A developer details the iterative UI design process for the 'Ask AI' feature in their note-taking app, Edna, focusing on API key clarity.
A developer's guide to calling various LLM APIs (OpenAI, Grok, Anthropic, Google) directly from the browser, including workarounds and using OpenRouter.
A technical exploration of llmfs, a FUSE filesystem where all file operations are dynamically generated and controlled by an LLM.
A guide to adding long-term memory to a Gemini 2.5 chatbot using the Mem0 library and vector databases for personalized AI interactions.
Explores the role of 'Expert Generalists' in tech, their key traits, and why they are increasingly vital alongside specialists and LLMs.
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.
![AI: did you check your work? [blog]](https://alldevblogs.blob.core.windows.net/thumbs/article-98b23f154f19-full-84e80bd4.webp)
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.
