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If implemented correctly these tricks will still work on less expensive models delivering nearly identical value.

Today, a hefty amount of standard coding tasks can be completed with similar results to gpt astra using terra and a tailored harness around it.

Also the scale matters. One big, expensive session, with a frontier model paired with a dev-babysitter is ok. But make it a factory (kindergarden: few devs, many parallel streams) and you'll want to follow a strict protocol.

by dmos621 hours ago|

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I disagree. Parallelization, coordination shouldn't be model-level functionality. Further, how do you know if or when we'll get orders of magnitude increases in context sizes. Or, do you mean that the labs will just nail the perfect plug-and-play harness? That's fair, but why wait.

by FearNotDaniel1 hours ago|

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Models are already good enough. Last week I had Fable plan out a project that took approx 4 days end to end with each phase orchestrated by a supervisor agent delegating individual tasks to other agents, coordinating everything and checking status by simple text files in the repo. I didn’t have to tell the agent to do it that way, it just came up with it and set up the infra as part of the planning overview. Great that everyone’s posting their “my secret sauce” cookbooks just to jump on the hype train but it looks like the models have already figured it out for themselves.

by simianwords59 minutes ago|

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true haha

> Great that everyone’s posting their “my secret sauce” cookbooks just to jump on the hype train but it looks like the models have already figured it out for themselves

Unfortunate lesson to be learned here: there's not much leverage here other than just using AI. Previously, us devs could get a head start and build some institutional knowledge but not this time. I'm bearish on all the custom harnesses stuff that people talk about.

What helps me is to understand the failure modes of LLMs - it can't be articulated in easy words but something you can learn slightly by just using it. For example I have an intuition of when to start compacting but Codex already does it for you now haha.

My take: the highest leverage move for us is to write AGENTS.md and provide everything that the model can't learn on its own or might take time to learn.

by normie30002 hours ago|

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So we should just ignore?

by dannyw1 hours ago|

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If you’re using models today, it’s worth it.

Yes it’ll eventually get built into the harness/model/interface; just like how “work it out step by step” became thinking, but if you have work to do today, it can be worth trying to improve it.