Current capability you can inspect
The point of the lab is simple: current AI and architecture capability should be visible in working systems, not only described in a resume or slide deck.
Current Proof Bench / R&D Station
Current AI capability you can inspect.
This is the working R&D station behind my current AI systems work: production AI-native platforms, methodology engines, media workflows, and client-context document intelligence that show how I move from operating problem to architecture to working system.
The current proof bench is deliberately narrow: CriticalThink HR, CriticalThink Advantage, SpectraCastr, and SCMS / SCMS 2.0. Earlier founder/operator and enterprise work—including HRTrainingClasses, Charter, Wells Fargo Advisors, and Centene—belongs on the Work page as career history, not as current lab inventory.
Products plus client-context proof
CriticalThink HR, CriticalThink Advantage, and SpectraCastr show current product and workflow patterns. SCMS / SCMS 2.0 shows those patterns transferring into a long-running client-owned environment.
Architecture through production
The proof bench spans methodology, AI workflows, structured data, document intelligence, media operations, batch processing, evaluation, UX, integrations, and production support.
Economics matter too
Batch-processing optimization, multi-provider model selection, and AI-enabled workflow design reduced CriticalThink HR content-pipeline cost by 50%, making ROI and TCO part of the architecture—not an afterthought.
Current AI-native platforms
CriticalThink HR
A production AI-native HR-certification platform that turns expert judgment and situational reasoning into a structured learning and readiness system.
What it proves
Expert knowledge can become governed product logic, scenario feedback, analytics, content operations, and scalable learning workflows without losing the need for human judgment.
CriticalThink Advantage
The methodology engine behind CriticalThink: a structured approach for turning high-stakes expert judgment into explainable decisions, workflows, and product logic.
What it proves
Tacit decision logic can be formalized into repeatable methodology, software rules, training, governance, and operating workflows.
SpectraCastr
SpectraCastr began as the media system CriticalThink HR needed for training walkthroughs, videos, marketing assets, and LinkedIn carousel/slideshow content. It is not generally available yet; public access opens in stages.
What it proves
An internal AI-enabled production need can be abstracted into a repeatable workflow and hardened into reusable system capability.
Client-context proof
SCMS / SCMS 2.0: document intelligence at scale
SCMS is the original 2010 sports contract management system. SCMS 2.0 is the AI-powered modernization: it processes contracts, addendums, and amendments in batch, uses AI-assisted analysis to extract contract intelligence, and turns that output into structured data that can be searched, queried, reported on, and used to support contract workflows.
- Batch ingestion of contract documents, addendums, and amendments
- AI-assisted extraction into a structured contract repository
- Search and query workflows across agreements, seasons, schools, and compensation terms
- Data workflows connected to USA TODAY college coaches salary reporting
The important signal is not the stack, though SCMS 2.0 runs on C# / Blazor / .NET Core 8 / Vertex AI / Document AI. The signal is the pattern: modernize a long-running operating system, turn unstructured contracts into a reliable data layer, and add AI without losing inspectability or workflow context.
Public-safe boundary
SCMS / SCMS 2.0 supports data workflows connected to USA TODAY college coaches salary reporting. That does not imply ownership of USA TODAY's public reporting product.
Why keep a proof bench at all?
Because current AI capability changes too quickly to live only in old project descriptions. The lab keeps me working against real model behavior, production constraints, cost tradeoffs, evaluation, data architecture, workflow design, and user experience.
A hiring manager or client should be able to inspect current systems and see the architecture, judgment, and execution behind the AI claim.
Proof screenshots
Current systems, not portfolio theater.
These public-safe views show working patterns for document intelligence, training systems, methodology products, and media operations.
SCMS 2.0 contract intelligence
Client-owned document workflows turned into searchable contract intelligence and reporting support.
CriticalThink HR readiness system
Expert HR judgment converted into structured training, explanation, and readiness workflows.
CriticalThink Advantage methodology
Decision methodology packaged into a repeatable operating model for high-stakes judgment.
SpectraCastr media workflow
Training walkthroughs, videos, marketing assets, and LinkedIn carousel/slideshow content prepared through staged-access media workflows.
Want to discuss the architecture behind the systems?
I welcome senior role, contract leadership, and high-fit consulting conversations where current AI systems capability matters more than buzzwords.
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