Jason ColapietroFractional forward-deployed AI engineer. Founder of Suede AI, author, builder

Multi-agent automation

Split work between agents when the parts can be completed and checked independently. Keep a single owner responsible for the final integrated result.

Find the real boundary

A useful split follows a boundary in the work. One agent can inspect the content model while another checks public routes; their findings can be combined without overlapping edits. Two agents rewriting the same component are much harder to coordinate. Before splitting a task, identify the shared interfaces and the order of dependencies. If the second task cannot begin until the first has made its design decision, run them in sequence.

Give each agent a complete brief

Include the goal, owned files, relevant context, acceptance check and forbidden side effects. Tell the agent that other work may be happening and that unrelated edits must be preserved. Ask it to report evidence, not just a completion label. A useful content brief names the audience, the reader's question, the product facts that may be claimed, and the source of those facts. A useful implementation brief names the input, expected behavior and failure cases.

Agree on a small interface

For a page built from structured content, agree on the fields before dividing implementation and writing. For example: title, introduction, sections and related links. For a software change, agree on the function signature or request and response shape. Avoid parallel work that depends on each agent inventing its own interpretation of the same interface. The coordinator should make that shared decision once and communicate it explicitly.

Integrate in a controlled order

Review each contribution against its brief, then run the combined checks after integration. Two patches can pass separately and conflict when combined. Pay particular attention to duplicated imports, changed paths, incompatible data shapes and links that point to a route another task renamed. Keep the branch history and review notes clear enough to isolate a regression. Do not assume a summary from one agent establishes that another agent's dependent work is still correct.

Use human review where judgment matters

Content claims, external messages, spending and access changes need an owner who understands their consequences. A workflow should make those decision points visible and provide a concrete draft or proposed action for review. Agent Studio is the linked workspace for building and reviewing agent workflows. Begin with one repeatable job, inspect the outputs and exceptions, and expand only after you can explain how a failed or incomplete run will be noticed and recovered.

Where the agents run

The method, published