Governed AI product work
I turn AI-assisted design work into usable training products.
I frame messy training problems, govern AI as a production system, build the supporting tools, validate the result in execution, and iterate from evidence.
Flagship proof CADE
A compressed staff-training problem became a repeatable controller-facing exercise product.
Execution evidence Three live runs · about 19 participants per session
The first executable version was produced in one week and then improved from execution evidence.
Product outcome Unified Controller Package
The system evolved toward a reusable runtime package instead of fragmented one-off artifacts.
How I Build
Read methodsProject proofs
View allCADE is the capstone. The controller-package pipeline and production support tools show the system behind it: source governance, repeatable workflows, review gates, and runtime usability.
Featured
Ongoing
CADE — Combined Arms Decision Exercise Turned a compressed battalion staff-training problem into a usable, repeatable exercise product. A two-person team produced the first executable version in one week; CADE has now run three times with about 19 participants per session. View case study Ongoing
CADE Production Support Tools Built support workflows that remove CADE production blockers when units arrive without complete graphics, annexes, or briefing materials. View case study Ongoing
CADE Controller Package Generator Built the core production pipeline that turns an OPORD into the five-document Controller Package used to run CADE, with source traceability and trainer review preserved across every turn. View case study Project Proof Format
See it appliedEvery project should prove the same six things quickly, then push domain-specific detail lower on the page.
CADE as flagship proof
Read CADECADE shows the full claim in one project: a compressed requirement became a usable exercise product through governed AI workflows, supporting tools, live validation, and evidence-driven iteration.
A two-person team produced the initial executable CADE in one week.
CADE has run three times with an average of about 19 participants per session.
Four validation criteria were met on the first execution: staff operated inside the structure, controllers executed with delivered artifacts, consequences created pressure, and review captured learning.
Fragmented first-run artifacts led directly to the unified Controller Package architecture for later versions.
AI Operating Decisions
View allThe decision records show how AI was governed: where it accelerated production, where it was constrained, and where human judgment stayed authoritative.
Use AI as the production engine, not the design authority CADE required fast production of research, planning artifacts, turn content, and controller materials, but the training effect depended on human judgment about purpose, boundaries,... Read decision Change CADE only when evidence justifies changing the system A reusable training framework needs stability. If every execution creates ad hoc changes, the core training effect erodes and future adopters cannot tell which parts are canonical. Read decision Make the Controller Package the runtime center of gravity A CADE event succeeds or fails in execution. Controllers need to find prompts, role guidance, adjudication aids, timing cues, and review structure under pressure without relying on... Read decision Use deterministic adjudication bands tied to observable behavior CADE depends on consequences that feel credible to participants and repeatable to controllers. If outcomes depend too heavily on individual controller judgment, different controlle... Read decision Anchor CADE artifacts to OPORD-quality source truth CADE produces multiple downstream artifacts: scenario materials, turn prompts, controller aids, decision products, briefings, and review structures. Without a governing source laye... Read decision Use plain-language and visual-forward delivery CADE may be executed with mixed-language audiences and uneven doctrinal familiarity. Dense phrasing and text-heavy products can slow comprehension, disrupt timing, and create avoid... Read decision
Talk about governed AI training products
Reach out to discuss CADE, AI-assisted training design, or production systems built for real operational constraints.
vincent.taijeron@gmail.com