Three evidence levels keep an AI guess from being presented as a business fact.
Your AI works. Is the system ready for production?
The model is only one component. YakData helps senior engineers turn working AI into production systems teams can trust, operate, recover, and own.
Built around 77 Rules: a real production AI system, not a hypothetical course project.
Does this look familiar?
The prototype is working. The production decision is not.
- The demo works, but nobody can define production-ready.
- The model performs well, but failure behavior is barely tested.
- The screen, behind-the-scenes logic, AI, and product work each move separately.
- Nobody is certain where human judgment belongs.
- Release is approaching, but nobody is sure what happens when it fails or who owns it.
What 77 Rules made obvious
The model was not the hard part.
A production AI system has to turn perception into evidence, controlled logic, a reviewable decision, and an operating result.
AI supplies evidence. Business-critical scoring follows visible rules that produce the same result from the same inputs.
Client-specific rules fit the core architecture, and the system was used to change reporting practice after handoff.
The FDE Production Map
Seven decisions. Five responsibility lanes. One production system.
These seven decisions show where a production AI system stands and what has to happen next.
The FDE keeps the lanes connected. They overlap from the beginning. This is not a neat PM → UX → backend → frontend → QA sequence.
See the method applied
Follow 77 Rules through the full production build.
FDE Lab is free. Follow 77 Rules through all seven production decisions, from definition through ownership.
Define it correctly.
Decide what deserves to be built. Turn expert judgment into requirements. Design the production system and the work.
Decision · Requirements · ArchitectureProve it works.
Build the smallest complete path through the system. Test the AI on real examples, deliberately test how it fails, and make human review explicit.
Vertical Slice · EvaluationMake it production.
Make the system reliable, release it, prove it can recover from failures, transfer ownership, and decide what should happen next.
Production · OwnershipFollow the FDE Lab
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Apply it to your own work
Now put your system under the same scrutiny.
Bring one real piece of your system and one consequential decision. We challenge the assumptions, evidence, how the system can fail, and what that means when real users depend on it. You retain ownership of the build and leave with the next action.
$1,500 / quarter- Weekly live Production Reviews
- Bring work from any of the seven production decisions
- Written Production Review Record for substantive reviewed work
- Reviewed does not mean passed
Why this standard exists
Built from production work, not certification theory.
Built the subscriber lifetime-value framework and worked on business problems spanning Finance, Marketing, and Operations.
Director of Product Management. Conceived the native forecasting engine and worked on advanced data-ingest and management flows.
Across clinical-trial data, enterprise BI, product leadership, analytics, software systems, and production AI.
Stephen looks at what the business needs and works back to the technology. This insight is invaluable for improving ROI and driving quick wins from the analytical investment.John LodmellCFO, Nordstrom Credit Services
