31–40 of 137 posts
edit: Apparently "choose boring technology" is just clickbait, and in fact the guy advocates for all the nuanced technology selection advocated here.... so errr, apparently he in fact is saying "don't chose boring technology" or something, whatever. I completely disagree with almost any blanket philosophy on technology. Don't choose boring technology. Choose technology that suits the context: * choose what you like f…
While I see how this makes sense, I don't like this. If most people follow this strategy, we will end up with utter stagnation, or even devolution. "Boring" technology also has many hidden costs - most importantly, opportunity costs of not having several times higher productivity due to the warts and quirks of the boring tools. Sure, with enough practice one can work around them but every backwards issue takes a good…
The talk doesn’t say to always choose boring technology. But you might think it does if you read three words and wrote a comment in response to them.
Edit: I kind of see what you mean now. My paragraph about hiring was somewhat tangential. I am sorry.
He writes all this philosophy and then concludes with using PostgreSQL instead of mongoDB or nodeJS (? I'm not sure how that was in the same category). PostgreSQL is the opposite of boring technology; I've been using it for over 10 years and am still discovering new and surprising features with new and surprising failure modes; PostgreSQL today is very different from PostgreSQL 10 years ago, but setting it up for tru…
Is boring technology even an option in high-velocity fields like ML/AI? I can pick boring databases and boring servers but when it comes to model architectures, model weights, GPUs, serving frameworks, etc. there's been such massive improvements lately that it doesn't feel like anything has settled enough to be "boring". If I need a language model, or an image classifier, or an ASR model, there are older options whic…
99.999...% of us don't work or seriously touch in AI in any way. At best you make an API call to something that might do some AI, but at that point its just another service. So for the vast majority of people doing dev work, boring choices are correct. I've had a lot of junior devs come to me with proposals for microservice architectures that can autoscale, be orchestrated, have 0 downtime with red/blue deployments,…
It allows you to use spot/ephemeral instances and scale down capacity to almost zero cost without any loss in availability.
Single server in the cloud is great for dev environments and if you don't care about uptime. But given that poor uptime is toxic for customer retention only incompetent businesses would deliberately not choose to use something better suited. Especially when it's so much cheaper.
Worst surprises generally comes from non verified expectations, and ends up to hard to workaround problems that becomes clear in hindsight «It never really worked that way».
You have better chances to avoid that with tech you are familiar with, but the only real way is to verify how the thing is built, and on what principles, confront that to your knowledge, and if it aligns you have greatly improved the chances of things going smoothly.
Since people are generally not rational and rarely do those checks, when working with a team, going with familiarity is the safe route.
Is boring technology even an option in high-velocity fields like ML/AI? I can pick boring databases and boring servers but when it comes to model architectures, model weights, GPUs, serving frameworks, etc. there's been such massive improvements lately that it doesn't feel like anything has settled enough to be "boring". If I need a language model, or an image classifier, or an ASR model, there are older options whic…
Yes. Use GBTs and off the shelf language models you don't train yourself.
ChatGPT costs serious money, is easy to integrate with and is great for specific, general tasks. But it hasn't been trained on recent datasets, can't take advantage of internal or custom datasets and has restrictions on how it can be used.
Also most companies will never allow exfiltration of sensitive data to a third party.
edit: Apparently "choose boring technology" is just clickbait, and in fact the guy advocates for all the nuanced technology selection advocated here.... so errr, apparently he in fact is saying "don't chose boring technology" or something, whatever. I completely disagree with almost any blanket philosophy on technology. Don't choose boring technology. Choose technology that suits the context: * choose what you like f…
You genuinely just agreed with the majority of the points made in this essay.
He writes all this philosophy and then concludes with using PostgreSQL instead of mongoDB or nodeJS (? I'm not sure how that was in the same category). PostgreSQL is the opposite of boring technology; I've been using it for over 10 years and am still discovering new and surprising features with new and surprising failure modes; PostgreSQL today is very different from PostgreSQL 10 years ago, but setting it up for tru…
PostgreSQL is absolutely boring technology. What makes it boring is: - people have been using it for decades, for all kinds of different things - this means that any problem you run into, someone else will have seen before - and will have talked about it online - you're not going to be using it to solve a class of problems that no one else has used it for before
Citus Data which people often recommended didn't exist prior to 2010 and may not exist next year now they've been acquired by Microsoft and conflict with their Azure business.
I've always found the "boring programmer" thing pretentiousness trying to disguise itself as humility.