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Startup founder, operator, advisor · PipelineAI -> AWS/Databricks/Netflix · Claude startup activation · 3x O’Reilly author · ~500K DeepLearning.AI learners
I've been on all three sides of the startup table: founder (PipelineAI, a production-AI platform), operator (AWS, Databricks, Netflix), and advisor to a number of AI startups, from frontier-model training labs to AI performance and infrastructure. Across that arc I've reached thousands of startups and worked closely with 50+ teams on LLM adoption and production architecture - founder days, build-a-thons, workshops, office hours, across YC, Techstars, Redpoint, and a16z portfolios. AWS was the biggest single chapter of that. The advisory bench keeps it growing. The rule was simple: every event ends in working code. PipelineAI taught me platform risk the hard way. That scar tissue is now the most useful thing I bring to founders: Ask whether the wedge survives platform gravity. I teach in public: 3× O'Reilly author, ~500K course learners (Generative AI with LLMs), a 100K-member meetup community (20 AI Performance Engineer groups worldwide), a ~96K-subscriber newsletter, and 200+ talks in recent years. I also build in public with Claude: claude-founder-kit builds a startup end to end in one repo, from the first API call to the data moat, plus standalone deep-dives for grounding, memory, parallelism, and Managed Agents. github.com/cfregly
Northwestern University
AI and Machine Learning
N/A – Present
San Francisco
AI Startup Advisor, Chief Pitch Officer
January 1, 2024 – Present
San Francisco, CA
AI Performance Engineering
3x O'Reilly Author and Mentor
January 1, 2024 – January 1, 2026
San Francisco, CA
Amazon Web Services (AWS)
AI Startup Advisor, Product and Engineering Leader
January 1, 2019 – January 1, 2024
San Francisco, CA
PipelineAI
AI Startup Founder and Chief Product Officer
January 1, 2015 – January 1, 2019
San Francisco, CA
Databricks
Engineering and Product Leader
January 1, 2013 – January 1, 2015
San Francisco, California
Netflix
Engineering Leader and Principal Engineer for Streaming (Emmy-Award Winner)
January 1, 2011 – January 1, 2013
San Francisco Bay Area
Product Management Certificate
Product School
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse experience across startups, large tech companies (AWS, Netflix, Databricks), and their role as an author/mentor suggests a strong adaptability and a proactive learning mindset. Their involvement in open-source projects and community building aligns well with a collaborative and knowledge-sharing culture. The focus on innovation, product-market fit, and high-performance systems indicates a drive for impact and excellence, which is generally a good cultural fit for fast-paced, technically demanding environments. The extensive experience in advising startups and building developer communities also points to a strong ability to foster growth and innovation.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership, mentorship, and communication skills through their roles as an author, advisor, and educator. Their experience in building and scaling teams, influencing product roadmaps, and engaging with developer communities suggests excellent operational fit for roles requiring strategic thinking, collaboration, and technical advocacy. The emphasis on performance optimization and problem-solving indicates a results-oriented approach.