The New Skill in AI is Not Prompting, It's Context Engineering
Explains why Context Engineering, not just prompt crafting, is the key skill for building effective AI agents and systems.
Explains why Context Engineering, not just prompt crafting, is the key skill for building effective AI agents and systems.
A developer documents their experience using the gemini-cli tool to create a Chrome Extension with AI assistance, including setup and features.
The article explores the concept of 'Expert Generalists'—professionals who span multiple specialties—and how to identify, hire, and train them.
A guide for tech leaders on choosing between traditional coding, training models, and prompting LLMs for software development, based on Andrej Karpathy's concepts.
Explores the trade-offs between single-agent and multi-agent AI systems, discussing their characteristics, pros, and cons for different tasks.
Explores the key traits of 'Expert Generalists'—professionals who bridge multiple specialties—and their growing importance in tech.
A technical writer's analysis of common pitfalls in LLM-generated writing and practical strategies for using AI tools effectively while maintaining quality.
Argues that the 'LLMs only predict tokens' critique fails, as human brains are similarly opaque systems that process input to produce output without conscious understanding.
A developer's personal exploration and critique of using AI coding assistants like GitHub Copilot and Claude, examining their impact on the craft of programming.
A presentation on using Large Language Model (LLM) techniques to enhance Recommendation Systems (RecSys) and Search, from the AI Engineer World's Fair 2025.
A developer's cautionary tale about LLM inaccuracies in simple tasks, highlighting the need to verify AI-generated results.
Explores the future of Wikipedia and journalism in an AI-dominated world, questioning the role of human summarizers as AI becomes ubiquitous.
Key takeaways from Simon Willison's podcast interview on software architecture, plugins, and effectively using LLMs in development.
A summary of a practical session on analyzing and improving LLM applications by identifying failure modes through data clustering and iterative testing.
Developer releases Legba 2.0.0, a Windows desktop app for managing LLM requests with OpenAI API format, featuring new source code inclusion.
A course teaching how to code Large Language Models (LLMs) from scratch to deeply understand their inner workings and fundamentals.
A course teaching how to code Large Language Models from scratch to deeply understand their inner workings, with practical video tutorials.
A tutorial on building a React.js UI to stream and compare responses from multiple AI models simultaneously using the Vercel AI SDK.
Explains key AI terminology like AI, ML, deep learning, and LLMs to help engineers use the correct terms.
A developer explains how to use an open-source LLM within a GitHub Actions workflow to generate descriptive titles for automated Pull Requests.