The work behind the product

See how AI work actually gets done.

Explore complete workflows, the specialist agents inside them, and practical guides for connecting AI to the tools your team already uses.

The system in one minute

Three parts. One complete job.

A request becomes a visible workflow. Focused agents own bounded responsibilities. The orchestrator chooses the next step, gates feedback, and checks the job against its accepted outcome.

Use the stack you already have

The tools stay. The work gets organized.

Browse 57 providers and 711 supported actions across communication, publishing, SEO, commerce, advertising, research, media, and more.

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From the work

Practice, evidence, and direct answers.

Each guide starts with the answer, then shows the decisions, evidence, failures, and practical methods behind it.

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AI operations8 min read

AI workflow automation: automate the rules, not the judgment

A practical way to decide what AI workflows should enforce in code, what agents should decide at runtime, and when a person genuinely needs to step in.

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AI operations8 min read

How should an AI orchestrator triage feedback?

A practical way for AI orchestrators to separate blocking findings from repairs, preferences, and scope drift without weakening review.

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AI operations12 min read

How to refine an AI agent workflow: best practices after the first working version

A practical method for using agents, independent workflow runs, and post-run debriefs to refine AI workflows without scope drift.

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AI operations10 min read

What should an AI agent handoff include?

A practical handoff packet for AI agents, covering objective, state, evidence, context, tools, output, recovery, ownership, and stopping rules.

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Focused responsibilities

The right specialist at the right stage.

Agents research, create, review, and verify. Orchestrators choose the next valid step and gate feedback against the accepted plan.

Meet every agent →