Agents
6 articles about agents.
AI Regulation - Protecting Creators While Enabling Agents
AI regulation needs to protect creators whose work trains models while not blocking the development of useful AI agents. The balance is hard but necessary.
Agent Orchestrators vs Parallel Sessions with Worktrees
Comparing agent orchestration patterns vs parallel sessions with git worktrees. Real isolation wins for coding tasks because each agent gets its own workspace.
AI Agents That Act on Your Computer vs Ones That Just Advise
Most AI tools generate text advice. Desktop agents actually operate your computer - clicking, typing, navigating between apps. The gap between advice and
Making AI Coding Enjoyable - Fix the Process, Not the AI
The 200-file changeset problem is a process failure, not an AI failure. Scope your agents tightly to make AI-assisted coding productive and enjoyable.
LLM Observability for Desktop Agents - Beyond Logging Model Outputs
Traditional LLM observability focuses on model outputs. For desktop agents, watching what the agent actually does on screen - logging actions, not just
Long-Term Memory Is What Separates Toy Agents from Useful Ones
Without persistent memory, every session starts from zero. With it, the agent knows your preferences, your contacts, your common workflows. The difference