461–470 of 478 posts
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The key words in the quote are "not everyone is aligned". It's not about execution ability.
The key words are “one hour”. So what if there is some mealy-mouthed preamble?
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The key words are “one hour”. So what if there is some mealy-mouthed preamble?
At big tech companies "were still finding alignment" is code for leadership not being able to make decisions and unblock execution.
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Your point is fair, but it rests on a major assumption I'd question: that the only limit lies with the user, and the tooling itself has none. What if it’s more like “you can’t squeeze blood from a stone”? That is, agentic coding may simply have no greater potential than what I've already tried. To be fair I haven't gone all the way in trying to make it work but, even if some minor workarounds exist, the full promise…
How can one judge potential without fully understanding or having used it to its full potential? I don’t think agentic programming is some promised land of instant code without bugs. It’s just a force multiplier for what you can do.
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Serious question - what kind of example would help at this point? Here are a sample of (IMO) extremely talented and well known developers who have expressed that agentic coding helps them: Antirez (creator of Reddit), DHH (creator of RoR), Linus (Creator of Linux), Steve Yegge, Simon Wilison. This is just randomly off the top of my head, you can find many more. None of them claim that agentic coding does a years' wor…
Those are some high profile (celebrity) developers. I wonder if they have measured their results? I believe that the perceived speed up of AI coding is often different from reality. The following paper backs this idea https://arxiv.org/abs/2507.09089 . Can you provide data that objects this view, based on these (celebrity) developers or otherwise?
This is a notoriously difficult thing to measure in a study. More relevantly though, IMO, it's not a small effect that might be difficult to notice - it's a huge, huge speedup.
How many developers have measured whether they are faster when programming in Python vs assembly? I doubt many have. And I doubt many have chosen Python over assembly because of any study that backs it up. But it's also not exactly a subtle difference - I'm fairly 99% of people will say that, in practice, it's obvious that Python is faster for programming than assembly.
I talked literally yesterday to a colleague who's a great senior dev, and he made a demo in an hour and a half that he says would've taken him two weeks to do without AI. This isn't a subtle, hard to measure difference. Of course this is in an area where AI coding shines (a new codebase for demo purposes) - but can we at least agree that in some things AI is clearly an order of magnitude speedup?
I think a critical point is how well one can communicate/delegate. I have a background with systems thinking and communication, so figuring out how to prompt for what I’m after was smooth.
I was also an early adopter of LLMs so there’s good muscle memory there.
It’s important to see AI tools as accelerators - not replacements or solvers. Still do test-driven development. Still maintain robust documentation. Good practices + AI is where the value is; not just throwing AI at things.
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To wrap this up, what I was trying to say is that the feeling of being faster may not align with the reality. Even for people that have a good understanding of the matter it may be difficult to estimate. So I would say be skeptical of claims like this and try to somehow quantize it in a way that matters for the tasks you do. This is something managers of software projects have been trying to tackling for a while now.…
So there seems to be an shared underestanding how difficult "measure your results" would be in this case, so could we also agree that asking someone: > I wonder if they have measured their results? [...] Can you provide data that objects this view, based on these (celebrity) developers or otherwise? isn't really fair? Because not even you or I really know how to do so in a fair and reasonable manner, unless we start…
I think in a small conversation like this, it's probably not entirely fair.
However, we're hearing similar things from much larger organisations who definitely have the resources to do studies like this, and yet there's very little decent work available.
In fact, lots of the time they are deliberately misleading people (25% of our code generated by AI being copilot/other autocomplete). Like, that 25% stat was probably true historically with JetBrains products and using any form of code generations (for protobufs et al) so it's wildly deceptive et al.
A principal engineer at Google posted on Twitter that Claude Code did in an hour what the team couldn’t do in a year. Two days later, after people freaked out, context was added. The team built multiple versions in that year, each had its trade offs. All that context was given to the AI and it was able to produce a “toy” version. I can only assume it had similar trade offs. https://xcancel.com/rakyll/status/200765974…
The LLM/AI tools are powerful and have a ton of use cases unlike technologies like crypto, but the hype train is running full steam and no one really knows where things will land over the next 5-10 years.
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At big tech companies "were still finding alignment" is code for leadership not being able to make decisions and unblock execution.
Dearest leadership not unblocking execution. What's that got to do with what we’re complaining about? Did Claude cure cancer (this is hyperbole) in one hour or not?
It really depends by what you mean by "it works". A retrospective of the last 6months. I've had great success coding infra (terraform). It at least 10x the generation of easily verifiable and tedious to write code. Results were audited to death as the client was highly regulated. Professional feature dev is hit and miss for sure, although getting better and better. We're nowhere near full agentic coding. However, by…
> I suddenly have the homelab of my dreams, all the ideas previously in the "too long to execute" category now get vibe coded while watching TV or doing other stuff. This is the true game changer. I have a large-ish NAS that's not very well organised (I'm trying, it's a consolidated mess of different sources from two deacades - at least they're all in the same place now) It was faster to ask Claude to write me a sear…
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> I suddenly have the homelab of my dreams, all the ideas previously in the "too long to execute" category now get vibe coded while watching TV or doing other stuff. This is the true game changer. I have a large-ish NAS that's not very well organised (I'm trying, it's a consolidated mess of different sources from two deacades - at least they're all in the same place now) It was faster to ask Claude to write me a sear…
This is exactly where LLMS shines, but when you get to a larger project,for me everything falls apart since most of the time the application gets way to complex because the LLM try to guess what you want. This is ok for small project but quite bad for larger ones.
It doesn’t need to guess if it has the tools and documentation available.