Tim Gulden

Background

About Tim Gulden

Policy researcher and strategist who connects leaders and engineers to turn AI ideas into things people can use. I’m known for quickly mapping how organizations actually work, asking the right questions early, and turning that clarity into solid decisions. I pair this with hands-on literacy in AI (LLMs, evaluation, retrieval) and research discipline—I test assumptions with data so we’re working from analysis, not impressions. This era is too interesting to be writing reports - let's do things together. What I bring Understanding: Rapidly synthesize org structure, incentives, data flows, market position, and constraints; surface the few questions that change the plan. Decision quality: Frame risks, trade-offs, and release criteria so leaders can move faster with confidence. Bridging roles: Translate between executives, clients, and engineering; align policy, product, and operations. Analytical depth: Geospatial (GIS), agent-based and system-dynamics modeling, and LLM-enabled workflows—used to validate narratives and de-risk choices. On-the-spot clarity: I know what I know right away and am comfortable in high-stakes meetings and complex decision discussions. Trust: I have directly advised generals, admirals, and other top officials on sensitive and important matters. Scale of current position: led project teams of 5–25 people • owned budgets $150K–$750K as PI • major team lead within RAND’s $37M/year engagement on a multi-billion-dollar FEMA program. Briefed senior military and civilian government decision-makers. Selected outcomes: standardized FEMA claims evaluation (including a support chatbot) adopted at the federal level; led an early RAND effort to build a full-scale AI literature-review tool with hallucination-resistant methods, shaping internal direction; LLM-driven social simulation enabling scenario testing and policy insight; document-intelligence workflows (retrieval-augmented review plus semantic/visual exploration) that sped research and informed product roadmaps. Breadth: Comfortable moving across technology, security, public services, infrastructure, and global systems—from generative AI to global food security—and into hands-on product work. Focus areas: Responsible AI & governance • evaluation & measurement • model/data governance • human-in-the-loop • AI policy & partnerships • long-context prompting • RAG & tool use • ABM & system dynamics • policy gaming & simulation • technical communication.