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Comment by firemelt | Hacker News Reader

whenever I see post like this

i said well yeah, but its too sophiscated to be practical

Fair point, but because I spent a year building and refining my custom tool, this is now the reality for all of my AI requests.

I prompt, press run, and then I get this flow: dev setup (dev-chat or plan) code-map (incremental 0s 2m for initial) auto-context (~20s to 40s) final AI query (~30s to 2m)

For example, just now, in my Rust code (about 60k LOC), I wanted to change the data model and brainstorm with the AI to find the right design, and here is the auto-context it gave me:

- Reducing 381 context files ( 1.62 MB)

- Now 5 context files ( 27.90 KB)

- Reducing 11 knowledge files ( 30.16 KB)

- Now 3 knowledge files ( 5.62 KB)

The knowledge files are my "rust10x" best practices, and the context files are the source files.

(edited to fix formatting)

How do you re-evaluate your approach? I'm asking because the landscape, at least from my lens, was completely different a year ago. So I fear that as the foundation shifts whatever learnings, approaches and mental models I have risk being obsolete and starts to work against me.

The problem of evaluating is hard enough as it is without layers of indirection built on top of it.

It's not sophisticated at all, he just uses a model to make some documentation before asking another model to work using the documentation

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