Lessons from Nathan Baschez

Nathan Baschez is a writer and product builder who co-founded Every and built Lex, applying traditional business strategy to modern media and the creator economy while exploring competitive advantage and AI’s role as a creative partner.

Lessons from Eric Newcomer

Eric Newcomer is a tech reporter who built an independent Silicon Valley media business through Newcomer, examining how venture capital works, how power shifts between founders and investors, and how the economics of tech journalism operate.

Lessons from Ed Sim

Ed Sim is founder and general partner of Boldstart Ventures, specializing in inception-stage funding for technical enterprise founders before incorporation and studying product formation, early hiring, the autonomous enterprise, and venture capital strategy.

Lessons from Ali Afridi

Ali Afridi is a venture capitalist focused on digitizing legacy industries such as insurance and manufacturing, exploring startup ideation, market cycles, and system-of-record software while using SandHill.io to aggregate investment theses and market opportunities.

Lessons from Mario Gabriele

Mario Gabriele founded The Generalist, combining long-form journalism’s narrative depth with venture capital analysis, and developed it into a standalone media property and venture fund while studying early-stage founders and modern business mechanics.

Lessons from Jamal Reimer

Jamal Reimer is an enterprise sales veteran who created the Two Mountain model and Executive Whispering to systemize major deals, focusing on executive access, business-value conversations, and the disciplined work of closing multimillion-dollar agreements.

Lessons from Jamin Ball

Jamin Ball is an Altimeter Capital partner and author of Clouded Judgement who translates public-market data for private founders, clarifying how software valuations shift across macroeconomic cycles and what growth efficiency, AI infrastructure, and core metrics reveal.

Lessons from Jordan Crawford

Jordan Crawford, founder of Blueprint GTM, treats B2B outbound sales as an engineering problem, replacing generic buyer personas with public data that identifies specific company pain and enables highly targeted, automated account research.

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