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✍️ Prompting & Context ​

Context engineering, prompts, spec-writing.

BlogSean Goedecke

LLMs Reward Expertise

An argument that prompting well isn't a generic, democratized skill — deep domain expertise is what lets someone steer an LLM effectively.

  • Uses Terence Tao's math conversations with ChatGPT as an example: his edge comes from spotting flaws and better approaches, not from prompting technique.
  • The limiting factor in AI collaboration is communicating exactly what kind of solution you want and judging the output — something only domain expertise enables.
  • As models improve, the human stays the bottleneck for complex, nuanced tasks, so domain expertise keeps its value rather than being flattened by AI.
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✍️ Prompting & Context

added by Adam Tomat • 2nd Sep 2026

DocsAnthropic

AI Fluency: Framework and Foundations

A self-paced course teaching a structured framework for working with AI systems effectively, ethically, and safely, built with academic partners.

  • Centres on a "4D" framework — Delegation, Description, Discernment, Diligence — covering generative AI fundamentals and prompting technique.
  • Progresses from foundational concepts to hands-on application, including a "Description-Discernment loop" and project planning exercises.
  • Ends in an assessment with a certificate of completion.
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✍️ Prompting & Context

added by Adam Tomat • 17th Aug 2026

DocsASD Simplified Technical English Maintenance Group

Use ASD-STE100 to Stop LLMs Writing Slop Documentation

ASD-STE100 (Simplified Technical English) is a controlled-language standard, originally built for aircraft maintenance manuals, that constrains vocabulary and grammar so technical writing is unambiguous — and it works as a style constraint for LLM-written docs too.

  • Defines ~900 approved words and 53 writing rules, maintained by ASD's Simplified Technical English Maintenance Group; free to download.
  • The idea circulating in the community: require an LLM to adhere to STE's rules as a prompt constraint to cut "AI-slop"-sounding technical documentation.
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✍️ Prompting & Context

added by Adam Tomat • 21st Jul 2026

BlogAlberto Arena

CLAUDE.md Is RAM, Not Disk

An argument for treating `CLAUDE.md` as small, constantly-loaded working memory, and pushing everything else into a `docs/` folder that's only pulled in on demand.

  • `CLAUDE.md` loads into every session and costs tokens every time, so keep it to a short project overview, pinned stack/versions, exact commands, and one-line pointers — not exhaustive detail.
  • Move deeper material into `docs/` (architecture in `DESIGN.md`, a phased roadmap in `PLAN.md`, a lightweight decision log in `DECISIONS.md`) referenced only when needed.
  • Nested, folder-level `CLAUDE.md` files keep domain-specific rules local instead of bloating the root file.
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✍️ Prompting & Context🤖 Building with Agents

added by Tom Harper • 15th Jul 2026

DocsOpenAI

Prompting Guidance for GPT-5.6 Sol

OpenAI's official guidance for adapting prompts and agent workflows to GPT-5.6 Sol.

  • Strip redundant instructions, examples, and tools first — OpenAI's internal tests found leaner prompts scored 10–15% better while cutting tokens 41–66%.
  • Describe the destination rather than prescribing every step, with clear stopping conditions and defined approval boundaries for autonomous action.
  • Migrate models incrementally: test before and after prompt changes, and debug regressions from real traces rather than rewriting prompts wholesale.
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✍️ Prompting & Context

added by Adam Tomat • 15th Jul 2026

ToolForward Future

Loop Library

A curated library of 70+ reusable "agent loop" prompt workflows.

  • Ready-made loop patterns you can drop into a project.
  • Reusable across different codebases and tasks.
  • Pairs directly with the loop-engineering idea.
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🤖 Building with Agents✍️ Prompting & Context

added by Adam Tomat • 18th Jun 2026

Curated from the AI Chinwag Slack community.

The good stuff, kept.