Production AI advisory
Production decisions, failure modes, architecture tradeoffs, economics, evaluation, and operating implications. Each note is built to expose what changes when an AI system has to survive real use.
Published Field Notes
Each Field Note takes one consequential production question, shows the evidence or system design behind it, and makes the decision and production implication explicit.
A higher weekly rate can still produce a much cheaper project when role consolidation, AI leverage, and loop compression change the delivery system.
See how image-and-text AI, explicit rules, evidence checks, fixed scoring, model testing, and human review are separated inside one production-shaped system.
A seven-stage production loop from business value and context through system design, complete-path build, hardening, real users, and return to value.
Have a consequential AI decision in front of you?
Bring the architecture, evaluation, economics, context, production-readiness, risk, or ownership question. YakData will get to the governing issue, show what evidence matters, and recommend the smallest next step that moves the work forward.
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