💬 Prompt Engineering - sybyl · Scour

Auto-Configuring AI Agents Based on Your Codebase (AutoSkills) 🧠Obsidian

autoskills.sh·1d·DEV

Memory Machines: Can LLMs create lasting flashcards from readers' highlights? 📖Interactive Fiction

memory-machines.com·1d·Hacker News

The Future of AI in Ubuntu 🧠Obsidian

discourse.ubuntu.com·3d·Hacker News, r/linux

aarondfrancis/counselors: Fan out prompts to multiple AI coding agents in parallel 📖Interactive Fiction

github.com·13h

RAG vs. Fine-Tuning vs. Prompting: 2026 Strategic Guide ⌨️Text Editors

endevsols.com·4d·DEV

Optimize Anything with LLMs ⌨️Text Editors

gepa-ai.github.io·6d

Global Claude Markdown file 📝Markdown

gist.github.com·4d·Hacker News

TDD Governance for Multi-Agent Code Generation via Prompt Engineering 📖Interactive Fiction

My AI tool stack 🧠Obsidian

ministryoftesting.com·3d

I over-engineered my AI coding setup one justified upgrade at a time ⌨️Text Editors

machinethoughts.substack.com·6d·Substack

Show HN: How LLMs Work – Interactive visual guide based on Karpathy's lecture 🗂️Zettelkasten

ynarwal.github.io·6d·Hacker News

mattpocock/skills: Skills for Real Engineers. Straight from my .claude directory. 🧠Obsidian

github.com·19h·r/GithubCopilot

Monitoring LLM behavior: Drift, retries, and refusal patterns 🧠Obsidian

venturebeat.com·6d·Hacker News

Entering the Post-Prompting World 📖Interactive Fiction

blog.southparkcommons.com·3d·Hacker News

Fixing What LLMs Get Wrong (22 minute read) 📡Information Theory

thebigdataguy.substack.com·4d·Substack

Programming with Data: Test-Driven Data Engineering for Self-Improving LLMs from Raw Corpora 🏷️Metadata Standards

Seven best practices for writing high quality prompts ⌨️Text Editors

blog.postman.com·6d

AI Week in Review 26.04.25 🧠Medical AI

patmcguinness.substack.com·5d·Substack

Beyond the next token: Why diffusion LLMs are changing the game 🧠Obsidian

developers.redhat.com·3d

Cross-checking LLM outputs at scale without manual overhead 🧠Obsidian

asknestr.com·4d·r/OpenAI

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