Dakota Radigan
I turn emerging AI capabilities into products, workflows, and systems people actually use.
Ask my AI about my work.
What I do
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.
Explore my work your way.
Same underlying experience. Different interfaces.
Things I've built.
Side projects, built for fun — separate from the AI I build at work.
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.
https://www.dakotaradigan.io/mcp
your AI clientget_resumestructured career datayour AI reasons
Under the hood
Hybrid retrieval
Semantic + lexical search to find better context.
Model routing
Use the right model for the question.
Evaluations
Human-grounded testing instead of vibe-based evaluation.
Guardrails
Validation, quotas, fallbacks, and production safety.
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