See the supported use cases, install workflow skills, and follow the setup docs.
AI coding tools can help with complex applications when work is divided into changes a person can specify, inspect, and verify. They do not remove the need for architecture decisions or integration ownership. A reliable workflow makes those responsibilities visible and gives each tool call enough context to complete one bounded task.
Start with requirements the team can revisit
Write down the user outcome, constraints, and acceptance criteria before asking for implementation. Include relevant interfaces, data ownership, failure behavior, and decisions that should not change. Keep this record outside a chat session so another person or agent can recover the intent later. Resolve ambiguous requirements before dependent changes are built on an assumption.
Break the project into verifiable changes
Split work around an outcome that can be reviewed and tested, such as adding one API behavior or updating one user flow. Record dependencies explicitly. Work spanning database design, authorization, API behavior, and interface states may need several steps. Each step should have enough context to make sense and a check that can exercise its result.
For a new export flow, one task can define workspace access and the response contract, another can implement the data query, and a third can connect the user interface. Write the contract and permission rule before splitting the work so each change fits the same design. Agree on the input and output shapes at the boundary, then integrate the pieces with a check that exercises the full request path. This gives agents separate tasks without losing ownership of the feature.
- Give each task an owner. A human remains accountable for integration, even when an agent prepares the change.
- State what must stay stable. Name public contracts, permission boundaries, and data invariants.
- Define the check first. Specify expected behavior and the relevant test or review before implementation.
Implement, review, and integrate in short cycles
Ask the tool for a focused change and a concise account of its edits. Inspect the diff for changes beyond scope, then run checks tied to the acceptance criteria. Review security-sensitive and architectural choices directly; a passing test cannot decide whether a product requirement was interpreted correctly. Integrate after the responsible reviewer can explain what changed and what evidence supports it.
Keep context useful across sessions
Provide the agent with the issue, relevant design notes, files or symbols, constraints, and exact check command. At handoff, record the current state, decisions, files changed, checks run, and unresolved questions in the durable work item. This lets the next session continue from project facts rather than reconstruct a long conversation.
Judge the workflow by what can be checked
A completed task should leave a clear trail from requirement to change to check. That trail does not prove every behavior is correct, but it makes review more concrete and gaps easier to route. Start with one workflow, learn where handoffs lose intent or evidence, and improve that part before expanding across a codebase.