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2x, not 10x: coding with LLMs in 2026

obryant.dev

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Re: 2x, not 10x: coding with LLMs in 2026

#81
post #3

Does a 60x speedup count? Are you still copying and pasting from chatgpt, because if so your definitely doing it wrong.

If 60x was a thing, we would see many fantastic products appearing on the market, every product would have improved or goten major new interesting features. Yet it hasn't really happened.

10x or 60x of very little is still not much. "Working programmers" unable to write FizzBuzz exist.

10x or 60x of a negative value is a 10-60x bigger problem than that initial negative value. We all regularly commit things that are actually net negative.

Finally, 10x or 60x more productivity channeled into yet another static site generator, CMS, or programming language doesn't really help in improving products or developing new interesting features.

In short: LLMs offer real productivity gains, but they are still tools, and they are very new, so we misuse them a lot, in various ways (not limited to examples above). Unless they replace programmers and can consistently produce better than average code (even if they fail catastrophically in a few cases), they won't fundamentally change programming. They did change a lot, but not enough to get the result you're describing.

Re: 2x, not 10x: coding with LLMs in 2026

#82

While I agree with the premise, I think this angle only applies on work one was going to do no matter what. The real power of these tools is that there are so many ideas people would like to try, but never have the time or motivation to pursue. So the comparison is not only "built with and without LLM" but "would you even build this if you didn't have the LLM?". The gap in productivity in this case is much more wide.

I think the ideas worth pursuing still require substantial time and motivation, even with LLMs. Otherwise you just end up with a half-baked sloppy artifact that nobody will ever use or study, for a net negative benefit to humanity.

Re: 2x, not 10x: coding with LLMs in 2026

#83
post #46
post #5

This reminds me of themes I recently saw in [Harness Engineering is not Enough: Why Software Factories Fail]( https://www.youtube.com/watch?v=Ib5GBkD555M ) (Warning: the last 3 slides seem like an advertisement). One thing I liked is how Dex has a little graphic he glossed over showing software development is - 25% planning & aligning with other teams - 25% coding - 25% testing/verifying - 25% code review/rework One…

AI is great because my job is a lot easier, but it produces some extremely crappy code that would've NEVER passed a code review 1 year ago. You could argue that it speeds up development by 5X or more, but then it slows down testing/verifying, code review, and in many cases it makes it impossible to review/rework by hand. I just do what I'm told at work but even though I'm sure I'm in the minority I'm extremely skepti…

> it produces some extremely crappy code that would've NEVER passed a code review 1 year ago

The 10x speed up comes from the fact that we have all given up on properly reviewing each others code and we just say “meh, it will be fine, lgtm”

Re: 2x, not 10x: coding with LLMs in 2026

#84

While I agree with the premise, I think this angle only applies on work one was going to do no matter what. The real power of these tools is that there are so many ideas people would like to try, but never have the time or motivation to pursue. So the comparison is not only "built with and without LLM" but "would you even build this if you didn't have the LLM?". The gap in productivity in this case is much more wide.

Those sort of ideas are unlikely to yield major benefit, though.

This is basically replicating the plight of the solo open source dev, writ large. Individual programmers have long built the thing they've cared about on their own time (essentially "for free" because, despite kindergarten economics theory, a programmer cannot usually monetize a marginal hour). And it usually goes that the project never gets adopted anywhere. It might acrue more features and total man-hour effort than most of what FAANG does in open source to drown out the solo devs. But the market will decide that "no organizational buy-in" is a signal the project doesn't matter. Other developers will decide, "if he could do it, so could I" and also not adopt.

Same exact thing is happening and will continue to happen with all these generated "but we wouldn't have done it otherwise" projects. It's just very, very unlikely to go anywhere.

That which took very little effort to create will receive very little effort to promote.

Re: 2x, not 10x: coding with LLMs in 2026

#85

> As such, I use LLMs mainly to produce a rough draft of the code which I then iterate on heavily, at least until I like the general structure. Weird… I would have said this was how it was about 2 years ago, but no way in 2026.

[flagged]

People are still figuring out how to use LLMs/AI and considering how feelings based and hard is to reproduce many of the results people get, a lot of the improved approaches are basically at "trust me bro" reliability.

TBH i expect it'll take several years before people largely settle on what works good and what works bad (or doesn't work) and that's assuming things wont chance in a massive way during that time.

And this isn't really anything new, people rarely come up with some new way of programming and have everyone learn and understand best uses from the start - it takes years (and that is assuming everyone will agree that'd be something worth bothering about).

Re: 2x, not 10x: coding with LLMs in 2026

#86

Even this is overstating it IMO. I already convert from multipliers to percentage of increase, so when someone claims 10x they very likely mean +100% productivity, and here 2x means +20% productivity, which seems about right. Nobody that was normally productive before LLMs has suddenly 10x'ed their output now. The problem is that 20% productivity when it comes to generating code, really doesn't translate in 20% produ…

2x is 100% increase.

I know, and I'm saying that 2x claims should be interpreted as an actual 20% increase, and 10x claims as an actual 100% increase. People are just bad at estimating their own productivity.

Re: 2x, not 10x: coding with LLMs in 2026

#87

While I agree with the premise, I think this angle only applies on work one was going to do no matter what. The real power of these tools is that there are so many ideas people would like to try, but never have the time or motivation to pursue. So the comparison is not only "built with and without LLM" but "would you even build this if you didn't have the LLM?". The gap in productivity in this case is much more wide.

> The real power of these tools is that there are so many ideas people would like to try, but never have the time or motivation to pursue.

This can be a negative multiplier: code I thought I wanted that gets immediately abandoned is a net-negative if no one else wants it (lets face it, this is the safest default posture for software of unknown providence).

In isolation, instant-abandonware takes up hdd space, burns dependabot's CPU-cycles, and wastes human attention when appearing in search results. In aggregate, it floods the zone with a deluge of forks with imperceptible differences between them, based on nit-picks, legitimate stand-out products will have a much harder time going forward.

Re: 2x, not 10x: coding with LLMs in 2026

#88
post #82

While I agree with the premise, I think this angle only applies on work one was going to do no matter what. The real power of these tools is that there are so many ideas people would like to try, but never have the time or motivation to pursue. So the comparison is not only "built with and without LLM" but "would you even build this if you didn't have the LLM?". The gap in productivity in this case is much more wide.

I think the ideas worth pursuing still require substantial time and motivation, even with LLMs. Otherwise you just end up with a half-baked sloppy artifact that nobody will ever use or study, for a net negative benefit to humanity.

Yes this is true to some extent. I've been using LLMs to run some computer vision tests, and I've certainly noticed myself running into the trap of "just one more AI experiment", or "just one more change" while neglecting to actually properly integrate the learnings into my mental model.

However, without an agent running its own experiments on a cloud GPU, would I realistically have invested my limited work hours and tried evaluating 10 different models, each with 10 different tuned parameters, to solve my specific use case?

Or would I have tried 1-2 models and spent my time trying to optimize those models?

I think there is some merit to the spray and pray approach when one is in the exploration phase of the solution space.

Also, on more than one occasion now, I have had fable halve the inference latency of a model simply because the original implementation from an academic included unnecessary GPU-to-CPU-to-GPU transfers or similarly inefficient operations. Those optimizations came at essentially 0 time cost to me and I can verify that the outputs are byte-identical. Pretty sweet!

Re: 2x, not 10x: coding with LLMs in 2026

#90
post #46

Earlier quoted context omitted.

AI is great because my job is a lot easier, but it produces some extremely crappy code that would've NEVER passed a code review 1 year ago. You could argue that it speeds up development by 5X or more, but then it slows down testing/verifying, code review, and in many cases it makes it impossible to review/rework by hand. I just do what I'm told at work but even though I'm sure I'm in the minority I'm extremely skepti…

> it produces some extremely crappy code that would've NEVER passed a code review 1 year ago The 10x speed up comes from the fact that we have all given up on properly reviewing each others code and we just say “meh, it will be fine, lgtm”

This. The bar has never been lower.
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