Get more out of the models you are allowed to run
Policy, residency or the hardware you own usually decides which model you run. What makes its output worth acting on is what happens after generation.
A single completion is a guess with good grammar
A served model answers once. Whether it compiles, passes, or quietly does nothing are questions the model cannot settle. A person settles them, by reading.
A better model moves the odds. It does not remove the step.
The gap closes after generation, not during it
Alternatives, not one answer
The first answer is not reliably the best one, and generating several costs attempts rather than accuracy.
Your checks, not a benchmark
Candidates run against the compilers, linters and tests your project already has.
Effort matched to difficulty
A scorer reads the serving model’s own embeddings and hidden states and sets the reasoning budget and candidate count per task.
What runs between the request and the answer
Proposal
The change your agent proposes enters the write path as candidate zero, the baseline.
Alternatives
Several candidates are generated instead of the first answer being accepted.
Execution
Each runs in an isolated sandbox against the project's available checks and the runtime's own oracles.
Guarded write
An alternative must earn authorization to replace the baseline. What did not earn it carries no verification metadata.
Failures return to step 02 as repair input rather than starting over
Proposal, alternatives, execution, guarded write, with repair feeding back.
Where a permitted model changes the answer first
Well-covered services
- The work
- Implementing changes in a service with a real test suite.
- What repeats
- The suite already encodes the behaviour. Each change is re-derived by hand anyway.
- What changes
- Candidates are executed against that suite before anyone reads them, and what each demonstrated is recorded.
Cross-file refactors
- The work
- Changes that touch definitions across several files.
- What repeats
- Calls that resolve to nothing in scope are the classic silent failure, and they read as correct.
- What changes
- Candidates whose cross-file calls resolve to no in-scope definition are rejected outright.
Work that looks done
- The work
- Changes that run cleanly without implementing the task.
- What repeats
- Code that executes while doing nothing useful survives review more often than a visible failure does.
- What changes
- That class is rejected as its own category rather than passed through as a success.
Other solutions
Run AI coding where the data is not allowed to leave
Every part of the system inside your jurisdiction, with no vendor-operated component in the path.
Read the solutionGive the teams that had to go without an approved path
Whole units have gone without AI assistance because no approved path existed. This is one.
Read the solutionTalk through your deployment constraints
The repository and the docs need no form. This one scopes a deployment.