PROMPT ENGINEERING

Give an agent one instruction and it obeys. Give it eight and it obeys all of them about five percent of the time, no matter which frontier model you bought. The phase transition is measured, the constraints also die in compaction and handoff notes, and in security-critical code the failure ships as infrastructure. The fix is not a better prompt. It is a smaller simultaneous budget and a side channel for the rules that must survive.

A fair look at Langfuse, PromptLayer, Promptfoo, Helicone, Latitude, and Agenta for versioning, evals, and deploying LLM prompts.

Rewriting prompts and skills for Fable 5: what changes when you migrate agents from Opus 4.x, how effort interplay works, and which old workarounds now hurt.

The latest GPT Image 2 prompt-library repos are not just galleries. They point at a practical workflow for repeatable visual systems, agent-friendly templates, and cheaper creative iteration.

Prompt engineering for coding is less about clever wording and more about task specs, repo context, constraints, examples, verification, and reviewable receipts.