Find the real workflow
Interview users, inspect artifacts, and surface the tacit rules that do not appear in the request.
Arthur Shafer · Forward-deployed AI / Enterprise systems
I turn ambiguous domain problems, fragmented data, and tacit expert workflows into evidence-grounded AI systems that people can actually use.
Selected systems
These systems begin with fragmented evidence, hidden workflow rules, regulated users, or an unfamiliar operating environment—and end as software people can interrogate, evaluate, and run.
A statewide campaign research and strategy workspace connecting public records, elections, geospatial voter-roll intelligence, candidate dossiers, money, public decisions, and an evidence-native agent.
What you'll see: statewide map · representative dossier view · evidence-bounded agent answer
A production federal opportunity-intelligence system evolved into a durable enterprise agent architecture with contracted tools, corrective retrieval, evaluation, and authorization built into the runtime.
A repeatable pipeline turns solicitations into working demonstrations, technical packages, and deployment-ready software across corrections, public services, justice, and assessment workflows.
A public, source-aware Orthodox study product built on a retrieval engine, domain-profiled corpus, conversational application, durable threads, and protected edge/origin deployment.
Serverless products for contractors and professionals: customer provisioning, identity, billing, structured AI document workflows, hosted sites, and usable business software.
How I work
Forward deployment is a continuous loop between domain experts, evidence, product decisions, software, and the constraints of the target environment.
Interview users, inspect artifacts, and surface the tacit rules that do not appear in the request.
Define sources, identity, authority, freshness, claim limits, and the tools the agent is allowed to use.
Ship the smallest real workflow, observe failures, add regression and adversarial tests, then widen deliberately.
Package the runtime, identity, observability, runbooks, and decision history so another team can own it.
Enterprise credibility
My path runs from Army intelligence through enterprise transformation and aerospace systems to governed AI delivery. The thread is translating consequential work into systems people can act on.
Active TS/SCI clearance · 15 years across intelligence, enterprise architecture, technical delivery, and AI product building.
February 2019 – present
May 2026 – present
Enterprise architecture, technical program leadership, and national-security software delivery.
December 2017 – February 2019
Senior Consultant, Technology and Innovation: modernization, requirements, and business-to-engineering translation.
June 2017 – October 2017
Business Systems Analyst intern: enterprise systems analysis and implementation support in a high-velocity engineering environment.
January 2011 – June 2014
Intelligence Analyst, 82nd Airborne Division: all-source intelligence, operational planning, and decision support.
Ask about the work
The assistant retrieves from a versioned set of approved public claims, routes the question, shows the evidence it selected, preserves caveats, and links each answer back to the work.