I said I’d move them to google sheets. There was about five minutes of awkwardness after that as I was interviewing for software developer. I was supposed to talk about what kind of tool I’d build.
I found it kind of eye opening but I’m still not sure what the right lesson to learn was.
The general way to handle this as an interviewer is really simple: acknowledge that the interviewee gave a good answer, but ask that for the purposes of evaluating their technical design skills that you'd like for them to design a new system/code a new implementation to solve this problem.
If the candidate isn't willing to suspend disbelief for the exercise, then you can consider that alongside all of the other signals your interviewer team gets about the candidate. I generally take it as a negative signal, not because I need conformance, but because I need someone who can work through honest technical disagreements.
As a candidate, what's worked for me before was to ask the interviewer if they'd prefer that I pretend ____ doesn't exist and come up with a new design, but it makes me question whether I want to join that team. IMO it's the systems design equivalent of the interviewer arguing with you about your valid algorithm because it's not the one the interviewer expects.
Now that I think about it, none of those organizations ever trained me at anything at all. Huh.
They trained us repeatedly not to bribe foreign government officials, even though I had zero access to anybody like that. There was also some mandatory training against harassing coworkers. I.e. "protect the company from lawsuits" training, not "here are some ideas for how to do your job more effectively" training. They were megacorps, too.
Now, I wonder if I had rejected earlier candidates that I would have passed if I was a better interviewer.
TL;DR: not enough training.
As a hiring manager, whenever we start a hiring period I have a conversation with my interviewer team about what qualities we're looking for and review the questions they plan to ask in order to normalize the process. Stuff like "what does a good answer look like, and why? what does a bad answer look like? is this something easy for a candidate to engage with or will you spend half the interview just explaining the background? is this coding question unreasonably hard?" and so on.
I also look at the evaluations that interviewers give relative to other interviewers. Almost every hiring cycle I've done I've had to deal with some interviewer (all over the seniority spectrum) asking unreasonably hard questions.
He got the prompt, asked questions about throughput requirements (etc.), and said, “okay, I’d put it all in Postgres.” He was correct! Postgres could more than handle the load.
He gets a call from Patrick Collison saying that he failed the interview and asking what happened. He explained himself, to which Patrick said, okay, well yes you might be right but you also understand what the point of the interview is.
They made him do it again and he passed.
As a hiring manager I've had situations like this arise because there was a gap in my plan and I didn't realize it. When those come up, we thank them for their cleverness, apologize to the candidate, reframe the situation, and give them another shot.
But also sometimes I leave intentional ambiguity in the plan. Part of the goal is to see if they have a degree of common sense commensurate to their level. If they're interviewing for a high level position, I'd expect them to be able to spot silly flaws and push back that perhaps the whole problem needs rethinking. And of course, I also expect them to know the brute force solution as well. Do they only know one? Both? Let's fine out.
The purpose of the interview is for the candidate to demonstrate their thought process and ability to communicate it. “Just use Postgres” doesn’t do that.
This would be more obvious if it was a LeetCode problem and the candidate just regurgitated an algorithm from memory without explaining anything about it. Yeah it’s technically the right answer but the interviewer can’t tell if you actually understand what you’re talking about or if you just happened to memorize and answer that works.
Interviews are about communication and demonstrating thought process.
That being said, it's also on the ones giving the interviews to push the candidates and ensure that they really are receiving the applicants best. The interviewers don't want to miss potentially great candidates (interviews are hard and nerve-wracking, and engineers aren't known for their social performance), and thus sometimes need to help nudge the candidates in the right direction.
The best thing someone can do to learn how to perform well in interviews is to sit on the other side where you’re interviewing candidates. Some candidates will get stuck on arguing some irrelevant point or trying to fight against the interview question for too long in an interview. Once you see how much it hurts the interview process you learn to never do it yourself.
There's a ton of incredibly talented neurodivergent people in our ecosystem who would trip up on that question just because of how it's framed
Because how is the interviewee to know if you're testing for the technically sophisticated answer no one in their right mind would ever write or the pragmatic one?
From one side, we call ourselves problem solvers, on the other hand we are not satisfied with simple solutions to these problems. If im interviewing for a job, i should be expected to behave and solve hypothetical problems the way id do it on the job. If that screws up your script, you probably suck at hiring and communicating your expectations.
I had this happen in a Google interview. I did back of the envelope math on data size and request volume and everything (4 million daily events, spread across a similar number of buckets) and very little was required beyond that to meet performance, reliability, and time/space complexity requirements. Most of the interview was the interviewer asking "what about" questions, me explaining how the simple design handled that, and the interviewer agreeing. I passed, but with "leans" vs. "strong" feedback.
On the other hand, interviewees can give poor answers with no explanation. The interviewer should press for an explanation in those cases, of course, but perhaps some are trying to see if the interviewee instinctively provides at least some basic rationale behind the answer without having to be prodded each time, in which case it is a matter of communication habits and skills. Communication is essential, and it is under-emphasized and under-taught in so-called 'STEM' curricula.
I'd assume that if he got a call from Patrick himself and a second opportunity to get interviewed, that's already a cue for interviewers to pass him regardless of what he says?
Exactly, it's also a test of ability to conform. Especially useful to weed out rogue behavior picked up in startups.
If a valid answer was “just use Postgres” then it just wasn’t a very good interview question.
In real life, the answer almost certainly would be “just use Postgres” and everyone would be happy.
If the interview wants you to think about stuff that never happens in your role, I think it is a sign that in your role, you're expected to solve the problems like in the interview.
And yes, I have done this on a second Google interview about 15 years ago.
Sometimes you just have a bad interviewer who is looking for something specific from you but isn't telling you. If you're experienced in these interviews, you catch the signs and adapt by asking questions to suss out which direction the interviewer wants to take it.
Sometimes your answer is plausible but the interviewer wants to see you justify it. Sometimes your answer is wrong but the interviewer wants to see if you can reason your way through it, and maybe come up with an alternative.
If you're junior/inexperienced, it's often hard to tell and it'll feel arbitrary/unfair, and unfortunately that's just how it goes. As a more senior/experienced candidate, you can often figure out which situation you're in by asking questions to feel out the interviewer and then try to pivot during the interview, though it still takes valuable minutes out of the interview that you could have otherwise spent showing your competence.
They want a conversation to see how you think, not an actual answer.
Which is stupid, because they asked a question that the person didn't need to think to answer. So they didn't get to see them think.
https://github.com/EnterpriseQualityCoding/FizzBuzzEnterpris...
I would hire the "just use postgres" dude in a heartbeat without re-testing, if the numbers made sense, and perhaps give a stern talking-to to the interviewers. But then again I'm not a unicorn founder, so what do I know.
This is the same issue that was prevalent when the industry switched from HDD to SSD: some system design questions suddenly became trivial, because the IOPS went up by magnitudes. This is not a failure of the interviewees, who correctly went with the times, but a failure of the interviewers.
The point of a system design interview is to have a discussion that examines possibilities and tradeoffs.
Then, there are hiring managers that suck and you might be discarded because you didn't follow the script. Sure, but that's a bullet you dodged.
So the point is? I honestly dont understand.
Sometimes the point of the interview is to see if the candidate knows an existing solution and "just use postgres" is the good answer. Sometimes it's to test the technical chops and pretending postgres doesn't exist is the point.
The candidate shouldn't be expected to always guess right, unless the position says "a psychic". The interviewer should notice if the candidate is solving the wrong kind of problem and nudge them in the right direction instead of punishing the candidate for the wrong guess.
The question is framed to you as a way for you to show you know x, y and z and talk about x, y and z.
Even if a valid solution is just do a, that's great. But the interviewer has no idea if you actually know about x ,y and z do they ?
I like that this sentence can be read both as a productive, well-meaning view on interviews, as well as a highly cynical one.
Also makes me wonder if the person will keep showing how much they know and how smart they are after they are hired, and if that is a good thing.
Saying “just use Postgres” and then providing no explanation for why you believe Postgres is sufficient for the job, a general explanation of what type of hardware and architecture you’d use, and other details is not answering the question.
With a smiley face front-end, of course. Wouldn't want to seem not-nice!
I feel like lots of people just follow the happy path and don't understand that complexity incurs real cost.
Why on Earth did the company have to be so willingly obtuse and stupid about it including what sounds like the CEO (well at least he gave him another shot, but there doesn't need to be implicit assumptions about the "point of the interview", just come out and address it head on explicitly.)
This should go straight to the DOL, EEOC, FTC and other bodies as some form of abusive labor practice that excises it from the employment process under threat of economic sanctions
As much as people will rely on databse (rdbms/sql) backed applicatons, in the end a lot of the business world runs on spreadsheets... Not only that, but excel, and I'm assuming plenty of others have integration points for pulling data from other resources... Spreadsheet masters can do very impressive things with what appears to be a simple tool.
I realize this is part of an interview game, but perhaps the best response is still to ask why this is a problem in the first place before you launch into a technical masterpiece. Force the counterparty to provide specific (contrived) reasons that this practice is not working for the business. Then, go about it like you otherwise would have.
I do dislike interviews where a candidate can fail simply by not giving a specific, pre-canned answer. It suggests a work culture that is very top-down and one that isn’t particularly interested in actually getting to the truth.
I get that "communicate your thought process" or "play along with the exercise" gets offered as the fix here. But that framing bothers me too. Why should simplicity require more justification than complexity? Google Sheets is the design. The fact that it doesn't sound like engineering is the whole point.
These days if I were interviewing someone and they said, "I'd use the simple solution that is fairly ubiquitous", I'd say, "yes! you've now saved yourself tons of engineering hours - and you've saved the company eng money".
So true...I've failed interviews, because the interviewee did see using library functions as a sign of weakness.
Sometimes we'll ask market sizing questions. We will say it's a case question, it's to see their thought process, they're supposed to ask questions, state assumptions, etc.
Occasionally we'd get a candidate that just doesn't get it. They respond "oh I'd Google that". And I'll coach them back but they just can't get past that. It's about seeing how you approach problems when you can't just Google the answer, and we use general topics that are easily accessible to do so. But the downside is yes, you can google the answer.
As an interviewee it’s important to try and identify whether the group you’re interviewing with operates this way, literally: How will they get the money to pay for your salary? That way you avoid giving nom-starter answers to interview questions.
Then it's the wrong solution. Period.
There are plenty of annoyances with spreadsheets, but part of what makes them so robust and powerful is that they don't take a ton of specialized knowledge, and they remain incredibly flexible.
An expensive, complicated, static, "right" solution for a small business is folly (honestly - this stays true up to medium/large business). It's a ton of time and energy focused on the absolute wrong thing. When a spreadsheet can reach the same result in a fraction of the time.
Especially given the result may not actually be that important, and they pivot to something else entirely in the very near future.
I've worked at several startups. I'd caution even software startups from assuming that custom solutions are the right approach. They usually aren't. They're a waste of time and effort that ends up saddling you with a brittle, expensive solution designed to solve problems from last year.
There are plenty of reasons that a department within a company will prefer spreadsheets. Software is not the answer to everything and also this is the same problem you get when Microsoft introduces those pesky 'Power App' developers etc or previously the Sharepoint 'web parts' etc....essentially someone who kind of feels they are the 'owner' of some information then decides to formalise the process in their own little way.
Now you have a person wasting a bit of time making their little tool but you've also got people complaining that someone's now essentially taken control of it etc. At a former employer our procurement team used spreadsheets to track basically everything but importantly everything on our PCBs - every single component and their suppliers and prices etc (various factories around China usually). This would have been a horrible thing to try and formalise in a web app just because of how often they were all changing their own conventions etc (often suppliers changing what information they gave to them, too). It would have been a wild goose chase to formalise it and more than the trouble it would be worth.
I'd actually trust you to take on harder problems
Doesn't really matter what the situation is, there's much more that can be achieved in my book with that kind of mindset :)
I'm also of the opinion that in an increasingly LLM software written world, being able to have this kind of mindset will actually be really valuable
Spreadsheets are a tricky one some people like the power and automomy they have with spreadsheets.
But more often spreadsheets are the only way to transfer data between solos and it wastes a lot of time and is error-prone.
If they are collectively spending 1hr/mo on the spreadsheet then it’s not worth an SWE’s time to optimize it. If they are spending 4hr/day on the spreadsheet then it’s a prime candidate for automation.
Then after a brief discussion of that you could actually ask if the purpose of the question was for you to design a system to handle that situation and jump into the design.
Exactly because that means less costs for software development when deliverying solutions.
But this is connected to another thread on HN about engineer/manager titles and how they basically have no value if you try to compare them between employers.
At least from the point of view of the interviewer, this was the point where they should give you a polite "hey, play along" nudge.
That may be the game, but we all know it's bullshit, and we shouldn't be playing along.
If a member of my team actually proposed building a bespoke system for something that can be straightforwardly done in a spreadsheet, we'd be having some conversations about ongoing maintenance costs of software
All interviews are contrived / artificial situations: The point is to understand the candidate's thought processes. Furthermore, we're getting Bilsbie's (op) take on the situation, there may be context that the interviewer forgot to mention or otherwise Bilsbie didn't understand / remember.
Specifically, if (the hypothetical situation) is a critical business process that they need an audit log of; or that they want to scale, this becomes an exercise in demonstrating that the candidate knows how to collect requirements and turn a manual process into a business application.
The interviewer could also be trying to probe knowledge of event processing, ect, ect, and maybe came up with a bad question. We just don't know.
Given that Bilsbie can't read their interviewer's mind, there's no way to know if that's what the interviewer wanted, or if the interviewer themselves was bad at interviewing candidates.
So now you get Engineer B's output even faster, with even more impressive-sounding abstractions, and the promotion packet writes itself in minutes too. Meanwhile the actual cost - debugging, onboarding, incident response at 3am - stays exactly the same or gets worse, because now nobody fully understands what was generated.
The real test for simplicity has always been: can the next person who touches this code understand it without asking you? AI-generated complexity fails that test spectacularly.
To be fair, a lot of the on call people being pulled in at 3am before LLMs existed didn't understand the systems they were supporting very well, either. This will definitely make it worse, though.
I think part of charting a safe career path now involves evaluating how strong any given org's culture of understanding the code and stack is. I definitely do not ever want to be in a position again where no one in the whole place knows how something works while the higher-ups are having a meltdown because something critical broke.
I like to have something like the following in AGENTS.md:
## Guiding Principles - Optimise for long-term maintainability - KISS - YAGNI
So, I asked it to modify its instructions.md file to not repeat that mistake. The result was the new line "Avoid single-use wrapper functions; inline logic at the call site unless reused"
instruction.md is the new intern.
Acting like people can't be good at their job is frankly dehumanizing and says a lot about your mindset with how you view other fellow devs.
Maybe that's "the manager's job", but that's just passing the buck and getting a worse solution. Every level of management should be looking for the best solution.
So, I asked it to modify its instructions.md file to not repeat that mistake. The result was the new line "Avoid single-use wrapper functions; inline logic at the call site unless reused"
instructions.md is the new intern.
But given how poorly bought software tends to fit the use case of the person it was bought for... eventually generate-something-custom will start making more and more sense.
If you end up generating something that nobody understands, then when you quit and get a new job, somebody else will probably use your project as context for generating something that suits the way they want to solve that problem. Time will have passed, so the needs will have changed, they'll end up with something different. They'll also only partially understand it, but the gaps will be in different places this time around. Overall I think it'll be an improvement because there will be less distance (both in time and along the social graph) between the software's user its creator--them being most of the time the same person.
Biggest problem is that next person is me 6 months later :) but even when it’s not a next person problem how much of the design I can just keep in my mind at a given time, ironically AI has the exact same problem aka context window
Avoid hands-on tech/team lead positions like hell.
In the FAANGs I've worked at, engineers who come from scrappy companies and implement hacks (Like the example of emailing spreadsheets around) undermine the business and will cost the productivity of thousands of people.
However, at the startups I've worked at, the folks from big companies that try to implement a super complex thing (e.g. exotic databases, overly ambitious infrastructure) The results are equally catastrophic for a company attempting to bootstrap when the complexity is so far removed from their core business.
What makes an experienced engineer is recognizing both states, understanding what works where and making the right trade-offs, usually from experience you can't fake your way through. I've seen a lot of projects that took 10-20 engineers 18 months to so we could sell something that landed a $100M contract with a customer. You see that enough times and you won't bias as hard against complexity. But of course it's situation dependent, like anything.
In many ways, the Door Desk award was for simplicity. I remember, one time, someone got an award for getting rid of some dumb operations room with some big unused LCD TVs. When you won these awards, you rarely got any kind of reward. It was just acknowledgement at the meeting. But that time, they literally gave the guy the TVs.
(amzn 94-96)
The longest lived projects and solutions I've worked on have always been the simplest, easiest to replace solutions. Often derived from simple tests scenarios or solutions that just work and get shifted over without much re-work.
What's somewhat funny, with this is that AI code assistants have actually helped a lot with continuing this approach for me... I can create a stand alone solution to work on a library or component, work through the problems, then copy the component/library into the actual work project it was for. I'm in a really locked down internalized environment, so using AI for component dev is on my own hardware... but the resulting work is a piece that can be brought in as-is. No exposure of internal data/resources.
I don't think I'll have a level of trust to "one-shot" or vibe code solutions from AI, but leveraging the ability to spin up a project as a sample to test a component/library is pretty great to say the least.
"Reduced incidents by 80%", "Decreased costs by 40%", "Increased performance by 33% while decreasing server footprint by 25%"
Simplicity for its own sake is not valued. The results of simplicity are highly valued.
If there's no competent front-line technical management who can successfully make this simple comparison, then, sure, in that case the team may be fucked.
In general, I agree that you can and should judge (not necessarily measure) thing like simplicity and good design. The problem is that business does want the "increased this by 80%, decreased that by 27%" stuff and simplicity does not yield itself to this approach.
Building a system that's fast on day one will not usually be rewarded as well as building a slow system and making it 80% faster.
(when there is a simpler design over more complex "big ball of mud abomination" in contrast)
His response: "I can sell a good looking car and then charge them for a better running engine"...
https://www.youtube.com/watch?v=T4Upf_B9RLQ hits a little too close to home.
That's regardless of the lip service they pay to cost cutting or risk reduction. It will only get worse, in the AI economy it's all about growth.
My experience is no one really gets promoted/rewarded for these types of things or at least not beyond an initial one-off pat on the back. All anyone cares about is feature release velocity.
If it's even possible to reduce incidents by 80% then either your org had a very high tolerance for basically daily issues which you've now reduced to weekly, or they were already infrequent enough that 80% less takes you from 4/year to 1/year.. which is imperceptible to management and users.
And at the same time it's impossible to convince tech illiterate people that reducing complexity likely increases velocity.
Seemingly we only get budget to add, never to remove. Also for silver bullets, if Big Tech promises a [thing] you can pay for that magically resolves all your issues, management seems enchanted and throws money at it.
There's a short film making the rounds that captures this perfectly -- an employee uses AI to generate the quarterly results his whole department was working on, and instead of being promoted, he gets fired: https://youtu.be/O5FFkHUdKyE
The simplicity penalty is even worse when the simplification comes from AI. It's not just "you made us look bad" -- it's "you made our entire team look unnecessary."
I guess it may be important to underscore the value that simplicity provides over needless complexity or to sell people on the value of problems prevented rather than preventable catastrophes that were dealt with
Maybe we could encourage a culture of patting people on the back for maintaining reliable "boring" systems
Some people also crave "drama" so there might be a way to frame "boring reliability" as some kind of "epic daily maintenance struggle that was successfully navigated"
As engineers, we tend to keep away from the limelight and quietly get shit done and be happy with it. But professional growth and recognition requires visibility somehow. We need to be creative on how to achieve that.
Being obviously pedantic here, I agree with what you meant.
Don't even get me started on the resume-driven development that came along with it.
And maybe I'm completely wrong. This is a perspective of one.
One common example I cite is at one job I owned Kafka and RabbitMQ clusters. Zero consideration was given to message size recommendations and we had incidents on the regular because some application was shoving multi-hundred megabyte messages into RMQ. They'd do other stupid shit like not ack their messages which would cause them to never be removed from local disk. This was a huge org, public company, hiring "only the best and brightest".
Management endlessly just threw more hardware at it rather than make the engineers fix their obviously bad architecture. What a headache. Some companies take the "prioritize engineer happiness" thing right off a cliff.
And complexity doesn't always sell better. A lot of times it might look like the whole thing is messy, or too hard to maintain, tech burden nightmare. Things that are simple might look complex and vice versa too, I think anyone who had to implement requirements from people who don't understand the implementation complexities will know this very well.
I've only worked at my startup so I can't comment on scale elsewhere, but if our simple architecture can handle 30k requests per second, I think it can handle most other companies scale too.
In the hands of an experienced developer/designer, AI will help them achieve a good result faster.
In the hands of someone inexperienced, out of their depth, AI will just help them create a mess faster, and without the skill to assess what's been generated they may not even know it.
It's good at code generation, feature wise, it can scaffold and cobble together shit, but when it comes down to code structure, architecture, you essentially have to argue with it over what is better, and it just doesn't seem to get it, at which point it's better to just take the reins and do it yourself. If there's any code smells in your code already, it will just repeat them. Sometimes it will just output shit that's overtly confusing for no reason.
There's always going to be some overlap, wanting to use a new skill/library in a production system, but maybe in general it's best to think of learning and writing/generating production code as two separate things. AI is great for learning and exploration, but you don't want to be submitting your experiments as PRs!
A good rule of thumb might be can you explain any AI-generated design and code as well as if you had written it yourself? If you don't fully understand it, then you are not in a good position to own it and take responsibility for it (bugs, performance, edge case behavior, ease of debugging, flexibility for future enhancement, etc).
I feel/am way more productive using chatgpt codex and it especially helps me getting stuff done I didn't want to get started with before. But the amount of literal slop where people post about their new vim plugin that's entirely vibecoded without any in-depth thinking about the problem domain etc. is a horrible trend.
Instead you talk about how you complete all your tasks and have so much bandwidth remaining compared to all your peers, the beneficial results of simplicity. Being severely under used while demonstrating the ability to do 2x-10x more work than everybody else is what gets you promoted.
In this vein simplicity is like hard work. Nobody gives a shit about hard work either. Actually, if all you have to show is how hard you work you are a liability. Instead its all about how little you work provided and that you accomplish the same, or more, than everybody else.
Ideally we need metrics saying, "my projects require 30% less support or 50% less brainpower than comparable projects". Things like "average cyclomatic complexity", etc.
At core, complexity is derived from discovery of demand within those pesky complex humans.
Simplicity is the mechanism of finding common pathways within the mess of complexity of a product.
the tragedy is that simplicity is very expensive and beyond most organizations ability to support (especially since it can slow down demand discovery), and this is one of the allures of big tech for me. I was greatly rewarded and promoted for achieving simplicity within infrastructure.
As a consultant/contractor I always evangelise simplification and modelling problems from first principles. I jump between companies every 6-12 months, cleaning up after years of complexity-driven development, or outright designing robust systems that anybody (not just the author) can maintain and extend.
This level of honesty helps you build a reputation. I am never short for work. I also bill more than I could ever as a full-time engineer based in Europe.
BUT, at least very occasionally I have seen people get promoted for simplicity, I've even successfully made the case myself. With a problem that was itself so complex that it was causing fires on a regular basis, and staff & principal engineers didn't want to touch it with a ten foot pole. When a senior eng spent a couple of weeks thinking about the problem and eventually figured out a way to reframe it and simplify the solution, melting away months of work, making the promo case was actually quite easy.
The problem is, the opportunities to burn down complexity like that don't present themselves nearly as often as the opportunities to overcomplicate a thing, which are pretty much unbounded.
Too often the smallest changeset is, yes, simple, but totally unaware of the surrounding context, breaks expectations and conventions, causes race conditions, etc.
The good bit in tfa is near the end:
> when someone asks “shouldn’t we future-proof this?”, don’t just cave and go add layers. Try: “Here’s what it would take to add that later if we need it, and here’s what it costs us to add it now. I think we wait.” You’re not pushing back, but showing you’ve done your homework. You considered the complexity and chose not to take it on.
The answer to this is almost always "NO" in my experience, because no one ever actually has good suggestions when it comes up. It's never "should we choose a scalable compute/database platform?" It's always "should we build a complex abstraction layer in case we want to use multiple blob storage systems that will only contain the lowest common denominator of features of both AND require constant maintenance AND have weird bugs and performance issues because I think I'm smarter than AWS/Google AND ALSO we have no plans to actually DO that?"
/I'm not bitter...
It's not just the most "elaborate system". The same thing happens in so many other ways. For example a good/simple solution is one and done. Whereas a complex one will be an interminable cause of indirect issued down the road. With the second engineer being the one fixing them.
Then there's another pattern of the 10x (not the case with all 10x-ers) seeding or asked to "fix" other projects, then moving on to the next, leaving all the debt to the team.
It's really an amazing dynamic that can be studied from a game theoretical perspective. It's perhaps one of the adjacent behaviors that support the Gervais principle.
It's also likely going to be over soon, now that AI is normalizing a lot of this work.
The sad thing is that it is common to get fired when you make things better bc then your work is perceived as "done" and your skills are no longer necessary. There are countless IT job stories where someone delivers a technical solution that saves a company a ton of money or generates revenue, then they get fired bc the solution has been delivered and an off shore team has been hired to maintain the work.
Big corps suck.
Edit -- reading some the responses here on this topic and they are...eye-opening and depressing.
Instead I went to the hardware store across the street and bought the biggest (and cheapest) screwdriver I could find and attached it with some cord to the HSM. They never lost it afterwards.
In fact, simplicity often is the best future-proofing. Complex designs come with maintenance costs, so simple designs are inherently more robust to reorgs, shifted priorities, and team downsizing.
Rarely have I seen an actually straightforward, simple feature that can be done in a day used as the basis to spin up a 3-week mini-project with a complicated new architecure.
What happens is a complicated-sounding feature is requested, and some devs will just take it literally and implement it, maybe along with some amount of "future-proofing" that logically follows because the spec is poorly scoped.
Other devs will spend some time thinking about it, realize that there is a really a simple requirement at the core of the request, and it only sounds complex because it was vaguely specified (or maybe these days an LLM was used to write the spec, and its vomit was copy-pasted verbatim). They just implement the simple thing that is the actual need.
This is one place where the agile/scrum practice of planning poker can help. You get a few smart people in a room, and discuss the story and its requirements. Hopefully someone will throw out a low number of points and say "isn't this simply asking for..."
Over my career, most of the complicated code I have written is no longer running. What is still running after 10 years? Postgres (or more broadly, a relational database). Fad frameworks or architectures come and go pretty quickly, they don't end up working as advertised, and it's on to the next thing. I no longer want to spend time in this hamster wheel churning out complicated code that will only end up as next year's tech debt.
If every company I know does this, how am I suppose to make money?
There are reasons for "unnecessary" complexity. Mainly cost and time.
Why? We learn all these cool patterns and techniques to address existing complexity. We get to fight TRexes… and so we get paid good money (compared to other jobs). No one is gonna pay me 120K in europe to build simple stuff that can work in a single sqlite db with a php fronted.
The honest opinion no one wants to hear is that programmers do not deserve the money they are paid for because MOST of the time what it's really needed is a "single sqlite db with a php frontend".
I built a showback model at a prior org. Re-used shelfware for the POC, did the research on granular costs for storage, compute, real estate, electricity, HVAC maintenance, hardware amortization, the whole deal. Could tell you down to the penny how much a given estate cost on-prem.
Simple. Elegant. $0 in spend to get running in production, modest spend to expand into public cloud (licensing, mainly). Went absolutely nowhere.
Got RIFed. On the way out the door, I hear a whole-ass team did the same thing, using additional budget, with lower confidence results. The biggest difference of all? My model gave you the actual cost in local currency, theirs gave you an imagined score.
The complexity (cost of a team, unnecessary scoring) was rewarded, not the simplicity.
Your job is to deliver value. If you can get stuff done quicker and without it breaking, you did great. Some one who spent more time doing the same thing except took longer and has a more brittle solution they have to keep going back and fixing doesn't look good.
And simple solutions are easier to explain and convince people.
The irony is that the elaborate design usually handles those hypotheticals incorrectly anyway, because you can't predict real requirements from imagination. The simple version gets modified when real feedback arrives, and the modifications are cheaper because there's less architecture to work around.
More than once I have seen the same project yield two separate promotions, for creating it and deleting it. In particular this happens when the timescale of projects is longer than a single engineer's tenure on a given team.
But yes, avoiding complexity is rarely rewarded. The only way in which it helps you get promoted is that each simple thing takes less time and breaks less often, so you actually get more done.
Of course, if it's the person in charge introducing said overengineering there is a problem.
Worse, to suggest a simpler approach checking existing products/APIs or even preparing toy prototype is required to be confident in own advice. This hidden work is left entirely unnoticed even by well meaning managers/engineers: they simply don't know if you knew or had to discover simpler solution.
— C. A. R. Hoare
Since one of microservice's benefits is solving a coordination problem, now that teams are getting smaller due to AI, I wonder if we will see monoliths make a resurgence in some cases.
The environment where the over-engineer tends to be promoted is one where the engineering department is (too) far separated from where the end users are. Think of very large organizations with walled departments, or organizations where there simply is not enough to do so engineers start to build stuff to fight non existing issues.
> But for Engineer A’s work, there’s almost nothing to say. “Implemented feature X.” Three words. Her work was better. But it’s invisible because of how simple she made it look. You can’t write a compelling narrative about the thing you didn’t build. Nobody gets promoted for the complexity they avoided.
Well, Engineer A's manager should help her writing a better version of her output. It's not easy, but it's their work. And if this simpler solution was actually better for the company, it should be highlighted how in terms that make sense for the business. I might be naive and too optimistic but good engineers with decent enough managers will stand out in the long run. That doesn't exclude that a few "bad" engineers can game their way up at the same time, even in functional organizations. though.
There's a significant asymmetry though, it's not just a bit more work. I'm a bit cynical here, but often it's easier to just overengineer and be safe than to defend a simple solution; obviously depending on the organization and its culture.
When you have a complex solution and an alternative is stacked up against it, everything usually boils down to a few tradeoffs. The simple solution is generally the one with the most tradeoffs to explain: why no HA, why no queuing, why no horizontally scalable, why no persistence, why no redundancy, why no retry, etc. Obviously not all of them will apply, but also obviously the optics of the extensive questioning will hinder any promotion even if you successfully justify everything.
Simpler than what? The reason this phenomenon is so pervasive in the first place is that people can’t know the alternatives. To a bystander (ie managers), a complex solution is proof of a complex problem. And a simple solution, well anyone could have done that! Right?
If we want to reward simplicity we have to switch reference frame from output (the solution), to input (the problem).
It's hard to keep things simple. Management should be mindful of that and encourage engineers to follow YAGNI, to do refactorings that remove more code than they add, etc.
It could be something overbuilt, large organization structures. Brittle solutions that are highly performant until they break. Or products/offerings that don't grow for similar reasons, simpler-is-better, don't compete with yourself. Or those that grow the wrong way-- too many, much to manage, frailty through complexity, sku confusion.
Alternatively, things that are allowed to grow with some leeway, some caution, and then pruned back.
There's failure modes in any of these but the one I see most often is overreaching concern for any single one.
a) finding a new theoretical frame that simplifies the space or solutions, helps people think through it in a principled way
b) finding ways to use existing abstractions, that others may not have been able to find
c) using non-technical levers, like working at the org/business/UX level to cut scope, simplify requirements,
The way you can make complexity work for your career, is to make it clear why the problem is complex, and then what you did to simplify the problem. If you just present a simple solution, no one will get it. It’s like “showing your work”.
In some orgs, this is hopeless, as they really do reward complexity of implementation.
Promotions are supposed to incentivise people to stay, rather than leave. If the company never promoted anyone, people would leave. So there needs to be a path for promoting people. But that process doesn’t have to be transparent, or consistent, or fair - in-fact it rarely is.
You promote people who consistently overdeliver, on time, at or below cost, who are a pleasure to work with, who would benefit the company long term, who would be a pain to lose. A key precondition is that such people consistently get more done compared to other people with equal pay, otherwise, they don’t stand out and they are not promotion material.
What counts as overdelivering will vary based on specific circumstances. It’s a subjective metric. Are you involved with a highly visible project, or are you working on some BS nobody would miss if it got axed? Are you part of a small team, or are you in a bloated, saturated org? Are you the go-to person when shit hits the fan, or are you a nobody people don’t talk to? Are you consistent, or are you vague and unpredictable? Does your work impact any relevant bottom lines, or are you just part of a cost centre? It really isn’t rocket science, for the most part.
Numerous times I've seen promotions going to people who were visible but didn't do the actual work. Those who share the achievements on Slack, those who talk a lot, get to meetings with directors, those who try to present the work.
1. Do I consistently deliver more (in output, impact, or reliability) than peers at my pay level?
2. Is my work visible and tied to meaningful business outcomes, rather than low-impact tasks?
3. Am I known as dependable and easy to work with, especially under pressure?
4. Would the company feel a real loss-operationally or financially-if I left?
5. Have I made myself clearly more valuable to the organization than what I currently cost?
- CV-driven development. Adding {buzzword} with {in production} sounds better than saying I managed to make simple solutions faster.
- Job security. Those who wish to stay longer make things complicated, unsupportable, and unmaintainable, so they become irreplaceable.
Can you actually imagine a promo committee evaluating the technical choices? "Ok, this looks pretty complex. I feel like you could have just used a DB table, though? Denied."
Absolutely not! That discussion happens in RFCs, in architecture reviews, in hallway meetings, and a dozen other places.
If you want simplicity, you need to encourage mentorship, peer review, and meaningful participation in consensus-building. You need to reward team-first behavior and discourage lone-wolf brilliance. This is primarily a leadership job, but everybody contributes.
But that's harder than complaining that everything seems complicated.
A committee with no skin in the game, who knows? But a manager who actually needs stuff done, absolutely.
I on the other hand spent 3 weeks optimizing our core service and reduced 2x the opex costs of the large complex 3 year migration.
In my yearly review my manager acknowledged my impact, but said I need to solve more complex problems to get to Staff Engineer. I protested saying that my 3 weeks of work had a larger impact than 20 engineers over 3 years, but he told me that is just how it works.
Take these two alternatives:
class UserService {
PostgresDatabase db;
}
class UserService {
IDatabase db;
}
There are some coworkers who will veto the second example for being too complex, because Postgres is all you use for now, and if you really need to use a second database, you can change the code then (YAGNI). Also the Interface gives you a pointless indirection that breaks IntelliSense so you can't just 'click-through' to follow the code flow.
The engineer that consistently quotes 3x my expectation (and ends up taking 4x with bugs) is going to look way worse than the engineer that ships things quickly with no drama.
It can even happen that the tag "very smart" gets attached to those sidelined engineers. That's not necessarily a compliment.
In smaller companies it's a lot easier to express the distinctions and values of simplicity to ears that might actually appreciate it (so long as you can translate it into what they value - simple example is pointing out that you produced the same result in much less time, and that you can get more done on overall feature/task level as a result).
The obvious outcome will be that the most skilled pretenders optimizing for their selfish profit narrow view, no matter what the consequences will be for the collectivity on large scale and at long terms.
In my (limited) experience as an engineer and manager, leadership (e.g., a VP) didn’t like (or reward) simplicity. Simple solutions often meant smaller teams, which wasn’t something they were pushing for, especially pre-2024. I do think this is slowly evolving, and that the best leaders now focus on removing unnecessary complexity and improving velocity.
Essentially, there are two parallel teams, one is seen constantly huddling together, working late, fixing their (broken) service. The other team is quiet, leaves on time, their service never has serious issues. Which do you think looks better from the outside?
The real question is how do you tell engineer A who can figure out how to make the complex problems simple from engineer C who can't handle complexity and so writes simple solutions when the complex one is needed.
I don't think this phenomenon is unique to programming. My plumber was explaining how he put in a manifold and centralized whole-house off valve accessible indoors and I was like, okay, thanks? I can just turn it off at the street.
Only established professionals have the status and self-confidence to show restraint. I think that explains interviews.
We have a calendar reminder to exercise the valves in our house yearly, and the fact that they’re easy to get at helps make sure it’s a quick job, not a tedious one.
Not a plumber, but have lived in enough old houses with iffy valves to have been bitten a few times.
> The interviewer is like: “What about scalability? What if you have ten million users?”
This reminded me of how much more fun I find it to work on software that always only has one user, and where scaling problems are related solely to the data and GUI interaction design.
> It also shows up in design reviews. An engineer proposes a clean, simple approach and gets hit with “shouldn’t we future-proof this?” So they go back and add layers they don’t need yet, abstractions for problems that might never materialize, flexibility for requirements nobody has asked for. Not because the problem demanded it, but because the room expected it.
$100 says the "clean, simple" approach is the one which directly couples the frontend to the backend to the database. Dependencies follow the control flow exactly, so that if you want to test the frontend, you must have the backend running. If you want to test the backend, you must have the database running.
The "abstractions for problems that might never materialize" are your harnesses for running real business logic under unit-test conditions, that is, instantly and deterministically.
If you do the "simple" thing now, and push away pesky "future-proofing" like architecting for testing, then "I will test this" becomes "I will test this later" becomes "You can't test this" becomes "You shouldn't test this."
For example, person A implements the simple solution, gets the project done faster while person B over engineers, has seemingly impressive stuff to talk about but at the end of the day doesn't ship.
This extends to suggesting huge licenses like from Salesforce. The Marketing and HR teams are ecstatic that they can purchase another license of their favorite software, they can go shopping! If I had implemented a free and more efficient CRM, there would be no networking effect.
This all builds systems that are vastly more expensive (to the tune of hundreds of thousands of dollars), slower, and much harder to fix. YCombinator financially benefits from this and it's all very corrupt. Most of the time, I have to really gain the "soft skills" to activate the networking (nepotism) effects.
It's not about what you know, it's about who you know.
Problem is in big tech -- the incentives are all aligned towards complex stuff
you wanna get promoted - do complex stuff that doesn't make sense. If you get promoted, then it also boosts the performance of your manager.
the only way to escape this nonsense is to work at smaller companies
right now you've people advocating for A.I coded solutions yet never realizing that A.I solutions result in a convoluted mess since A.I never possesses the ART of software engineering i.e knowing what to cut out
Good leaders perceive workhorse vs showhorse spectrum, critical toil vs needless flash (and vice versa).
It’s hard. Most fail at hard things. The industry in the aggregate will fail at hard things
So you get articles like this.
Be the change you want to see in the world. If you are in management, promote those that see the value in simplicity.
as a manager its constant fighting the pressure to build "Great software" that is way above what the company needs instead building working software that addresses customer needs in a timely manner.
My dude we are s startup with two servers and 20 customers, we do not need infinite scalability.
A lot of this boils down to promo system being so systematized. I've never heard of people in any other field min/max their promotions as hard along with all of the expert jargon in any other field I've worked in. Packets, peers, comp, other co comps, what your boss thinks of you, what your boss thinks of your peers (nee: competitors), and the inevitable crash out when they don't get the promotion. All part of the bigco experience! I feel like when we systematized comp into ranks Lx, Ly we gave up our leverage a little bit.
You can try to explain this OP’s concept to a stakeholder in a 1000 different sensible ways and you’ll get blinking deer-in-headlight eyes back at you.
This skill is hard-earned and, so, rare.
Therefore, many hierarchies are built on sufficient mediocrity top to bottom.
Which works because bottom line doesn’t often matter in software dev anyway.
And even when it does matter it’s multiplicatively rare to have a hierarchy or even the market that it tries to serve who can build, comprehend, handle high power::complexity systems, products, tools.
it just isn't very appetising
The service saw maybe a few hundred transaction per day, total database size: 2 - 3GB. The systems would hold data about each transaction, until processed and then age it out over three months, making the database size fairly stable.
Talking to a developer advocate for Azure we learned that CosmosDB would get a Cassandra API and we got access to the preview. The client was presented with a solution were the service would run as a single container in Azure Websites and using CosmosDB as the database backend. The whole thing could run within the free tier at that point. Massive saving, much easier to manage. We got rejected because the solution didn't feel serious and to simplistic for an organisation of their scale.
On the other hand I also once replaced a BizzTalk server with 50 lines of C# and that was well received by the client, less so of my boss who now couldn't keep sending the bill for a "BizzTalk support contract" (which we honestly couldn't honour anyway).
I sometimes feel like that's what it is. Simple solutions make some people feel unimportant.
And long before performance review time, I'd have mentioned further up that A was looking like a 5X engineer - best if we keep her happy.
I once hacked a spreadsheet in a week that was good enough to not embark on a multiple-months 3-devs project.
In the same team, I tweaked a configuration file for distributed calculations that shaved 2 minutes of calculation on an action that the user would run thirty times a day.
I got paid all right.
People don't give a shit about complexity or simplicity. They care about two things:
1. Does it work
2. How soon can you ship
There is a third thing that stakeholders really like: when you tell them what they should be building, or not building.