Educational guideUpdated
How to build an AI agent backend from an approved specification
In brief
Build an AI agent backend by defining the business outcome and API contract first, approving that specification, generating an inspectable layered artifact, validating the exact version, and then choosing a download or deployment preflight. This keeps the backend aligned with the requirement and makes the evidence part of the handoff.
System map
Keep the decision system separate from the runtime.
Control plane
Decide what to build
- Business outcome
- API contract
- Human approval
Generated runtime
Own what runs
- Layered source
- Version evidence
- Handoff choice
Backend anatomy
What an AI agent backend includes
An agent backend is more than a model prompt. It includes the API surface, typed data contracts, workflow or decision logic, actions against external systems, failure handling, runtime files, and the tests or validation evidence used to judge that version.
The control plane that specifies and generates the project should stay separate from the generated runtime that serves the API. That boundary lets a team inspect, download, deploy, and operate the artifact without presenting the generation system as the customer runtime.
Contract
Endpoints, typed inputs, outputs, errors, and validation rules.
Orchestration
Use-case flow, agent decisions, and business-rule boundaries.
Actions
External systems, failure handling, runtime files, and evidence.
Seven decisions
A seven-step, spec-first workflow
Each step closes one uncertainty before the next boundary opens. The sequence keeps business intent connected to the artifact and the evidence used for handoff.
- 01
Intent
Define the business outcome
State who invokes the agent, what decision or action it owns, and what a useful response must contain.
- 02
Contract
Write the API contract
Make endpoints, inputs, outputs, validation rules, errors, and external integrations explicit.
- 03
Gate
Review and approve the specification
Resolve ambiguity before generation. Approval is the boundary between a proposal and the contract to build.
- 04
Build
Generate a layered backend artifact
Keep endpoint transport, use-case orchestration, agent decisions, and external actions separable enough to inspect and change.
- 05
Proof
Validate the artifact version
Tie validation evidence to the generated version instead of treating a previous run as proof for changed source.
- 06
Revision
Edit through a new version
When requirements change, preserve the approved contract and produce a traceable artifact revision.
- 07
Handoff
Choose download or deployment preflight
Hand over the source artifact, or verify that the selected deployment lane is configured and ready before claiming a live endpoint.
Proof package
Validation evidence to capture before handoff
- Evidence 1: The approved specification and the artifact version it produced.
- Evidence 2: Generation status and any failure that prevented a complete artifact.
- Evidence 3: Automated validation results for the exact artifact version.
- Evidence 4: The input/output contract the receiving team can inspect.
- Evidence 5: Changes introduced by later edits and the new version identifier.
- Evidence 6: A downloadable artifact or a truthful deployment-preflight result.
Evidence boundary
What not to claim before deployment
A generated artifact is not proof of a live service. A passing validation run is not proof that credentials, provider configuration, networking, and a deployment lane are ready. Treat those as separate evidence boundaries.
If preflight is blocked, report the missing prerequisite and keep the download path available. For a concrete contract, continue to the lead enrichment example.
Generated artifact
Source exists and the exact version can be validated.
Live service
Credentials, networking, and the selected lane must still pass preflight.
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Related resources
Move between the agency workflow, implementation guide, proof, reference scenarios, and comparison.