AI-native engineering, with evidence at every step.
We design AI agents and software as complete systems. Coding agents help us implement and test; engineers maintain the architecture, review changes, and validate behavior before release.
Each decision becomes an artifact the next stage can use. Follow an illustrative invoice-review workflow through its requirements, implementation, evaluation, and release boundary.
Execution model01 / 04
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Workflow specificationExample record
Task
Review an invoice exception
Boundary
No ERP write before reviewer approval
Acceptance
Repeated approval cannot create a second bill
Follow the architecture as you scroll, or select a layer.
01
Turn the workflow into a testable contract.
Map users, source records, permitted actions, and failure cases. Record architecture decisions and acceptance criteria before implementation so people and coding agents work from the same context.
Input
Workflow, source systems, and operating constraints
Transform
Define boundaries and observable acceptance criteria
Output
Versioned brief and architecture decisions
⌑Identify the decision owner⌑Agree the first release boundary
02
Build with coding agents and engineering review.
Maintain repository context and typed interfaces. Coding agents help implement, test, and document changes. Engineers review the diff, integration behavior, and failure handling against the agreed design.
Input
Architecture, examples, schemas, and repository context
Transform
Implement, inspect changes, and exercise integrations
Output
Reviewed code with explicit tool contracts
⌑Validate model outputs against schemas⌑Keep write authority outside the model
03
Test the behavior that the workflow depends on.
Combine code tests with representative model and workflow evaluations. Inspect the traces behind failures, add regression cases, and compare results against agreed quality, latency, and cost limits.
Input
Candidate build and reviewed example cases
Transform
Run tests, evaluate behavior, inspect failures
Output
Versioned results and a release recommendation
⌑Test negative and uncertain outcomes⌑Separate model quality from integration correctness
04
Make the system operable by its next owner.
Review the release evidence, deployment configuration, and rollback path with your team. Document monitoring, escalation, and ownership so the next change follows an understood process.
⌑Unmet release criteria keep deployment on hold⌑Agree ongoing support and escalation
Engineering judgment
Different jobs need different controls.
We use models where interpretation helps and conventional code where the result must follow an explicit rule.
WorkModel contributionApplication enforcement
Understand the request
Model contributionInterpret language, retrieve context, and propose a response.
Application enforcementEnforce identity, source permissions, and the permitted tool set.
Prepare a change
Model contributionExtract fields and draft a structured proposal.
Application enforcementValidate schema, calculate amounts, and check business rules.
Execute an action
Model contributionExplain the proposed action and its supporting evidence.
Application enforcementVerify approval, bind the exact payload, and reconcile retries.
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Engineers own the implementation review. People set the operating policy, inspect consequential failures, and decide whether the release evidence meets the agreed criteria.
Delivery and continuity
A handover you can build on.
We agree code ownership, licensing, deployment accounts, and operating responsibilities before implementation. Your handover records those decisions alongside the system itself.
