Frame the input
Specify the problem, origin of data, usage rights and research question.
METHOD / CONTROLLED AUTONOMY
Technology only becomes dependable when its limitations are understood and the findings can be independently reproduced.
We are building a foundry with spending limits, stable contracts, independent testing and safe rejection. These safeguards are not magical features of a language model; they require deliberate engineering.
01 / EXPERIMENT LOOP
No local technical result silently authorizes an external step.
Specify the problem, origin of data, usage rights and research question.
Record the hypothesis, strongest baseline, test method and limits.
Run a bounded workflow and preserve input and computation versions.
Return PASS, REJECT or STOP and assess the separate economic gate.
02 / SAFETY PRACTICES
The right to refuse unsafe or uneconomic work is an architectural feature.
If data, costs, rights or contracts are unknown or invalid, the process stops instead of filling gaps with guesses.
The evaluator cannot revise the task after seeing a result or treat an executor's report as proof. It rechecks declared thresholds and alternatives.
No unrestricted model calls or autonomous payments. Expected expense must be known before authorization and included in net-economics assessment.
Separate synthetic, owned and possible client data. Review the legal status of code, models, source material and any derived results.
03 / RELEASE READINESS
Passing a unit test on fictional records is not evidence of customer demand or safe production operation.
04 / CURRENT LIMIT
Current work validates typed workflows, limited research scenarios and negative tests. It does not replace legal review, independent market validation or authorization for commercial deployment.