Ryan Wexler

Principal

Ryan joined SignalFire in 2024 to help build the next generation of great infrastructure companies. He spends his time working with highly-driven founders at seed and Series A stages with a heavy focus on AI/ML, data infrastructure, and cybersecurity. Ryan splits his time across both New York and San Francisco.

Prior to Signalfire, Ryan spent the last 8 years as an investor at Unusual Ventures and Dell Technologies Capital. Before venture investing, he had worked as a data engineer at Magnetar Capital back during the Hadoop era. Ryan received his BA in Economics and Computer Science from Northwestern University.  

Outside of work, you can find Ryan going for long runs along either the West Side Highway or Embarcadero, hiking in Northern California, or testing out various coffee brewing methods.

Ryan Wexler

Ryan Wexler's Posts

July 13, 2026

Save the trace - Why AI agent trajectories are your most valuable assets

Don't delete your AI agent traces. Learn why agent trajectories are critical data assets for enterprise LLM monitoring, security, governance, and fine-tuning. Consider traces as a first-class data asset, and treat them with the same respect as your system logs, CRM, or data warehouse.

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May 4, 2026

Moats are for castles: A new argument for permanence over defensibility in AI startups

Stop manufacturing premature moats. This post argues that AI startups should prioritize permanence over defensibility. Learn why real moats are earned by solving persistent problems that endure even when intelligence is a cheap commodity. (188 characters)

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February 18, 2026

The missing layer in Enterprise AI: Why we invested in Solid

Solid raises $20M to solve enterprise AI’s context problem, building a trusted semantic layer that makes AI agents accurate, reliable, and production-ready.

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November 4, 2025

Why expert data is becoming the new fuel for AI models

As the open web runs out of usable data, the next frontier of AI training lies in expert knowledge. Learn why the future of AI depends on high-quality, domain-specific data and how startups curating expert workflows are becoming the new power brokers of the AI economy.

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