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If you need reproducible, consistent outputs from an LLM, set temperature to 0. This makes the model always select the highest-probability token at each step, effectively making it deterministic. This…

Sharing my code review workflow that catches issues our team of five humans regularly misses. I feed each PR diff to Claude with a structured review prompt covering bugs, security,…

Wrapping prompt sections in XML tags dramatically improves output quality, especially with Claude. Instead of relying on markdown headers or plain text separators, use tags like , , , and…

Ran a systematic comparison on a sentiment classification dataset: zero-shot hit 78% accuracy, one-shot reached 85%, and three-shot examples pushed it to 91%. The examples do not need to be…

I have been reading papers on chain-of-thought prompting and the performance gains are remarkable, especially on math and logic tasks. The prevailing theory is that CoT forces the model to…

I built a complete blog automation pipeline using chained AI prompts. Step one generates topic ideas from trending keywords. Step two creates detailed outlines. Step three drafts each section with…

I tested Claude with a full 200K token context containing a large codebase and was surprised by how accurately it could reference specific functions deep in the input. The attention…