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What I don't understand about this whole "get on board the AI train or get left behind" narrative, what advantage does an early adopter have for AI tools? The

What I don't understand about this whole "get on board the AI train or get left behind" narrative, what advantage does an early adopter have for AI tools? The way I see it, I can just start using AI once they get good enough for my type of work. Until then I'm continuing to learn instead of letting my brain atrophy.

Ekaros 8mo ago
By their promises it should get so good that basically you do not need to learn it. So it is reasonable to wait until that point.
- dkdcio 8mo ago
  this is a straw man, nobody serious is promising that. it is a skill like any other that requires learning
  - Ekaros 8mo ago
    OpenAI is going to get to AGI. And AGI should in minutes build a system that takes vague input and produces fully functioning product out of it. Isn't singularity being promised by them?
    - dkdcio 8mo ago
      you’re just repeating the straw man. if you can’t think critically and just regurgitate every dumb thing you hear idk what to tell you. nobody serious thinks a “singularity” is coming. there’s not even a proper definition of “AGI” your argument amounts to “some people said stupid shit one time and I took it seriously”
  - robot-wrangler 8mo ago
    I agree about skills actually, but it's also obvious that parent is making a very real point that you cannot just dismiss. For several years now and far short of wild AGI promises, the answer to literally every issue with casual or production AI has been something like "but the rate of model improvement.." or "but the tools and ecosystem will evolve.." If you believe that uncritically about everything else, then you have to answer why agentic workflows or MCP or whatever is the one thing that it can't evolve to do for us. There's a logical contradiction here where you really can't have it both ways.
    - dkdcio 8mo ago
      I’m not understanding your point… (and would be genuinely curious to)? the models and systems around them have evolved and gotten better (over the past few years for LLMs and decades for “AI” more broadly) oh I think I do get your point now after a few rereads (correct if wrong but you’re saying it should keep getting better until there’s nothing for us to do). “AI”, and computer systems more broadly, are not and cannot be viable systems. they don’t have agency (ironically) to affect change in their environment (without humans in the loop). computer systems don’t exist/survive without people. all the human concerns around what/why remain, AI is just another tool in a long line of computer systems that make our lives easier/more efficient
      - robot-wrangler 8mo ago
        AI Engineer to Software Engineer: Humans writing code is a waste of time, you can only hope to add value by designing agentic workflows Prompt Engineer to AI Engineer: Designing agentic workflows is a waste of time, just pre/postfix whatever input you'd normally give to the agentic system with the request to "build or simulate an appropriate agentic workflow for this problem"
  - fabianholzer 8mo ago
    > nobody serious is promising that There is a staggering number of unserious folks in the ears of people with corporate purchasing power.
  - sensanaty 8mo ago
    Nobody serious, like every single AI CEO out there? I mean I agree, nobody should be taking them seriously, yet we're fast on track for a global financial meltdown because of these fraudsters and their "non-serious" words.
- simonw 8mo ago
  If you listen to promises like that you're going get burned. One of the key skills needed in working with LLMs is learning to ignore the hype and marketing and figure out what these things are actually capable of, as opposed to LinkedIn bluster and claims from CEOs who's net worth are tied to investor sentiment in their companies. If someone spends more time talking about "AGI" then what they're actually building, filter that person out.
  - pydry 8mo ago
    >One of the key skills needed in working with LLMs is learning to ignore the hype and marketing and figure out what these things are actually capable of This is precisely what led me to realize that while they have some use for code review and analyzing docs, for coding purposes they are fairly useless. The hypesters responses' to this assertion exclusively into 5 categories. Ive never heard a 6th.
- theshrike79 8mo ago
  Do you always believe what the marketing people tell you? If so, I've got a JPEG of a monkey to sell you =)
edg5000 8mo ago
It took me a few months of working with the agents to get really productive with it. The gains are significant. I write highly detailed specs (equiv multiple A4 pages) in markdown and dicate the agent hierarchy (which agent does what, who reports to who). I've learned a lot of new things this year thanks to AI. It's true that the low levels skills with atrophy. The high level skills will grow though; my learning rate is the same, just at a much higher abstraction level; thus covering more subjects. The main concern is the centralisation. The value I can get out of this thing currently well exceeds my income. AI companies are buying up all the chips. I worry we'll get something like the housing market where AI will be about 50% of our income. We have to fight this centralisation at all costs!
- wmwragg 8mo ago
  This is something I think a lot of people don't seem to notice, or worry about, the moving of programming as a local task, to one that is controlled by big corporations, essentially turning programming into a subscription model, just like everything else, if you don't pay the subscription you will no longer be able to code i.e. PaaS (Programming as a Service). Obviously at the moment most programmers can still code without LLMs, but when autocomplete IDEs became main stream, it didn't take long before a large proportion of programmers couldn't program without an autocomplete IDE, I expect most new programmers coming in won't be able to "program" without a remote LLM.
  - Lio 8mo ago
    That ignores the possibility that local inference gets good enough to run without a subscription on reasonably priced hardware. I don't think that's too far away. Anthropic, OpenAI, etc. are pushing the idea that you need a subscription but if opensource tools get good enough they could easily become an expensive irrelivance.
    - flyinglizard 8mo ago
      My concern is that inference hardware is becoming more and more specialized and datacenter-only. It won’t be possible any longer to just throw in a beefy GPU (in fact we’re already past that point).
nikcub 8mo ago
I've used cursor and claude code both daily[0] within a month of their releases - i'm learning something new on how to work with and apply the tools almost every day. I don't think it's a coincidence that some of the best developers[1] are using these tools and some openly advocating for them because it still requires core skills to get the most out of them I can honestly say that building end-to-end products with claude code has made me a better developer, product designer, tester, code reviewer, systems architect, project manager, sysadmin etc. I've learned more in the past ~year than I ever have in my career. [0] abandoned cursor late last year [1] see Linus using antigravity, antirez in OP, Jared at bun, Charlie at uv/ruff, mitushiko, simonw et al
- dkdcio 8mo ago
  I started heavy usage in April 2025 (Codex CLI -> some Claude Code and trying other CLIs + a bit of Cursor -> Warp.dev -> Claude Code) and I’m still learning as well (and constantly trying to get more efficient) (I had been using GitHub Copilot for 5+ years already, started as an early beta tested, but I don’t really consider that the same) I like to say it’s like learning a programming language. it takes time, but you start pattern matching and knowing what works. it took me multiple attempts and a good amount of time to learn Rust, learning effective use of these tools is similar I’ve also learned a ton across domains I otherwise wouldn’t have touched
CuriouslyC 8mo ago
AI development is about planning, orchestration and high throughput validation. Those skills won't go away, the quality floor of model output will just rise over time.
bsaul 8mo ago
An ecosystem is being built around AI : Best prompting practices, mcps, skills, IDE integration, how to build a feedback loop so that LLM can test its output alone, plug to the outside world with browser extensions, etc... For now i think people can still catch up quickly, but at the end of 2026 it's probably going to be a different story.
- edg5000 8mo ago
  > probably going to be a different story Can you elaborate? Skill in AI use will be a differentiator?
  - epolanski 8mo ago
    Yes. At some point you will need to combine multiple skills together: - communication - engineering skills (understanding requirements, finding edge cases, etc) - architectural proficiency - prompting - agentic workflows and skills - context management - and yes, proper old fashioned coding skills to keep things tidy and consistent
- rvz 8mo ago
  > Best prompting practices, mcps, skills, IDE integration, how to build a feedback loop so that LLM can test its output alone, plug to the outside world with browser extensions, etc... Ah yes, an ecosystem that is fundamentally inherently built on probabilisitic quick sand and even with the "best prompting practices", you still get agents violating the basics of security and committing API keys when they were told not to. [0] [0] https://xcancel.com/valigo/status/2009764793251664279 https://xcancel.com/valigo/status/2009764793251664279
  - dkdcio 8mo ago
    I have tons of examples of AI not committing secrets. this is one screenshot from twitter? I don’t think it makes your point CPUs are billions of transistors. sometimes one fails and things still work. “probabilistic quicksand” isn’t the dig you think it is to people who know how this stuff works
rvz 8mo ago
> What I don't understand about this whole "get on board the AI train or get left behind" narrative, what advantage does an early adopter have for AI tools? The ones pushing this narrative have either the following: * Invested in AI companies (which they will never disclose until they IPO / acquired) * Employees at AI companies that have stock options which they are effectively paid boosters around AGI nonsense. * Mid-life crisis / paranoia that their identity as a programmer is being eroded and have to pivot to AI. It is no different to the crypto web3 bubble of 2021. This time, it is even more obvious and now the grifters from crypto / tech are already "pivoting to ai". [0] [0] https://pivot-to-ai.com/ https://pivot-to-ai.com/
- KaiserPro 8mo ago
  I'm not an AI booster, but I can't argue with Opus doing lots of legwork > It is no different to the crypto web3 bubble of 2021 web3 didn't produce anything useful, just noise. I couldn't take a web3 stack to make an arbitrary app. with the PISS machine I can. Do I worry about the future, fuck yeah I do. I think I'm up shit creek. I am lucky that I am good at describing in plain English what I want.
  - jeroenhd 8mo ago
    Web3 generated plenty of use if you're in on it. Pension funds, private investors, public companies, governments, gambling addicts, teenagers with more pocket money than sense, they've all moved billions into the pockets of Web3 grifters. You follow a tutorial on YouTube, spam the right places, maybe buy a few illegal ads, do a quick rugpull, and if you did your opsec right, you're now a millionaire. The major money sources have started to dry up (although the current American regime has been paid off by crypto companies so a Web3 revival might just happen). With AI companies still selling services far below cost, it's only a matter of time before the money runs out and the true value of these tools will be tested.
    - KaiserPro 8mo ago
      > Pension funds, private investors, public companies As someone who was at a large company that was dabbling in NFTs, there was no value apart from pure gambling. At the time that we were doing it, it was also too late, so it was just a jinormous My issue with GenAI is the rampant copyright violation, and the effect it will have on the economy. Its also replacing all of the fun bits of the world that I inhabit. At least with web3 it was mostly contained with in the BO infested basement that crypto bros inhabit. AI bollocks has infected half the world.
oncallthrow 8mo ago
My take: learning how to do LLM-assisted coding at a basic level gets you 80% of the returns, and takes about 30 minutes. It's a complete no-brainer. Learning all of the advanced multi-agent worklows etc. etc... Maybe that gets you an extra 20%, but it costs a lot more time, and is more likely to change over time anyway. So maybe not very good ROI.
- deleted 8mo ago
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- __MatrixMan__ 8mo ago
  It seems like you're mostly focused on the tooling for actually directing the LLM but there's a whole host of other technology which becomes relevant re: building guardrails and handcuffs for your agent. For instance I've been doing a lot of contract testing lately. It's not new tech, not changing at a blistering pace, but now that generating mountains of code is cheap, techniques for dealing with those mountains are suddenly more necessary.
- theshrike79 8mo ago
  1. Basic vanilla LLM Agentic coding 2. Build tools for the LLM, ones that are easy to use and don't spam stuff. Like give it tools to run tests that only return "Tests OK" if nothing failed, same with builds. 3. Look into /commands and Skills, both seem to be here to stay Maybe a weekend of messing about and you'll be pretty well off compared to the vast masses who still copy/paste code out of ChatGPT to their editor.
antirez 8mo ago
I think that who says that you need to be accustomed to the current "tools" related to AI agents, is suffering from a horizon effect issue: these stuff will change continuously for some time, and the more they evolve, the less you need to fiddle with the details. However, the skill you need to have, is communication skills. You need to be able to express yourself and what matters for your project fast and well. Many programmers are not great at communication. In part this is a gift, something you develop at small age, and this will, I believe, kinda change who is good at programming: good communicators / explorers may not have a edge VS very strong coders that are bad at explaining themselves. But a lot of it is attitude, IMHO. And practice.
- embedding-shape 8mo ago
  > Many programmers are not great at communication. This is true, but still shocking. Professional (working with others at least) developers basically live or die by their ability to communicate. If you're bad at communication, your entire team (and yourself) suffer, yet it seems like the "lone ranger" type of programmer is still somewhat praised and idealized. When trying to help some programmer friends with how they use LLMs, it becomes really clear how little they actually can communicate, and for some of them I'm slightly surprised they've been able to work with others at all. An example the other day, some friend complained that the LLM they worked with was using the wrong library, and using the wrong color for some element, and surprised that the LLM wouldn't know it from the get go. Reading through the prompt, they never mentioned it once, and when asked about it, they thought "it should have been obvious" which yeah, to someone like you who worked for 2 years on this project that might be obvious, but for some with zero history and zero context about what you do? How you expect it to know this? Baffling sometimes.
  - prodigycorp 8mo ago
    Yup. I'd take a gander than most complaints by people who have even used LLMs for long time can be resolved by "describe your thing in detail". LLM's are such a relief on my wrists that I often get tempted to write short prompts and pray that the LLM divines my thoughts. I always get much better results in a lot faster time when i just turn on the mic and have whisper transcribe a couple minutes of my speaking though.
zahlman 8mo ago
The idea, I think, is to gain experience with the loop of communicating ideas in natural language rather than code, and then reading the generated code and taking it as feedback. It's not that different overall, I suppose, from the loop of thinking of an idea and then implementing it and running tests; but potentially very disorienting for some.
deleted 8mo ago
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simonw 8mo ago
This is a pretty common position: "I don't worry about getting left behind - it will only take a few weeks to catch up again". I don't think that's true. I'm really good at getting great results out of coding agents and LLMs. I've also been using LLMs for code on an almost daily basis since ChatGPT's release on November 30th 2022. That's more than three years ago now. Meanwhile I see a constant flow of complaints from other developers who can't get anything useful out of these machines, or find that the gains they get are minimal at best. Using this stuff well is a deep topic. These things can be applied in so many different ways, and to so many different projects. The best asset you can develop is an intuition for what works and what doesn't, and getting that intuition requires months if not years of personal experimentation. I don't think you can just catch up in a few weeks, and I do think that the risk of falling behind isn't being taken seriously enough by much of the developer population. I'm glad to see people like antirez ringing the alarm bell about this - it's not going to be a popular position but it needs to be said!
- yeasku 8mo ago
  [dead]
- systemf_omega 8mo ago
  > Using this stuff well is a deep topic. Just like the stuff LLMs are being used for today. Why wouldn't "using LLMs well" be not just one of the many things LLMs will simplify too? Or do you believe your type of knowledge is somehow special and is resistant to being vastly simplified or even made obsolete by AI?
  - simonw 8mo ago
    An interesting trend over the past year is that LLMs have learned how to prompt each other. Back in ~2024 a lot of people were excited about having "LLMs write the prompt!" but I found the results to be really disappointing - they were full of things like "You are the world's best expert in marketing" which was superstitious junk. As of 2025 I'm finding they actually do know how to prompt, which makes sense because there's a ton more information about good prompting approaches in the training data as opposed to a couple of years ago. This has unlocked some very interesting patterns, such as Claude Code prompting sub-agents to help it explore codebases without polluting the top level token window. But learning to prompt is not the key skill in getting good results out of LLMs. The thing that matters most is having a robust model of what they can and cannot do. Asking an LLM "can you do X" is still the kind of thing I wouldn't trust them to answer in a useful way, because they're always constrained by training data that was only aware of their predecessors.
quitit 8mo ago
You're right, it's difficult to get "left behind" when the tools and workflows are being constantly reinvented. You'd be sage with your time just to keep a high-level view until workflows become stable and aren't advancing every few months. The time to consider mastering a workflow is when a casual user of the "next release" wouldn't trivially supersede your capabilities. Similarly we're still in the race to produce a "good enough" GenAI, so there isn't value in mastering anything right now unless you've already got a commercial need for it. This all reminds me of a time when people were putting in serious effort to learn Palm Pilot's Graffiti handwriting recognition, only for the skill to be made redundant even before they were proficient at it.
nicce 8mo ago
> What I don't understand about this whole "get on board the AI train or get left behind" narrative, what advantage does an early adopter have for AI tools? Replace that with anything and you will notice that people who are building startups in this area will want to bring the narrative like that as it usually highly increases the value of their companies. When narrative gets big enough, then big companies must follow - or they look like "lagging behind". Whether the current thing brings value or not. It is a fire that keeps feeding itself. In the end, when it gets big enough - we call it as bubble. Bubble that may explode. Or not. Whether the end user gets actual value or not, is just side effect. But everyone wants to believe that that it brings value - otherwise they were foolish to jump in the train.
_ea1k 8mo ago
I thought this way for a while. I still do to a certain degree, but I'm starting to see the wisdom in hurrying off into the change. The most advanced tooling today looks nothing like the tooling for writing software 3 years ago. We've got multi-agent orchestration with built in task and issue tracking, context management, and subagents now. There's a steep learning curve! I'm not saying that everyone has to do it, as the tools are so nascent, but I think it is worthwhile to at least start understanding what the state of the art will look like in 12-24 months.
epolanski 8mo ago
What would be the type of work you're doing where you wouldn't benefit from one or multiple of the following: - find information about APIs without needing to open a browser - writing a plan for your business-logic changes or having it reviewed - getting a review of your code to find edge cases, potential security issues, potential improvements - finding information and connecting the dots of where, what and why it works in some way in your code base? Even without letting AI author a single line of code (where it can still be super useful) there are still major uses for AI.
xboxnolifes 8mo ago
Early adopters get the advantage of only having to learn a trickle of new things every few weeks instead of everything all at once. Part of the problem with things that iterate quickly is that iterations tend to reference previous versions. So, you try learning the new hotness (v261), but there are implied references to v254, v239, and v198. Then you realize, v1, v5, v48, v87, v138, v192, and v230 have cute identifiers that you aren't familiar with and are never explained anywhere. New concepts get introduced in v25, v50, v102, and v156 that later became foundational knowledge that is assumed to be understood by the reader and is never explained anywhere. So, if you feel confident something will be the next hotness, it's usually best to be an early adopter, so you gain your knowledge slowly over years instead of having to cram when you need to pick it up.
__MatrixMan__ 8mo ago
You don't want a bit of influence over the design?
kahrl 8mo ago
When I think real hard about it, I can translate the bullshit speak. "get on board the AI train or get left behind" -> "BUY BUY BUY OUR SHIT! WE ARE SOOO OVER LEVERAGED WE ARE SO FUCKED. PLEASE CONSOOM"

Ekaros 8mo ago

By their promises it should get so good that basically you do not need to learn it. So it is reasonable to wait until that point.

dkdcio 8mo ago
this is a straw man, nobody serious is promising that. it is a skill like any other that requires learning
- Ekaros 8mo ago
  OpenAI is going to get to AGI. And AGI should in minutes build a system that takes vague input and produces fully functioning product out of it. Isn't singularity being promised by them?
  - dkdcio 8mo ago
    you’re just repeating the straw man. if you can’t think critically and just regurgitate every dumb thing you hear idk what to tell you. nobody serious thinks a “singularity” is coming. there’s not even a proper definition of “AGI” your argument amounts to “some people said stupid shit one time and I took it seriously”
- robot-wrangler 8mo ago
  I agree about skills actually, but it's also obvious that parent is making a very real point that you cannot just dismiss. For several years now and far short of wild AGI promises, the answer to literally every issue with casual or production AI has been something like "but the rate of model improvement.." or "but the tools and ecosystem will evolve.." If you believe that uncritically about everything else, then you have to answer why agentic workflows or MCP or whatever is the one thing that it can't evolve to do for us. There's a logical contradiction here where you really can't have it both ways.
  - dkdcio 8mo ago
    I’m not understanding your point… (and would be genuinely curious to)? the models and systems around them have evolved and gotten better (over the past few years for LLMs and decades for “AI” more broadly) oh I think I do get your point now after a few rereads (correct if wrong but you’re saying it should keep getting better until there’s nothing for us to do). “AI”, and computer systems more broadly, are not and cannot be viable systems. they don’t have agency (ironically) to affect change in their environment (without humans in the loop). computer systems don’t exist/survive without people. all the human concerns around what/why remain, AI is just another tool in a long line of computer systems that make our lives easier/more efficient
    - robot-wrangler 8mo ago
      AI Engineer to Software Engineer: Humans writing code is a waste of time, you can only hope to add value by designing agentic workflows Prompt Engineer to AI Engineer: Designing agentic workflows is a waste of time, just pre/postfix whatever input you'd normally give to the agentic system with the request to "build or simulate an appropriate agentic workflow for this problem"
- fabianholzer 8mo ago
  > nobody serious is promising that There is a staggering number of unserious folks in the ears of people with corporate purchasing power.
- sensanaty 8mo ago
  Nobody serious, like every single AI CEO out there? I mean I agree, nobody should be taking them seriously, yet we're fast on track for a global financial meltdown because of these fraudsters and their "non-serious" words.
simonw 8mo ago
If you listen to promises like that you're going get burned. One of the key skills needed in working with LLMs is learning to ignore the hype and marketing and figure out what these things are actually capable of, as opposed to LinkedIn bluster and claims from CEOs who's net worth are tied to investor sentiment in their companies. If someone spends more time talking about "AGI" then what they're actually building, filter that person out.
- pydry 8mo ago
  >One of the key skills needed in working with LLMs is learning to ignore the hype and marketing and figure out what these things are actually capable of This is precisely what led me to realize that while they have some use for code review and analyzing docs, for coding purposes they are fairly useless. The hypesters responses' to this assertion exclusively into 5 categories. Ive never heard a 6th.
theshrike79 8mo ago
Do you always believe what the marketing people tell you? If so, I've got a JPEG of a monkey to sell you =)

edg5000 8mo ago

It took me a few months of working with the agents to get really productive with it. The gains are significant. I write highly detailed specs (equiv multiple A4 pages) in markdown and dicate the agent hierarchy (which agent does what, who reports to who). I've learned a lot of new things this year thanks to AI. It's true that the low levels skills with atrophy. The high level skills will grow though; my learning rate is the same, just at a much higher abstraction level; thus covering more subjects. The main concern is the centralisation. The value I can get out of this thing currently well exceeds my income. AI companies are buying up all the chips. I worry we'll get something like the housing market where AI will be about 50% of our income. We have to fight this centralisation at all costs!

wmwragg 8mo ago
This is something I think a lot of people don't seem to notice, or worry about, the moving of programming as a local task, to one that is controlled by big corporations, essentially turning programming into a subscription model, just like everything else, if you don't pay the subscription you will no longer be able to code i.e. PaaS (Programming as a Service). Obviously at the moment most programmers can still code without LLMs, but when autocomplete IDEs became main stream, it didn't take long before a large proportion of programmers couldn't program without an autocomplete IDE, I expect most new programmers coming in won't be able to "program" without a remote LLM.
- Lio 8mo ago
  That ignores the possibility that local inference gets good enough to run without a subscription on reasonably priced hardware. I don't think that's too far away. Anthropic, OpenAI, etc. are pushing the idea that you need a subscription but if opensource tools get good enough they could easily become an expensive irrelivance.
  - flyinglizard 8mo ago
    My concern is that inference hardware is becoming more and more specialized and datacenter-only. It won’t be possible any longer to just throw in a beefy GPU (in fact we’re already past that point).

nikcub 8mo ago

I've used cursor and claude code both daily[0] within a month of their releases - i'm learning something new on how to work with and apply the tools almost every day. I don't think it's a coincidence that some of the best developers[1] are using these tools and some openly advocating for them because it still requires core skills to get the most out of them I can honestly say that building end-to-end products with claude code has made me a better developer, product designer, tester, code reviewer, systems architect, project manager, sysadmin etc. I've learned more in the past ~year than I ever have in my career. [0] abandoned cursor late last year [1] see Linus using antigravity, antirez in OP, Jared at bun, Charlie at uv/ruff, mitushiko, simonw et al

dkdcio 8mo ago
I started heavy usage in April 2025 (Codex CLI -> some Claude Code and trying other CLIs + a bit of Cursor -> Warp.dev -> Claude Code) and I’m still learning as well (and constantly trying to get more efficient) (I had been using GitHub Copilot for 5+ years already, started as an early beta tested, but I don’t really consider that the same) I like to say it’s like learning a programming language. it takes time, but you start pattern matching and knowing what works. it took me multiple attempts and a good amount of time to learn Rust, learning effective use of these tools is similar I’ve also learned a ton across domains I otherwise wouldn’t have touched

CuriouslyC 8mo ago

AI development is about planning, orchestration and high throughput validation. Those skills won't go away, the quality floor of model output will just rise over time.

bsaul 8mo ago

An ecosystem is being built around AI : Best prompting practices, mcps, skills, IDE integration, how to build a feedback loop so that LLM can test its output alone, plug to the outside world with browser extensions, etc... For now i think people can still catch up quickly, but at the end of 2026 it's probably going to be a different story.

edg5000 8mo ago
> probably going to be a different story Can you elaborate? Skill in AI use will be a differentiator?
- epolanski 8mo ago
  Yes. At some point you will need to combine multiple skills together: - communication - engineering skills (understanding requirements, finding edge cases, etc) - architectural proficiency - prompting - agentic workflows and skills - context management - and yes, proper old fashioned coding skills to keep things tidy and consistent
rvz 8mo ago
> Best prompting practices, mcps, skills, IDE integration, how to build a feedback loop so that LLM can test its output alone, plug to the outside world with browser extensions, etc... Ah yes, an ecosystem that is fundamentally inherently built on probabilisitic quick sand and even with the "best prompting practices", you still get agents violating the basics of security and committing API keys when they were told not to. [0] [0] https://xcancel.com/valigo/status/2009764793251664279 https://xcancel.com/valigo/status/2009764793251664279
- dkdcio 8mo ago
  I have tons of examples of AI not committing secrets. this is one screenshot from twitter? I don’t think it makes your point CPUs are billions of transistors. sometimes one fails and things still work. “probabilistic quicksand” isn’t the dig you think it is to people who know how this stuff works

rvz 8mo ago

> What I don't understand about this whole "get on board the AI train or get left behind" narrative, what advantage does an early adopter have for AI tools? The ones pushing this narrative have either the following: * Invested in AI companies (which they will never disclose until they IPO / acquired) * Employees at AI companies that have stock options which they are effectively paid boosters around AGI nonsense. * Mid-life crisis / paranoia that their identity as a programmer is being eroded and have to pivot to AI. It is no different to the crypto web3 bubble of 2021. This time, it is even more obvious and now the grifters from crypto / tech are already "pivoting to ai". [0] [0] https://pivot-to-ai.com/ https://pivot-to-ai.com/

KaiserPro 8mo ago
I'm not an AI booster, but I can't argue with Opus doing lots of legwork > It is no different to the crypto web3 bubble of 2021 web3 didn't produce anything useful, just noise. I couldn't take a web3 stack to make an arbitrary app. with the PISS machine I can. Do I worry about the future, fuck yeah I do. I think I'm up shit creek. I am lucky that I am good at describing in plain English what I want.
- jeroenhd 8mo ago
  Web3 generated plenty of use if you're in on it. Pension funds, private investors, public companies, governments, gambling addicts, teenagers with more pocket money than sense, they've all moved billions into the pockets of Web3 grifters. You follow a tutorial on YouTube, spam the right places, maybe buy a few illegal ads, do a quick rugpull, and if you did your opsec right, you're now a millionaire. The major money sources have started to dry up (although the current American regime has been paid off by crypto companies so a Web3 revival might just happen). With AI companies still selling services far below cost, it's only a matter of time before the money runs out and the true value of these tools will be tested.
  - KaiserPro 8mo ago
    > Pension funds, private investors, public companies As someone who was at a large company that was dabbling in NFTs, there was no value apart from pure gambling. At the time that we were doing it, it was also too late, so it was just a jinormous My issue with GenAI is the rampant copyright violation, and the effect it will have on the economy. Its also replacing all of the fun bits of the world that I inhabit. At least with web3 it was mostly contained with in the BO infested basement that crypto bros inhabit. AI bollocks has infected half the world.

oncallthrow 8mo ago

My take: learning how to do LLM-assisted coding at a basic level gets you 80% of the returns, and takes about 30 minutes. It's a complete no-brainer. Learning all of the advanced multi-agent worklows etc. etc... Maybe that gets you an extra 20%, but it costs a lot more time, and is more likely to change over time anyway. So maybe not very good ROI.

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__MatrixMan__ 8mo ago
It seems like you're mostly focused on the tooling for actually directing the LLM but there's a whole host of other technology which becomes relevant re: building guardrails and handcuffs for your agent. For instance I've been doing a lot of contract testing lately. It's not new tech, not changing at a blistering pace, but now that generating mountains of code is cheap, techniques for dealing with those mountains are suddenly more necessary.
theshrike79 8mo ago
1. Basic vanilla LLM Agentic coding 2. Build tools for the LLM, ones that are easy to use and don't spam stuff. Like give it tools to run tests that only return "Tests OK" if nothing failed, same with builds. 3. Look into /commands and Skills, both seem to be here to stay Maybe a weekend of messing about and you'll be pretty well off compared to the vast masses who still copy/paste code out of ChatGPT to their editor.

antirez 8mo ago

I think that who says that you need to be accustomed to the current "tools" related to AI agents, is suffering from a horizon effect issue: these stuff will change continuously for some time, and the more they evolve, the less you need to fiddle with the details. However, the skill you need to have, is communication skills. You need to be able to express yourself and what matters for your project fast and well. Many programmers are not great at communication. In part this is a gift, something you develop at small age, and this will, I believe, kinda change who is good at programming: good communicators / explorers may not have a edge VS very strong coders that are bad at explaining themselves. But a lot of it is attitude, IMHO. And practice.

embedding-shape 8mo ago
> Many programmers are not great at communication. This is true, but still shocking. Professional (working with others at least) developers basically live or die by their ability to communicate. If you're bad at communication, your entire team (and yourself) suffer, yet it seems like the "lone ranger" type of programmer is still somewhat praised and idealized. When trying to help some programmer friends with how they use LLMs, it becomes really clear how little they actually can communicate, and for some of them I'm slightly surprised they've been able to work with others at all. An example the other day, some friend complained that the LLM they worked with was using the wrong library, and using the wrong color for some element, and surprised that the LLM wouldn't know it from the get go. Reading through the prompt, they never mentioned it once, and when asked about it, they thought "it should have been obvious" which yeah, to someone like you who worked for 2 years on this project that might be obvious, but for some with zero history and zero context about what you do? How you expect it to know this? Baffling sometimes.
- prodigycorp 8mo ago
  Yup. I'd take a gander than most complaints by people who have even used LLMs for long time can be resolved by "describe your thing in detail". LLM's are such a relief on my wrists that I often get tempted to write short prompts and pray that the LLM divines my thoughts. I always get much better results in a lot faster time when i just turn on the mic and have whisper transcribe a couple minutes of my speaking though.

zahlman 8mo ago

The idea, I think, is to gain experience with the loop of communicating ideas in natural language rather than code, and then reading the generated code and taking it as feedback. It's not that different overall, I suppose, from the loop of thinking of an idea and then implementing it and running tests; but potentially very disorienting for some.

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simonw 8mo ago

This is a pretty common position: "I don't worry about getting left behind - it will only take a few weeks to catch up again". I don't think that's true. I'm really good at getting great results out of coding agents and LLMs. I've also been using LLMs for code on an almost daily basis since ChatGPT's release on November 30th 2022. That's more than three years ago now. Meanwhile I see a constant flow of complaints from other developers who can't get anything useful out of these machines, or find that the gains they get are minimal at best. Using this stuff well is a deep topic. These things can be applied in so many different ways, and to so many different projects. The best asset you can develop is an intuition for what works and what doesn't, and getting that intuition requires months if not years of personal experimentation. I don't think you can just catch up in a few weeks, and I do think that the risk of falling behind isn't being taken seriously enough by much of the developer population. I'm glad to see people like antirez ringing the alarm bell about this - it's not going to be a popular position but it needs to be said!

yeasku 8mo ago
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systemf_omega 8mo ago
> Using this stuff well is a deep topic. Just like the stuff LLMs are being used for today. Why wouldn't "using LLMs well" be not just one of the many things LLMs will simplify too? Or do you believe your type of knowledge is somehow special and is resistant to being vastly simplified or even made obsolete by AI?
- simonw 8mo ago
  An interesting trend over the past year is that LLMs have learned how to prompt each other. Back in ~2024 a lot of people were excited about having "LLMs write the prompt!" but I found the results to be really disappointing - they were full of things like "You are the world's best expert in marketing" which was superstitious junk. As of 2025 I'm finding they actually do know how to prompt, which makes sense because there's a ton more information about good prompting approaches in the training data as opposed to a couple of years ago. This has unlocked some very interesting patterns, such as Claude Code prompting sub-agents to help it explore codebases without polluting the top level token window. But learning to prompt is not the key skill in getting good results out of LLMs. The thing that matters most is having a robust model of what they can and cannot do. Asking an LLM "can you do X" is still the kind of thing I wouldn't trust them to answer in a useful way, because they're always constrained by training data that was only aware of their predecessors.

quitit 8mo ago

You're right, it's difficult to get "left behind" when the tools and workflows are being constantly reinvented. You'd be sage with your time just to keep a high-level view until workflows become stable and aren't advancing every few months. The time to consider mastering a workflow is when a casual user of the "next release" wouldn't trivially supersede your capabilities. Similarly we're still in the race to produce a "good enough" GenAI, so there isn't value in mastering anything right now unless you've already got a commercial need for it. This all reminds me of a time when people were putting in serious effort to learn Palm Pilot's Graffiti handwriting recognition, only for the skill to be made redundant even before they were proficient at it.

nicce 8mo ago

> What I don't understand about this whole "get on board the AI train or get left behind" narrative, what advantage does an early adopter have for AI tools? Replace that with anything and you will notice that people who are building startups in this area will want to bring the narrative like that as it usually highly increases the value of their companies. When narrative gets big enough, then big companies must follow - or they look like "lagging behind". Whether the current thing brings value or not. It is a fire that keeps feeding itself. In the end, when it gets big enough - we call it as bubble. Bubble that may explode. Or not. Whether the end user gets actual value or not, is just side effect. But everyone wants to believe that that it brings value - otherwise they were foolish to jump in the train.

_ea1k 8mo ago

I thought this way for a while. I still do to a certain degree, but I'm starting to see the wisdom in hurrying off into the change. The most advanced tooling today looks nothing like the tooling for writing software 3 years ago. We've got multi-agent orchestration with built in task and issue tracking, context management, and subagents now. There's a steep learning curve! I'm not saying that everyone has to do it, as the tools are so nascent, but I think it is worthwhile to at least start understanding what the state of the art will look like in 12-24 months.

epolanski 8mo ago

What would be the type of work you're doing where you wouldn't benefit from one or multiple of the following: - find information about APIs without needing to open a browser - writing a plan for your business-logic changes or having it reviewed - getting a review of your code to find edge cases, potential security issues, potential improvements - finding information and connecting the dots of where, what and why it works in some way in your code base? Even without letting AI author a single line of code (where it can still be super useful) there are still major uses for AI.

xboxnolifes 8mo ago

Early adopters get the advantage of only having to learn a trickle of new things every few weeks instead of everything all at once. Part of the problem with things that iterate quickly is that iterations tend to reference previous versions. So, you try learning the new hotness (v261), but there are implied references to v254, v239, and v198. Then you realize, v1, v5, v48, v87, v138, v192, and v230 have cute identifiers that you aren't familiar with and are never explained anywhere. New concepts get introduced in v25, v50, v102, and v156 that later became foundational knowledge that is assumed to be understood by the reader and is never explained anywhere. So, if you feel confident something will be the next hotness, it's usually best to be an early adopter, so you gain your knowledge slowly over years instead of having to cram when you need to pick it up.

__MatrixMan__ 8mo ago

You don't want a bit of influence over the design?

kahrl 8mo ago

When I think real hard about it, I can translate the bullshit speak. "get on board the AI train or get left behind" -> "BUY BUY BUY OUR SHIT! WE ARE SOOO OVER LEVERAGED WE ARE SO FUCKED. PLEASE CONSOOM"