Context engineering, not prompt engineering: 8 techniques for 10x LLM output
JafarNajafov · x · 2026-10-13
The author argues top lab engineers get 10x more from the same LLMs via context engineering rather than prompt engineering, then details 8 techniques: persona + expertise context (a 'senior engineer' persona produces fundamentally different code reviews), reference context (paste 2-3 examples and name their patterns to stop hallucinated guessing), and constraint context (specify what NOT to do, must-haves, format and priorities — 'unlimited freedom = mediocre outputs'). Core thesis: design the context systematically instead of tweaking wording.
More from coding & agent
- LangChain adds support for ScaleDown's cheap, fast constrained decision models for agent loops — LangChain · 2026-10-13
- Yoniq Compute repo ships inference recipes validated on 1x-8x RTX Pro 6000 with SGLang and vLLM — TheZachMueller · 2026-10-13
- SaaS Vendors and Agencies Are Asking to Plug Into HQ, the New Entry Point for Work — jacob_posel · 2026-10-13
- He Built a 7-Bot Product Swarm on Grok Bot — Here's What Actually Works — PawelHuryn · 2026-10-13
- Claude tried installing ffmpeg from a sketchy fork instead of apt while setting up a VM — haydendevs · 2026-10-13
- Google rolling out custom MCP support in Gemini desktop app to more users — testingcatalog · 2026-10-13