Move your mouse or drag across the portrait to turn Dakota's head. When focused, use the arrow keys; Home returns to center. Reduced motion keeps the portrait still.
AI Strategy, Senior Product Manager @ Morgan Stanley

Dakota Radigan

I turn emerging AI capabilities into products, workflows, and systems people actually use.

Ask about my experience

Dakota's AI · Claude + Jev · may make mistakes

Enter to send · Shift + Enter for a new line

Chats are saved for Dakota to review, anonymized, with no account or email attached to you. Pasted job descriptions aren't kept; only the analysis is.

What I do

AI strategy, product leadership, and the code to prove it.

AI Strategy

Turn new AI capabilities into practical product and operating strategies.

Product Leadership

Find the problem, define the product, align people, and ship.

Technical Builder

Prototype and build with Python, RAG, agents, MCP, APIs, and production AI systems.

Financial Services

Deep experience across investing, technology, and complex enterprise environments.

Choose your interface

Explore my work your way.

Same underlying experience. Different interfaces.

Bring your own AI

Connect a compatible MCP client and let your preferred AI reason directly over my structured resume data.

For AI agents

Built for humans. And agents.

Most resumes are documents designed for people to read. This one is also available as structured data through MCP, so compatible AI tools can evaluate my experience directly.

The MCP server doesn't run my AI assistant for you. It exposes my resume — experience, projects, skills, education, certifications — as structured, AI-readable data, and your own AI does the reasoning: comparing me against a role, mapping strengths and gaps, or preparing interview questions.

Remote MCP server · streamable HTTP · no auth
https://www.dakotaradigan.io/mcp

your AI clientget_resumestructured career datayour AI reasons

Connection instructions →
Under the hood

Honest answers, by design.

Hybrid retrieval

Semantic + lexical search to find better context.

Typed judgments

Jev picks the Claude model for each question and scores every job requirement against the résumé: probabilities, not prose.

Evaluations

Human-grounded testing instead of vibe-based evaluation.

Guardrails

Validation, quotas, fallbacks, and production safety.

Direction

Where I do my best work.

Problems where AI changes not just a feature, but how the product or workflow should work.

  • AI-native products
  • Enterprise AI strategy & adoption
  • Technical product leadership
  • AI in financial services & complex enterprise systems