Agents Articles

5 posts

• The Claude Code Plugin Marketplace: How Skills, MCP Servers, and Plugins Actually Fit Together in 2026 5/19/2026 In April 2026 Anthropic shipped a real plugin marketplace inside Claude Code. By May there were 2,800 skills, 400 plugins, and a community of developers swapping workflows the way we used to swap dotfiles. The marketplace is the most underrated developer tooling shift of the year, and most teams have no idea how to think about it. Here is the mental model, the install workflow, and the part that nobody is talking about yet.
• Vercel Zero: The Programming Language Built So AI Agents Can Read, Repair, And Ship Native Code 5/18/2026 Vercel Labs just dropped a new systems language called Zero whose compiler speaks JSON, whose effects live in your function signatures, and whose binaries weigh less than ten kilobytes. The pitch is simple: a language where an AI agent can read a compiler error, ask for a typed fix, and ship a native program without a human in the loop. Here is what Zero actually is, what it is not, and whether the agent-first compiler is a clever bet or a Vercel side project you can safely ignore.
• AI Browser Agents in 2026: Stagehand vs Browser Use vs Playwright 4/27/2026 Most browser automation tutorials show you how to click buttons. They do not show you what happens when the button moves, the page layout changes, and the model confidently clicks the wrong thing anyway. Here is how to build browser agents that survive contact with the real web.
• Multi-Agent vs Single-Agent Architecture in 2026: When the Crew Beats the Soloist 4/25/2026 Multi-agent systems are the architecture pattern everyone is talking about in 2026 and almost nobody actually needs. After shipping both shapes in production, here is the honest framework for when a crew of agents beats a single well-prompted one, and when it just multiplies your bugs.
• AI Agent Observability: Debugging Production Agents Without Going Insane (2026) 4/21/2026 The reason your agent works in development and quietly falls apart in production is almost never the model. It is that you cannot see what it did. Here is the observability setup that turns mystery failures into fixable bugs.