Prompt Engineering
6 pieces on Prompt Engineering, including 2 step-by-step guides.
Guides
Beyond Prompt Engineering: Deep-Dive RAG for Intent Detection & Slot Filling in AI Agents
Stop relying on massive, static context prompts. Learn how to combine Retrieval-Augmented Generation (RAG), vector search (FAISS), and history compaction to achieve scalable intent detection and slot filling.
What Is Tokenization Drift? A Practical Guide to Finding and Fixing It
Learn why small prompt formatting changes can alter token sequences, reduce reliability, and push LLM inputs away from the format a model was tuned to follow.
News & Analysis
Claude Fable 5.1 System Prompt Bans Lyric and Character Reproduction
Anthropic's Fable 5.1 system prompt adds persistent lyric-refusal blocks and coded SVG character bans, days after Sony and Warner sued over training data.
LLM Judge Approved Its Own Errors: Three Biases Explained
A production SQL pipeline approved wrong queries for weeks. The judge and generator shared the same model — and that structural flaw caused the incident.
Context Engineering: Four Antipatterns Breaking Coding Agents
At QCon, Baruch Sadogursky and Patrick Debois demonstrated four concrete context engineering antipatterns — and architectural fixes for each.
Stop Hand-Tuning Prompts: A Production Workflow for Automated LLM Optimization
Move beyond trial-and-error prompting with a measurable workflow for evaluating and optimizing LLM prompts in production systems.