Most prompt engineering content treats technique selection as a matter of preference. It isn’t. When you’re building agents that run…
Browsing: Prompt Engineering & Techniques
Advanced prompt engineering techniques, system prompt design, and getting consistent output from LLMs
If you’ve built anything real with LLMs, you’ve hit this wall: you ask for JSON, you get JSON-ish. A trailing…
If you’ve ever hit Claude’s context limit mid-conversation and watched your carefully assembled prompt get truncated, you already understand the…
If you’ve built anything serious with Claude or GPT-4, you’ve hit the wall: a legitimate business task — generating a…
Most agent workflows fail not because the prompts are bad, but because the structure is wrong. You’ve probably seen both…
Most developers treat system prompts like a terms-of-service document — throw in a list of “do this, don’t do that”…
Most developers treat zero-shot vs few-shot as a coin flip — throw some examples in if the output looks bad,…
Most developers building AI agents treat safety and alignment as an afterthought — a moderation API call bolted on after…
Most LLM failures in production aren’t model failures — they’re task design failures. You hand a single prompt a problem…
Most developers ship their first LLM integration with temperature set to whatever the API default is, tweak it once when…