381–390 of 512 posts
So, regarding the productivity argument: I don't get it. It doesn't really matter (for regular employees) that you can do now in 2h what before it took 2 days. Why? Because it's not that you have the rest of the day for yourself. You still have to work 8h/day as usual. But now the pattern is different: instead of enjoying the craft digging deeper into problems in the span of 2 days, now you are rushing into some slot…
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Agent mania setting in It's also pretty funny sometimes how it gives weird future roadmap estimates ("part 2 - 3 weeks, part 3 - 2 months", etc.) and when you tell it to actually do those changes it's pretty much done in half an hour
It repeats what it has seen in the training data. Expecting it to reason about the complexity of a task is a pipe dream. The best is to tell it not to come back with estimates, and when it does, remove them anyway.
So, regarding the productivity argument: I don't get it. It doesn't really matter (for regular employees) that you can do now in 2h what before it took 2 days. Why? Because it's not that you have the rest of the day for yourself. You still have to work 8h/day as usual. But now the pattern is different: instead of enjoying the craft digging deeper into problems in the span of 2 days, now you are rushing into some slot…
Like with any tech there are dumb ways of using it and there are smart ways. Treating it as a "slot machine giving you the right answer" is a dumb way - it may work for a bit, but it won't carry you very far because everyone else can also do this. No one is stopping anybody from digging deeper into problems than ever before using this technology - that's the smart way.
Fast AI seems genuinely exciting and somewhat unsettling to me. Right now Claude is faster than me on some tasks but we’re at least close. I have a prompt to clean up a PR that’s been running for 1h now and I expect it to take another few. It’s hard to imagine how the workflow would look like if it was near-instant. On the one hand, it might be easier to focus. Some prompts take so long that I start to multitask and…
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You would do us all a service by telling us how your experiences of that have been.
I would say about 35% of the time I run into problems and eventually give up and go to GPT 5.5 and it much more efficiently handles the original task. Then I see the token costs going up and it motivates me to continue trying the open source ones.
I'm seeing some people say flash is amazing and can handle everything, and some say it's useless. It seems to depend on the task. I think it depends on the harness too (it works better in Claude Code in my experience, it's probably been trained on that).
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You would do us all a service by telling us how your experiences of that have been.
I've been doing the same, though admittedly out of curiosity more so than lack of funds. The open models are catching up quickly in their abilities, to the point where they're (mostly) not doing stupid stuff regularly, but you have to be very specific about what you want. I found that Opus, for example, is much better at asking me to clear up ambiguity in a request before starting, whereas the Chinese models tend to…
That's the main thing I've noticed. Small models can follow instructions just fine. If the instructions are very specific. Then I often have to spend more time explaining a task than it would have taken me to do it myself.
The bigger models have a lot more common sense.
I wonder if that could be improved slightly through prompting. Asking it to clarify anything that's confusing. Or maybe it just makes incorrect assumptions without realizing the ambiguity. One way to find out!
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We are living in a ZIRP-like era where builders at the fastest pace layer have misattributed their velocity to exponential gains in model capability. In fact, they are surfing on decades of careful effort to build a robust foundation of highly reusable software libraries. This strategy will seem to work really well until the economy that enabled that foundation to form is hollowed out. Then, there will be a reckoning…
It's not just software libraries. Specs, applications (the browser!), expectations, device integrations, operating systems, etc. So much that starting from scratch seems impossible. I'm not agreeing or disagreeing with you, but my brain cannot comprehend how machines can advance such interconnected systems while keeping humans in focus . Perhaps I shouldn't have watched the Animatrix again.
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why is deepseek v4 pro a lot lower than flash? where is mimo 2.5?
DeepSeek v4 Pro struggles with a custom harness, and all the models ranked above it don't, so it gets downweighted in the agentic coding benchmarks (although it ranks better than Flash in one-shot problem solving: https://gertlabs.com/rankings?ow=1&mode=oneshot_coding ). We ran plenty of samples. MiMo v2.5 is on there, as well as the pro version. We found a few anomalies in our evaluations, which makes sense -- if ev…
Flash handles it fine, which I found amusing. (Since Mimo is supposed to be opus level!) But Flash seems to work even better in Claude Code...
With smaller models I always have the issue of needing to adapt myself to their preferred workflow... which sort of defeats the purpose. Price is hard to beat tho :)
I may sound like a shill, but exponential growth and all. We are going to get near instant software from prompt, multiple ones and then choose the best one. Discussions about choosing a library with the best syntactic sugar method naming is just as crazy as suggesting we type in assembly.
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