AI Agents

Explore cutting-edge methods for providing continuous context to AI models, focusing on agentic search, intelligent memory management, and preventing context drift for more efficient and coherent interactions.

Discover how senior software engineers are practically using AI for coding, from effective 2-agent TDD setups to automating boilerplate, and why agent quality often trumps basic copilots.

Explore the debate around "vibe coding" as a craft, its intersection with AI, and practical advice for integrating generative AI into software development workflows. Discover whether this new paradigm requires mastery or if traditional coding skills suffice.

Explore the provocative concept of LLM agents calling humans as on-demand tools. This analysis delves into its plausibility, economic and ethical implications, and alternative approaches for a future where AI and humans collaborate.

Explore practical strategies for safely sandboxing AI coding agents, from VMs and containers to custom solutions, and learn from real-world "hard-earned" lessons to protect your development environment.

Explore whether AI agents are just hype or genuinely scalable for complex, multi-step workflows outside of developer tools, revealing where true production value lies in specialized internal applications.

Explore a discussion on the practical applications of personal AI agents, from creating natural language interfaces for Jira to building private, local knowledge bases for your notes and meetings. Discover real-world examples and the ongoing debate about their true utility versus simple scripts.

AI coding assistants promise to boost productivity, but many developers find they destroy the focus and enjoyment of a 'flow state.' Discover the practical strategies and mindset shifts developers are using to stay productive and engaged in the age of AI.

Explore the key differences between Model Context Protocol (MCP) and RAG. Learn how MCP servers empower LLMs to perform actions and interact with live data, and discover practical use cases and best practices.

Discover the AI developer assistant setups that professionals are actually using to boost productivity. From combining Claude and Copilot to self-hosting models, learn about the workflows that work best in 2025.