Tag: prompt engineering

Reinforcement Learning from Prompts (RLfP) automates prompt optimization using feedback loops, boosting LLM accuracy by up to 10% on key benchmarks. Learn how PRewrite and PRL work, their real-world gains, hidden costs, and who should use them.

NLP pipelines and end-to-end LLMs aren't competitors-they're complementary. Learn when to use each for speed, cost, accuracy, and compliance in real-world AI systems.

Small changes in how you phrase a question can drastically alter an AI's response. Learn why prompt sensitivity makes LLMs unpredictable, how it breaks real applications, and proven ways to get consistent, reliable outputs.

Recent-posts

Chunking Strategies That Improve Retrieval Quality for Large Language Model RAG

Chunking Strategies That Improve Retrieval Quality for Large Language Model RAG

Dec, 14 2025

Pattern Libraries for AI: How Reusable Templates Improve Vibe Coding

Pattern Libraries for AI: How Reusable Templates Improve Vibe Coding

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Agentic Generative AI: How Autonomous Systems Are Taking Over Complex Workflows

Agentic Generative AI: How Autonomous Systems Are Taking Over Complex Workflows

Aug, 3 2025

Prompt Robustness: How to Make Large Language Models Handle Messy Inputs Reliably

Prompt Robustness: How to Make Large Language Models Handle Messy Inputs Reliably

Feb, 7 2026

Preventing AI Dark Patterns: Ethical Design Checks for 2026

Preventing AI Dark Patterns: Ethical Design Checks for 2026

Feb, 6 2026