I remember reading this back in 2015, but how is this not just the age old conservative (don't do more than needed) vs progressives (lets try some new risk things) debate? As much as I can relate to a more conservative choice when choosing tech that might power a giant consumer company, sometimes using riskier tech in a startup makes more sense to get the real innovation flowing...
and the idea of "Choose New Technology, Sometimes" just feels like a little cheat to get away from the bigger issue with the overall thesis. In this way, the idea in this blog just feels so out of touch.
> Let’s say every company gets about three innovation tokens. You can spend these however you want, but the supply is fixed for a long while.
This is one of my favorite blog posts, and it can basically be encapsulated in the idea of "innovation tokens." It is one of the most useful concepts I have had as a PM / eng leader in my career. It helps actually make the the right tradeoffs, and helps even more in explaining those tradeoffs to colleague of all levels. Highly recommend.
There was another, much older, post similar to this about, I think, "beans" that engineers use to solve problems. If I remember correctly, it was something like, solving a problem costs "beans", and engineers will always use most all of their "beans" to solve a given problem, because it's somewhat "easy" until you run out of them.
Maybe it wasn't beans? But, I've been looking for it for years.
This is where efficiency can be applied in two distinct ways. On the one hand, if using more beans means you can solve the problem more quickly, then it is more efficient to the problem solver to do so.
But if beans are scarce, and that's where you can try to find ways to use less beans per function, then the goal is to make the function more efficient by using less beans.
His example of a web crawler stinks. I can get behind the philosophy, but his specific web crawler example at a minimum needs to retry, respect robots.txt, and rate limit per domain. So no, xargs + curl is a dumb example.
I love this post. It’s also interesting to revisit in the age of agents.
Using the language of the article, I’d say “push all your innovation tokens into agents” is probably a good move. This means the tech your agents work with should all be boring tech.
Another way of saying this is “use in-distribution technology”. If agents are substantially better at Rust than Zig, probably you should use Rust, even if Zig is “better”. The amount that Zig is better is going to get swamped by the amount that in-distribution agents are better.
(This is not a claim that Rust actually is better, just a hypothetical fact pattern for discussion.)
It's a total tangent but AI being so good at developing rust means that my first impression of seeing a rust project has totally changed.
4 or 5 years ago if I had to weigh up two options and one was written in rust it was almost a sure thing that the program was snappy, fast, reliable and that the author was competant.
Now it's a sure fire sign that the project was probably vibe coded. Not saying it can't still be good, I just have a different first impression now
One thing I learned about AI is that, e.g., if you're making websites you're much better off going for php/ruby/elixir, even if you don't like the languages much.
Pipelines and deploys gets much easier and faster than the very common TypeScript monorepo, and so does communication between server and client.
And I say that as a TypeScript and Effect aficionado who has no particular love for neither php or ruby, but they are extremely solid choices to move fast, well, and get excellent performance and tooling out of the box.
Great point! I'd also add that Django's another solid choice for boring tech that LLM agents will know very well and will very likely continue to do so. A fair bit of SWE Bench and other Python benchmarks are Django related tests, which the LLM vendors care very deeply about keeping their scores up. Also, Django's docs are excellent, so strategically pointing an LLM to them in a prompt can often produce great results.
PHP has had a lot of conventions so the training data is all over the place. Ruby is a nightmare in that regard. Can't speak to Elixir but I'm surprised to hear someone say LLMs producing good code in either language.
On the other hand, Go code from 2012 and Go code from 2026 looks virtually the same. Conventions are respected, go fmt is the one single formatter, "use the stdlib" is a popular mantra and the code is readable by design.
If I were to codegen a project I wouldn't use anything but Go at this point.
Is that what's happening in this example, though? Ditching TypeScript in favor of PHP seems to be a net positive in favor of having a reliable, performant tech stack. From certain perspectives, TypeScript is itself a form of technical debt: writing code in one language just to transpile it into another interpreted language just to add type safety to correct for human error seems like a heavy layer of complexity just to make development teams work faster.
If we get to the point where AI tools are able to consistently able to produce desired results within strict performance and security constraints, without having to make the same tradeoff between delivery velocity and final quality, why would we not have them target the lowest level feasible for implementation, and cut out all of the middleware cruft that makes everything slow and take up ten times the RAM it actually needs to?
I disagree. We've been doing this for two decades already. A lot of monoliths were rewritten in a way that best fit the AWS pricing model of the time with the software itself seemingly being an after afterthought. (I'm not here to discuss whether monoliths or micro services are better, I'm just saying the choice of how they were rewritten was too often mostly for AWS pricing)
I think you're completely misreading what I wrote.
PHP (lets use this as an example) brings already many benefits over a common solution like a TypeScript monorepo mostly operational simplicity. That was already true before AI.
It's boring, very fast and easy to deploy, offers straightforward horizontal scaling, no need to orchestrate containers and/or multiple runtime processes, has excellent html rendering (nothing in JS-land really does), and has very solid framework solutions like Laravel where everything works out of the box.
Those merits existed before AI already.
The issue was that you had to buy into PHP as a language, which was a horrible experience.
But if AI writes most of the code? Suddenly PHP becomes an excellent candidate to choose for many use cases.
If anything, AI makes the choice of programming and languages and software about finding the right tool for the job. Somehow the industry instead keeps vomiting React/Tailwind slop which are the right tool for 1% of the jobs.
I'm reminded of my father in law, who when asked what superpower he'd want, it was flight, so he could get to work without waiting in traffic.
If all of your employees are AI's, clarity of vision trumps choosing boring. And if you're having boring visions... well the world is already full of competition for you, so good luck I guess.
It's bad for building your resume. Managers and employees are rewarded for popular thing. Popularity is mostly a function of novelty. So the (social and therefore economic) incentive structure is inversely correlated with choosing boring technology.
Try to explain that part of an imagined "Agentic AI Everything" product being built would be cheaper and more efficient as a simple function call. Good luck!
Software that works year-after-year has never been a commodity. It's boring on the surface. It doesn't get the flashy posts. But I'll choose reliable over new in almost all cases.
Some of this may have been a reaction to the era of Javascript framework churn. There were way too many different technologies for doing roughly the same job.
They all more or less worked.
On the other hand, IBM was late getting into integrated circuits. They had Solid Logic Technology, automated machinery for putting transistors into ceramic substrates to make tiny but discrete circuits. That's what powered the IBM System/360. Worked, but kept mainframe prices high and made IBM late to minicomputers.
Innovation when the problem is hard is more interesting. Look at the history of US long range bombers. The B-29 was effective, but underpowered, and had a lot of trouble getting off the ground fully loaded. So, after WWII, the next development was the B-36, which answered the question "what if we scaled up the B-29?"[1] Six propellers, and four jet engines (added late in the design cycle). Was a sky barge, but it worked, as long as no one was trying hard to shoot it down. No flyable aircraft remain. That was the boring technology approach.
After that came the B-47, which answered the question "what if we scaled up a jet fighter to bomber size?"[2] The B-47 was all jets, no props. It needed solid-fuel rocket boosters (!) to help it get off the ground, and a drag chute to slow it down on landing. It was terrible to fly; its operating speed and altitude were too near the "coffin corner" where stall and Mach buffet meet.[3] No flyable aircraft remain.
Then came the B-52. New engines. New airframe. New design. [4] That's the high-risk approach. It worked. Hundreds are still in active service. Outlasted most of its successors, the B-58 Hustler (a supersonic intercontinental bomber), the B-70, the F-111, etc.
On the commercial side, we have Boeing, whose most successful airliner is a variant of the B-737, which first flew in 1967. But that's another story.
I'll push back against this, despite it being so popular. I dislike the arbitrary "innovation tokens" and I think this entire concept really blurs the lines and feels sort of unserious.
Engineers should understand requirements, risks, tradeoffs, and potential gains. New technology may be right for that. Novel approaches may be right for that. "Novel" or "New" are only proxies and they're weak.
For example, I may think "New" means untested, but is that true? What if a new project has Jepsen testing, a fuzzing suite, massive compute running tons of oracle tests, etc? I should just say "Choose well tested" instead of "Choose old" - lots of old software is very poorly tested.
Maybe I think that "Old" implies better documentation, but does it? Lots of older projects have insane cruft and weird edge cases that are undocumented and accumulated over years.
Why do we need a metaphor? Why is "innovation token" helpful?
If you're incapable of evaluating a technology in terms of these properties, you aren't a serious developer and "boring" will not save you.
Sit down, write our your requirements, determine candidate solutions, and choose them based on their fit. "Boring" means nothing, it's a vague proxy term. "Well tsted", "performant for our use case", "developers know it", etc mean something.
> MySQL is boring. Postgres is boring. PHP is boring. Python is boring. Memcached is boring. Squid is boring. Cron is boring.
Literally every one of these has caused hilarious and disastrous failures for me in my career. But yep, boring.
> If you choose to write your website in NodeJS, you just spent one of your innovation tokens. If you choose to use MongoDB, you just spent one of your innovation tokens.
What if you know NodeJS really well? Or MongoDb? What if you have empirical, verifiable reasons for why they fit better?
I'm a bit tired of "simple" and "boring" and other nonsense words in this field taking up the air in the room that should be spent evaluating solutions on their actual merits.
I don't think that context is relevant to my comment. I didn't say "in hindsight, those technologies are great!", I pointed out that "boring" is meaningless, and any meaning you attribute to it like "defined as the tech you know the sharp edges of" is better substituted in.
That is, if someone said two sentences, I would only care about the second one:
1. "We should use this because it is boring"
2. "We should use this because we understand the sharp edges"
I wouldn't care at all about (1) and I'd have a real conversation based on (2).
Any productive conversation that starts with (1) immediately has to follow "can you clarify what that means", so the term is useless at best and thought terminating at worst.
Isn't this somewhat semantical? Boring implies a lot of the things you said, especially if it means your team's experience is largely pooled in a particular dev environment. Assuming most boring tech is ubiquitous, it's probably rare that your team, statistically, is deeply literate in some obscure tech - they most likely are experts in some definition of "boring".
TLDR; #1 and #2 are essentially implying the same thing.
I see innovation as a guardrail against CV driven development. More, I think you need to consider the context of when this was written. It was a period of rapid innovation/evolution - I remember more than a handful of projects failing (either undelivered or rewritten well under their expected lifecycle) around this time because teams had taken bets on new tech either they didn't know how to use well or the tech didn't take off and was a dead end.
> What if you know NodeJS really well?
Then you consider it boring. I'm sure Node and MongoDB were singled out by the author because at the time of writing they were still relatively new and undergoing periods of rapid development and change.
CV driven development is just as well guarded against by asking someone to justify their technical decisions based on the requirements and how the solution meets them. So "boring" does nothing to further that.
> More, I think you need to consider the context of when this was written. It was a period of rapid innovation/evolution
It's linked today, people feel it's relevant today. This isn't a historic piece about how the tech industry used to be, people reference this post today.
> around this time because teams had taken bets on new tech either they didn't know how to use well or the tech didn't take off and was a dead end.
Yes, they should have had a discussion about their requirements and which technologies would have solved them.
> Then you consider it boring.
Then "boring" is useless and you should just say "I know this technology well and it maps to our use case well" and be able to justify that.
I don't agree with the article though and I dislike the influence it has had. I have seen engineers use "Boring" to justify "I know this technology" for situations where that technology is a bad fit.
Conversations about technical solutions are bespoke, there is no one term that can or should be used to guide them.
Poor choices whether influenced by this article or engineers chasing CV points are no different. Boring technology is a tool or communication device like any other. I hope in your situation you were able to influence the engineers utilising it poorly to reconsider.
> That's quite hard to do for solutions that you don't know the details.
That's a great thing to discuss when deciding on the technology. Maybe you should aim for solutions that you know well, or a solution that makes migrating away easy, or maybe you need to do some discovery work, etc.
> You have an objection to something. It's clearly not to the article's point, though.
It's an objection to the nature of the article itself - that technical decisions should work this way, that metaphors like "innovation tokens" are useful, that "boring" is a good proxy word.
Well your points are making sense in isolation whereas this article is making more sense in general.
> I'm a bit tired of "simple" and "boring" and other nonsense words in this field...
This is hilarious in sense millions more will be tired and exhausted by evaluating new and exciting technology endlessly appearing all the time.
People go by these rule of thumbs which may not be perfect in every single case but they do increase success chances for even sub-par teams as opposed to "rigorously evaluating latest technology"
I don't think it's exhausting to determine if a solution fits your requirements and I don't think much about the people who would find it exhausting. I'm not suggesting some insane formal verification, but you really can't just answer basic questions about how technologies can address problems? Then what is your role? To choose mysql irrespective of requirements?
> People go by these rule of thumbs which may not be perfect in every single case but they do increase success chances for even sub-par teams as opposed to "rigorously evaluating latest technology"
Rule of thumb. And it's not a rule. It's a bias based on a vague term.
Well mysql likely will turnout to be better choice than choosing "Cloud scale nosql DBs" when evaluators have rather limited hands-on knowledge about either of them.
> Well mysql likely will turnout to be better choice than choosing "Cloud scale nosql DBs" when evaluators have rather limited hands-on knowledge about either of them.
Obviously a straw-man, but also... justify it then? That's the point. You should be able to justify your position. "Cloud scale nosql db" doesn't tell me why you shouldn't choose it.
If it's understood then it's pointless. I also reject that it's understood.
I have no idea why you're talking about Prinicipia Mathematica as if I'm advocating for some sort of formal verification or extraordinary rigor as opposed to my suggestion that people just use their words and have reasons behind their decisions.
Then it's useless. If I have to take the context into account then I should be prepared to have a conversation about the requirements and how the technology fits it, which "boring" does not facilitate (and discourages).
Weird take. It's clearly useful as a communication tool. You talk to your team, you say "Let's use boring technology. Read the essay, then we can discuss what boring technology means to us first."
I obviously don't agree that it's useful as a communication tool though. Why not "Use the technology that's appropriate for our use case"? That seems radically better and doesn't suffer from weird misinterpretations or vague terms.
Because people LOVE COMING UP with excuses to try a new technology under the basis that "this is appropriate for our use-case", and if you don't introduce a concept similar to innovation tokens you may find that six months later your project is combining three different unproven new technologies and doesn't actually work yet.
Encouraging your team to be selective in where they place their new bets - and use "boring" aka already-understood technology for the bits that are not going to help solve unique problems - can help avoid expensive mistakes.
nawh. 50x node modules, typescript out the wazoo, all the state in the client (where you can't see it in prod), the most over-complicated UI, paired with async callback spaghetti is what you do these days.
We're "scalable" over here. It's a sexy problem to have.
Excellent post. Now, somewhat outdated, and in other ways, more relevant than ever. To whom it may concern: if you need a database, always choose postgresql.
I read a similar blog post years ago about restricting the technologies you use, and making do with a slightly worse option if it means reusing the stack you already have.
The example they gave was something like they wanted to use rabbitmq for a new side project (I might be misremembering) but they were forced to make it work with redis instead. The author said that years later he found out that that side project had exploded in popularity and it had coped with it fine because the infra team were already handling the stack and it wasn't some snowflake deployment.
> A good example of this from my experience is Etsy’s activity feeds. When we built this feature, we were working pretty hard to consolidate most of Etsy onto PHP, MySQL, Memcached, and Gearman (a PHP job server). It was much more complicated to implement the feature on that stack than it might have been with something like Redis (or maybe not). But it is absolutely possible to build activity feeds on that stack.
> An amazing thing happened with that project: our attention turned elsewhere for several years. During that time, activity feeds scaled up 20x while nobody was watching it at all. We made no changes whatsoever specifically targeted at activity feeds, but everything worked out fine as usage exploded because we were using a shared platform. This is the long-term benefit of restraint in technology choices in a nutshell.
I can't believe I was asking about the same article. The flow of time made it feel different and I forgot this was one of my all time favourites that I've been trying to re-find for years. Thank you
i just did an AI hackathon and 90% of the submissions were written in TypeScript and Next.js which is mostly due to the training data. AI is skewed to use these tools by default vs the best for the job.
The problem with this is that the list of tech that gets boring changes all time, faster than people's opinions. Kubernetes is very boring tech, but if you go through the old discussion threads on this (even from the last year or two), Kubernetes is still cited as some brand new wizbang thing you shouldn't spend tokens on.
Lol. In 2015 boring technology is at the hands of your PM spinning up some agent spam. Bury this pile of outdated thinking. Go hard at the most difficult programming you can find or go home.
This is one of my favorite blog posts, and it can basically be encapsulated in the idea of "innovation tokens." It is one of the most useful concepts I have had as a PM / eng leader in my career. It helps actually make the the right tradeoffs, and helps even more in explaining those tradeoffs to colleague of all levels. Highly recommend.
Maybe it wasn't beans? But, I've been looking for it for years.
But if beans are scarce, and that's where you can try to find ways to use less beans per function, then the goal is to make the function more efficient by using less beans.
[0] https://widgetsandshit.com/teddziuba/2010/10/taco-bell-progr...
Using the language of the article, I’d say “push all your innovation tokens into agents” is probably a good move. This means the tech your agents work with should all be boring tech.
Another way of saying this is “use in-distribution technology”. If agents are substantially better at Rust than Zig, probably you should use Rust, even if Zig is “better”. The amount that Zig is better is going to get swamped by the amount that in-distribution agents are better.
(This is not a claim that Rust actually is better, just a hypothetical fact pattern for discussion.)
4 or 5 years ago if I had to weigh up two options and one was written in rust it was almost a sure thing that the program was snappy, fast, reliable and that the author was competant.
Now it's a sure fire sign that the project was probably vibe coded. Not saying it can't still be good, I just have a different first impression now
Pipelines and deploys gets much easier and faster than the very common TypeScript monorepo, and so does communication between server and client.
And I say that as a TypeScript and Effect aficionado who has no particular love for neither php or ruby, but they are extremely solid choices to move fast, well, and get excellent performance and tooling out of the box.
On the other hand, Go code from 2012 and Go code from 2026 looks virtually the same. Conventions are respected, go fmt is the one single formatter, "use the stdlib" is a popular mantra and the code is readable by design.
If I were to codegen a project I wouldn't use anything but Go at this point.
If we get to the point where AI tools are able to consistently able to produce desired results within strict performance and security constraints, without having to make the same tradeoff between delivery velocity and final quality, why would we not have them target the lowest level feasible for implementation, and cut out all of the middleware cruft that makes everything slow and take up ten times the RAM it actually needs to?
PHP (lets use this as an example) brings already many benefits over a common solution like a TypeScript monorepo mostly operational simplicity. That was already true before AI.
It's boring, very fast and easy to deploy, offers straightforward horizontal scaling, no need to orchestrate containers and/or multiple runtime processes, has excellent html rendering (nothing in JS-land really does), and has very solid framework solutions like Laravel where everything works out of the box.
Those merits existed before AI already.
The issue was that you had to buy into PHP as a language, which was a horrible experience.
But if AI writes most of the code? Suddenly PHP becomes an excellent candidate to choose for many use cases.
If anything, AI makes the choice of programming and languages and software about finding the right tool for the job. Somehow the industry instead keeps vomiting React/Tailwind slop which are the right tool for 1% of the jobs.
I hope to have cleared the concept.
If all of your employees are AI's, clarity of vision trumps choosing boring. And if you're having boring visions... well the world is already full of competition for you, so good luck I guess.
I've found it extremely useful over the years, personally.
On the other hand, IBM was late getting into integrated circuits. They had Solid Logic Technology, automated machinery for putting transistors into ceramic substrates to make tiny but discrete circuits. That's what powered the IBM System/360. Worked, but kept mainframe prices high and made IBM late to minicomputers.
Innovation when the problem is hard is more interesting. Look at the history of US long range bombers. The B-29 was effective, but underpowered, and had a lot of trouble getting off the ground fully loaded. So, after WWII, the next development was the B-36, which answered the question "what if we scaled up the B-29?"[1] Six propellers, and four jet engines (added late in the design cycle). Was a sky barge, but it worked, as long as no one was trying hard to shoot it down. No flyable aircraft remain. That was the boring technology approach.
After that came the B-47, which answered the question "what if we scaled up a jet fighter to bomber size?"[2] The B-47 was all jets, no props. It needed solid-fuel rocket boosters (!) to help it get off the ground, and a drag chute to slow it down on landing. It was terrible to fly; its operating speed and altitude were too near the "coffin corner" where stall and Mach buffet meet.[3] No flyable aircraft remain.
Then came the B-52. New engines. New airframe. New design. [4] That's the high-risk approach. It worked. Hundreds are still in active service. Outlasted most of its successors, the B-58 Hustler (a supersonic intercontinental bomber), the B-70, the F-111, etc.
On the commercial side, we have Boeing, whose most successful airliner is a variant of the B-737, which first flew in 1967. But that's another story.
[1] https://www.youtube.com/watch?v=vKQYG_fA2uM
[2] https://www.youtube.com/watch?v=l1-urTRxeEM
[3] https://en.wikipedia.org/wiki/Coffin_corner_%28aerodynamics%...
[4] https://www.youtube.com/watch?v=k8EURBL53_k
Engineers should understand requirements, risks, tradeoffs, and potential gains. New technology may be right for that. Novel approaches may be right for that. "Novel" or "New" are only proxies and they're weak.
For example, I may think "New" means untested, but is that true? What if a new project has Jepsen testing, a fuzzing suite, massive compute running tons of oracle tests, etc? I should just say "Choose well tested" instead of "Choose old" - lots of old software is very poorly tested.
Maybe I think that "Old" implies better documentation, but does it? Lots of older projects have insane cruft and weird edge cases that are undocumented and accumulated over years.
Why do we need a metaphor? Why is "innovation token" helpful?
If you're incapable of evaluating a technology in terms of these properties, you aren't a serious developer and "boring" will not save you.
Sit down, write our your requirements, determine candidate solutions, and choose them based on their fit. "Boring" means nothing, it's a vague proxy term. "Well tsted", "performant for our use case", "developers know it", etc mean something.
> MySQL is boring. Postgres is boring. PHP is boring. Python is boring. Memcached is boring. Squid is boring. Cron is boring.
Literally every one of these has caused hilarious and disastrous failures for me in my career. But yep, boring.
> If you choose to write your website in NodeJS, you just spent one of your innovation tokens. If you choose to use MongoDB, you just spent one of your innovation tokens.
What if you know NodeJS really well? Or MongoDb? What if you have empirical, verifiable reasons for why they fit better?
I'm a bit tired of "simple" and "boring" and other nonsense words in this field taking up the air in the room that should be spent evaluating solutions on their actual merits.
So yes, pick boring tech, defined as the tech you know the sharp edges of.
That is, if someone said two sentences, I would only care about the second one:
1. "We should use this because it is boring"
2. "We should use this because we understand the sharp edges"
I wouldn't care at all about (1) and I'd have a real conversation based on (2).
Any productive conversation that starts with (1) immediately has to follow "can you clarify what that means", so the term is useless at best and thought terminating at worst.
TLDR; #1 and #2 are essentially implying the same thing.
> What if you know NodeJS really well?
Then you consider it boring. I'm sure Node and MongoDB were singled out by the author because at the time of writing they were still relatively new and undergoing periods of rapid development and change.
> More, I think you need to consider the context of when this was written. It was a period of rapid innovation/evolution
It's linked today, people feel it's relevant today. This isn't a historic piece about how the tech industry used to be, people reference this post today.
> around this time because teams had taken bets on new tech either they didn't know how to use well or the tech didn't take off and was a dead end.
Yes, they should have had a discussion about their requirements and which technologies would have solved them.
> Then you consider it boring.
Then "boring" is useless and you should just say "I know this technology well and it maps to our use case well" and be able to justify that.
However, it's influenced a lot of people for more than a decade and the snippy title might well have something to do with that.
Conversations about technical solutions are bespoke, there is no one term that can or should be used to guide them.
The article answers this, and the answer is "no". New technology is one you don't know the details of.
> determine candidate solutions, and choose them based on their fit
That's quite hard to do for solutions that you don't know the details.
You have an objection to something. It's clearly not to the article's point, though.
That's a great thing to discuss when deciding on the technology. Maybe you should aim for solutions that you know well, or a solution that makes migrating away easy, or maybe you need to do some discovery work, etc.
> You have an objection to something. It's clearly not to the article's point, though.
It's an objection to the nature of the article itself - that technical decisions should work this way, that metaphors like "innovation tokens" are useful, that "boring" is a good proxy word.
> I'm a bit tired of "simple" and "boring" and other nonsense words in this field...
This is hilarious in sense millions more will be tired and exhausted by evaluating new and exciting technology endlessly appearing all the time.
People go by these rule of thumbs which may not be perfect in every single case but they do increase success chances for even sub-par teams as opposed to "rigorously evaluating latest technology"
> People go by these rule of thumbs which may not be perfect in every single case but they do increase success chances for even sub-par teams as opposed to "rigorously evaluating latest technology"
Rule of thumb. And it's not a rule. It's a bias based on a vague term.
Obviously a straw-man, but also... justify it then? That's the point. You should be able to justify your position. "Cloud scale nosql db" doesn't tell me why you shouldn't choose it.
I have no idea why you're talking about Prinicipia Mathematica as if I'm advocating for some sort of formal verification or extraordinary rigor as opposed to my suggestion that people just use their words and have reasons behind their decisions.
Then they're not boring. Boring isn't a universal trait, it has to be evaluated within the context of your own team.
Encouraging your team to be selective in where they place their new bets - and use "boring" aka already-understood technology for the bits that are not going to help solve unique problems - can help avoid expensive mistakes.
We're "scalable" over here. It's a sexy problem to have.
Sadly, that is real out-of-the-box thinking.
The example they gave was something like they wanted to use rabbitmq for a new side project (I might be misremembering) but they were forced to make it work with redis instead. The author said that years later he found out that that side project had exploded in popularity and it had coped with it fine because the infra team were already handling the stack and it wasn't some snowflake deployment.
Does anyone remember the post I'm talking about?
> A good example of this from my experience is Etsy’s activity feeds. When we built this feature, we were working pretty hard to consolidate most of Etsy onto PHP, MySQL, Memcached, and Gearman (a PHP job server). It was much more complicated to implement the feature on that stack than it might have been with something like Redis (or maybe not). But it is absolutely possible to build activity feeds on that stack.
> An amazing thing happened with that project: our attention turned elsewhere for several years. During that time, activity feeds scaled up 20x while nobody was watching it at all. We made no changes whatsoever specifically targeted at activity feeds, but everything worked out fine as usage exploded because we were using a shared platform. This is the long-term benefit of restraint in technology choices in a nutshell.
Don't let one affect the other.
edit: Node is boring, as far as the frontend goes -- a notoriously unstable ecosystem.