity might actually be a competitive advantage.
Third, "the simplest thing that could possibly work" leaves a lot of money on the table. Want to make a TV show that is "the simplest thing that could possibly work"? Get an iPhone and record 3 people in an empty room saying lines. Publish a new episode every week. That is technically a TV show - but it would probably not get many views. Critics saying that you have "the simplest show" is probably not gonna put money in your pocket.
You want a grand design principle that always applies? Here's one: "Design for what you need in the near future, get it done on time and under budget, and also if you have the time, try to make it work well."
I don't follow. I've made simple things many times without having to make a complex thing first.
The beauty of this approach is that you don't design anything you don't need. The requirements will change, and the design will change. If you didn't write much in the first place, it's easy.
You just described Podcast. It did work for many (obviously it failed for many as well). That's an excellent example of why one should start with the simplest thing that could possibly work. Probably better than the OP's examples.
1) Sometimes the simplest things is still extremely complex
2) The simplest thing that works is often very hard to find
Time and time again amazingly complex machines and they just fail to perform better than a rubber-band and bubble gum.
This stuff just can not be reimplemented that simple and be expected to work.
The music was also quite good imo.
You aren't gonna need it
If you can do this regularly, you can keep the _effective_ cognitive size of the system small even as each closed box might be quite complex internally.
Many "industry best-practices" seen in this light are make-work, a technique for expanding simple things to fill the time to keep oneself employed.
For example, the current practice of dependency injection with interfaces, services, factories, and related indirections[1] is a wonderful time waster because it can be so easily defended.
"WHAT IF we need to switch from MySQL to Oracle DB one day?" Sure, that... could happen! It won't, but it could.
[1] No! You haven't created an abstraction! You've just done the same thing, but indirectly. You've created a proxy, not a pattern. A waste of your own time and the CPU's time.
applies to the narrative
'unfuck' anything
as well. any industry and any
'behavioral lock in'
and so on.
Don't add passwords, just "password" is fine. Password policies add complexity.
For services that require passwords just create a shared spreadsheet for everyone.
/s