💬 Prompt Engineering - tyler · Scour

Prompt Engineering for Humans 🤖Creative Automation

michaelheap.com·2d·Hacker News·

Somewhere Between Prompt and Context Engineering 📜Procedural Text

xiegerts.com·6d·Hacker News·

Long-Context Isn't the Answer 🔧Code Generation

humanlayer.dev·2d·Hacker News·

How to move from Context Engineer to Prompt Engineering (With demo code). 🔧Code Generation

contextbento.substack.com·6d·Substack·

Knowledge Innovation System (KIS) Enhances the Quality of Inventive Concepts in Large Language Models: A Multi-Model Experimental Study 🔍RAG

zenodo.org·2d·Hacker News·

Prompt Engineering for Senior Devs: Scaling Excellence Without Technical Debt 🔧Code Generation

hackernoon.com·1d·

LLMs Are Still Just Predicting the Next Word. So Why Are They So Good Now? 📊LLM Evals

medium.com·3d·Hacker News, Hacker News·

The architectural trade-offs of AI code generation 🔧Code Generation

aha.io·2d·Hacker News·

Show HN: I block LLM hallucinations with a cognitive math framework(re!Think it) 📊LLM Evals

github.com·6d·Hacker News·

Mistral AI Workflows 📦PWA Tooling

docs.mistral.ai·1d·Hacker News·

A Mirror Test For LLMs 📊LLM Evals

lesswrong.com·2d·Hacker News·

Meta-Harness: End-to-End Optimization of Model Harnesses 📊LLM Evals

yoonholee.com·3d·Hacker News·

Entering the Mind of Ralph Wiggum 🔧Code Generation

stevekinney.com·2d·Hacker News, Hacker News·

Show HN: AI Engineering AI-native Self-learning course repo 🧠AI

aiengineeringfromscratch.com·2d·Hacker News·

Paper Cuts #2: RAG is dead, long live memory 📊LLM Evals

sderosiaux.substack.com·3d·Substack·

LLMs and Agents: How do they Work? 📊LLM Evals

mattrogish.com·5d·Hacker News·

The Case Against Text Prompts for AI Sound Generation 🎼Procedural Music

hackernoon.com·1d·

Semantic – Reducing LLM "Agent Loops" by 27.78% via AST Logic Graphs 📊LLM Evals

github.com·2d·Hacker News·

Knowledge Innovation System (KIS) v2.0: Why Question-Space Cannot Be Baked Into LLM Weights 🔍RAG

zenodo.org·4d·Hacker News·

adrida/tracer: TRACER: replace 90%+ of your LLM classification calls with a traditional ML model. Formal parity guarantees. Self-improving. 🦙Local LLM

github.com·2d·Hacker News, r/compsci·

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