Turned ecosystem signal into diligence, founder conviction, and product judgment.

The role sat at the edge of market sensing and operator logic: track early shifts, evaluate founder quality, and translate research into better investment and product thinking.

Focus

Founder sourcing, diligence, market intelligence

Markets tracked

MCP, RAG, vision, LLM tooling, AI infrastructure

Anchor result

15+ founders supported with product and strategy feedback

Discuss This Work Back to Case Studies

Situation

AI markets were moving fast, and surface-level noise was everywhere.

Sourcing and diligence needed sharper filters than social excitement. The useful work was separating momentum, technical feasibility, and actual product relevance.

Approach

Use operator logic to make venture judgment more concrete.

Evaluated early-stage AI startups through product, infrastructure, and GTM tradeoffs.
Built ongoing market intelligence on emerging protocols and tooling shifts.
Worked with founders on product roadmaps, MVP framing, and strategic pivots.

Outcomes

The work improved sourcing quality, founder support, and speed of conviction.

15+

Portfolio founders supported through roadmap refinement and strategic feedback.

4 domains

Active intelligence maintained across MCP, RAG, vision, and LLM workflows.

1 lens

Investor thinking grounded in operator reality rather than abstract trend chasing.