13 articles
We rebuilt and replatformed this site in a day by running a fleet of AI agents in parallel. Here is the honest operating model - the ownership rules, the verification gate on every handoff, and the failure modes we hit, with the guardrail each one produced.
Factory.ai shipped a router that auto-picks the model for each Droid session and fails over across providers. The vendor claims 20-25% lower token spend and 99.9%+ request reliability. Here is what the product actually does, which claims are vendor claims, and whether a router beats DIY routing for your team.
A code-heavy field guide to model routing. Real, runnable-style configs for tiering tasks by complexity, routing simple work to open-weights, reserving frontier models for hard reasoning, building failover chains, and keeping prompt caches warm with OpenRouter, LiteLLM, and Factory Router.
Claude Managed Agents now have multiagent sessions, outcomes, webhooks, and vault events. The practical takeaway is not just better agents. It is that agent runs need backend job discipline.
31 deployed apps. 7 down. Favicons missing on 20 of 24 reachable hosts. Sentry on zero. Here is how a single audit turned into 58 PRs in one afternoon - and what shipped, what didn't, and what the pattern was.
Notes from a single session running 200+ Claude Code subagents in parallel across 35 repos. What worked, what broke, and the patterns I codified into a skill so the recipe replays.
A deep comparison of Codex's new /goal loop and Claude managed agents outcomes, with practical workflow examples, control tradeoffs, and migration guidance for long-running tasks.
I told an agent to improve the site every 10 minutes and went to sleep. Here is what 12 new repos, 60 PRs, and three goofs taught me about overnight orchestration.
Configurable memory, sandbox-aware orchestration, Codex-like filesystem tools. Here is how the new Agents SDK actually behaves in prod.
The math of agent pipelines is brutal. 85% reliability per step compounds to about 20% at 10 steps. Here is why long chains collapse in production, and the six patterns the field has converged on to fight the decay.
From single-agent baselines to multi-level hierarchies, these are the seven patterns for wiring AI agents together in production. Each with a decision rule, an implementation sketch, and the tradeoffs that actually matter.
Production-tested patterns for orchestrating AI agent teams - from fan-out parallelism to hierarchical delegation. Covers CrewAI, LangGraph, AutoGen, OpenAI Agents SDK, Google ADK, and custom approaches with real code.
From swarms to pipelines - here are the patterns for coordinating multiple AI agents in TypeScript applications.
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