autoresearch Beyond ML — Optimizing Prompts, Code Performance, and Landing Pages Overnight
Apply the autoresearch pattern to non-ML problems. Working code for system prompt optimization, code performance optimization, and landing page copy optimization.
autoresearch Beyond ML — Optimizing Prompts, Code Performance, and Landing Pages Overnight
In Parts 1-3, we applied the autoresearch pattern to ML tasks: LLM pretraining, text classification, image classification, and RAG pipelines. But the ratchet loop — modify, run, evaluate, keep or discard — doesn't care what you're optimizing.
In this post, we apply autoresearch to three non-ML problems that developers and marketers deal with every day:
- System prompt optimization — automatically improve an LLM prompt's accuracy
- Code performance optimization — make your build faster, your bundle smaller
The rest of this series is paid
- ✓ The whole “autoresearch hands-on” series: 3 posts in English, 3 in Korean
- ✓ 2 Jupyter notebooks
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