If you're looking for a coding agent that would fit nicely into resource-constrained environments (such as laptops, or tiny VPS servers, or tiny single-board computers, etc), and would also work great with local models - you might also like hax (https://usehax.dev/). 0.7 MB dynamically linked native C binary, few MBs of RAM usage when running, auto-discovers config from running local llama-server, and uses minimalist system prompt and tools for lean context usage.
Fun reference I tested on 32 GB ram laptop with no extra GPU: llama.cpp: “what is ls”, almost immediate starts answering at one ~word/sec. Ask opencode with same model (some gwen e4b or something) to check what’s in its working directory: 20 min to response.
Opencode system prompt contains a lot of stuff but even worse is oh-my-pi where their long prompt looks like random garbage hallucinated by a 2023 LLM:
The same thing as the last word of "That is the difference between 22 and 226 seconds, measured." Techies I know would mostly omit "measured"; the rest would show, not tell.
“Chad” initially looked interesting but the minute I saw the ai-written markdown and giant commit I just left. I just can’t bring myself to read someone elses’ slop, regardless of performance.
If all a developer hand writes is a truthy and readable markdown document, I really don’t care if the rest of the project is vibe coded, but I struggle to get interested in AI generated summaries and docs.
https://m.youtube.com/watch?v=c_fQoDkULl0 (see around 8:00)
"it spreads up to 50% between nights, so nothing between the lean arms is a finding."
“Chad” initially looked interesting but the minute I saw the ai-written markdown and giant commit I just left. I just can’t bring myself to read someone elses’ slop, regardless of performance.
If all a developer hand writes is a truthy and readable markdown document, I really don’t care if the rest of the project is vibe coded, but I struggle to get interested in AI generated summaries and docs.