Why Ad Actum Exists
AI-assisted tools can shorten the time required to produce a software change. They do not remove the work of understanding how that change affects the rest of a system.
A change can satisfy a ticket and pass the available tests while still weakening an authorization rule, leaving stale data behind, duplicating lifecycle logic, or increasing coupling between parts of the codebase.
These are not problems created by AI. They are ordinary software problems that can accumulate faster as the volume of change increases.
Linters, tests, and code review remain essential, but each answers a limited set of questions. They do not always show whether a change crossed an ownership boundary, introduced an inconsistent cleanup path, or made an architectural assumption harder to maintain.
Ad Actum focuses on that gap.
The service reviews a defined area of a codebase against a specific concern. Depending on the scope, that concern may be architecture and lifecycle, reliability, or security. The review follows behavior across modules, data flows, and trust boundaries instead of treating a pull request as an isolated artifact.
The work is structured around three practical outputs:
- Prioritized findings supported by references to the relevant code
- A bounded remediation plan with clear acceptance criteria
- When implementation is included, a pull request for the team to review
Ad Actum does not replace tests, code review, or the engineers who own the system. It provides a focused second pass for situations in which a team needs to understand a risky change or a subsystem that has become difficult to reason about.
Ad Actum is still at an early stage. I am starting with narrowly scoped reviews and doing the work directly. This keeps the scope clear and allows the service to develop around concrete engineering problems rather than broad promises.
If you have a specific repository, subsystem, or risk area you would like reviewed, request a scoped review.