Tag: prompt engineering
Chain-of-Thought in Vibe Coding: Why Explanations Before Code Make You a Better Developer
Chain-of-thought prompting forces AI coding assistants to explain their logic before generating code, reducing errors and building real understanding. Learn how this simple technique transforms how developers work with AI.
Read More
Retrospectives for Vibe Coding: How to Learn from AI Output Failures
Learn how to run effective retrospectives for Vibe Coding to turn AI code failures into lasting improvements. Discover the 7-part template, real team examples, and why this is the new standard in AI-assisted development.
Read More
Error Messages and Feedback Prompts That Help LLMs Self-Correct
Learn how to use error messages and feedback prompts to help LLMs fix their own mistakes without retraining. Discover the most effective techniques, real-world results, and when self-correction works-or fails.
Read More
Reducing Hallucinations in Large Language Models: A Practical Guide for 2026
Learn practical, proven methods to reduce hallucinations in large language models using prompt engineering, RAG, and human oversight. Real-world results from 2024-2026 studies.
Read More
Operating Model for LLM Adoption: Teams, Roles, and Responsibilities
An effective LLM operating model defines clear teams, roles, and responsibilities to safely deploy generative AI. Without it, even powerful models fail due to poor governance, unclear ownership, and unmanaged risks.
Read More