AGENTS

A companion guide to the Agents 101 video: a behind-the-scenes walkthrough of building and deploying AI agents fast on Vercel, the agentic infrastructure stack. Here is the map of what to learn and where to go next.

No single model wins every task anymore, and the companies that never trained one - Factory, Devin, Perplexity, Cursor, OpenCode - are turning that into a moat. This is how model routing works, why open weights and neoclouds make it cheap, and the honest counter-argument.

Cursor Automations lets AI agents run in the background based on triggers, not prompts. Here is how to set them up, configure triggers, and integrate into your workflow.

Anthropic's first generally available Mythos-class model, released June 9, 2026. 1M context, 128K max output, $10/$50 per million tokens. Built for long-horizon agentic work.

Anthropic's recommended default for complex work, released May 28, 2026. 1M context, 128K output, $5/$25 per million tokens. Defaults to high effort on all surfaces.

Open-source AI coding agent for terminal, desktop, and IDE. Works with 75+ LLM providers including Claude, GPT, Gemini, and local models. Runs parallel sessions on one project.

Google's asynchronous coding agent. Point it at a GitHub repo, it clones to a cloud VM, plans with Gemini, and opens a pull request. Tiered plans from 15 to 300 tasks per day.

Open-source AI agent built in Rust, now governed by the Agentic AI Foundation at the Linux Foundation. Desktop app, CLI, and API. 15+ model providers, 70+ MCP extensions.

Mac app for running parallel Claude Code, Codex, and Cursor agents in isolated workspaces. Watch every agent work at once, then review and merge their changes.

Open-source cloud sandboxes for AI agents. Isolated environments that start in under 200ms, run code in Python, JavaScript, and more, and persist sessions up to 24 hours.

Fable 5 ships with safety classifiers that route flagged requests away from the model. In production you need to handle this, and Anthropic shipped three ways to do it. Here's how each one works, with code, plus the billing rules nobody has written up.

Graphify is trending because coding agents keep hitting the same wall: they can edit files, but they still need a durable map of how the codebase, docs, schemas, and decisions connect.

InsForge is trending because coding agents can scaffold UI faster than they can safely operate databases, auth, storage, functions, and deployments. The backend now needs an agent-readable control plane.

Open-source terminal agent runtime with approval modes, rollback snapshots, MCP servers, LSP diagnostics, and a headless HTTP API. Uses DeepSeek models by default.

GitHub is filling with multi-agent frameworks, skills, and coding harnesses. The useful lesson is not that every team needs a swarm. It is that every agent needs receipts: tests, logs, diffs, and reviewable checkpoints.

SNEWPAPERS is a useful Show HN signal: the strongest agentic search products do not replace search results with prose. They teach the agent to operate a real search system.

DeepSeek V4 is trending because it is close enough to frontier coding models at a much lower token price. The real question for developers is where cheap reasoning belongs in an agent stack.

Flue is trending because it names the part of agent infrastructure that is becoming product-critical: the programmable harness around the model.

jcode is trending because it competes on a less glamorous but important agent metric: how cheap it is to keep many coding sessions alive.

Hugging Face's ml-intern is trending because it narrows the agent loop around one domain: papers, datasets, model training, Hub traces, and ML shipping workflows.