01Define
Define the behavior
Name the decision or the job to be done — and what it costs you when it is wrong, late or missing.
Approach / From uncertainty to operation
Start with what can break it.
We begin with the decision the system must support, what happens when it gets that decision wrong, and the evidence available to test it.
Four stages of the work
02Constrain
Find what can break it
Find the one constraint that decides everything, the path back to the source, and the line the system must not cross.
03Engineer
Build the complete loop
Connect the model, the product, the checks, the software and the infrastructure into the smallest system that works.
04Evolve
Observe and change
Watch how it fails in real use, fix the system around the model, and keep changing it as conditions change.
An average score can conceal the mistake that makes a system unusable. We examine real inputs, likely failures, latency and cost requirements, and the decisions that depend on the output.
For Shelfr, confusing two near-identical variants could change a shelf-compliance decision. Evaluation needed to expose that confusion, even when the overall score looked strong.
Shelf recognition and release gates ↗The implementation can include perception or retrieval, application logic, web and mobile interfaces, data pipelines, cloud infrastructure, and the tools needed to operate it. We choose what the product needs and build the connections between those parts.
For ShotDeck, useful search began with film processing: selecting representative frames, preserving cinematic meaning, and making the resulting library searchable.
From source film to retrieved shot ↗We specify what a model may propose and what the surrounding software must check. Missing evidence, ambiguous intent, and invalid operations need explicit outcomes.
Biscuit AI routes intent through bounded specialists and checks required product attributes against the live catalogue. When the evidence is insufficient, clarification is part of the system’s behavior.
Controlled product recommendation ↗Intent + live catalogueRequired attributes checked
Enough evidence → recommendMissing evidence → ask or decline
Production changes the question. Data drifts, catalogues grow, vendors retire capabilities, and infrastructure costs accumulate. Evaluation, diagnostic traces, and a clear migration path help locate and correct failures.
When a ShotDeck dependency reached sunset, the work included rebuilding capabilities in-house and reprocessing the corpus while maintaining the product experience.
We agree acceptance criteria, access, escalation, and ongoing operating responsibilities with the client. Domain decisions and consequential uses remain explicit parts of that agreement.