Definition
TAM (Total Addressable Market)
Total addressable market.
From the episode “How Gelu Sulugiuc Built AI Workflows That Beat Bloomberg by 47 Seconds”How founders on the podcast use it
Total addressable market. North America alone holds over one hundred thousand veterinarians, before adding equine, livestock, and international.
From Apple To Animals: The Pivot That Built A 6-Continent AI Company In 30 MonthsThe full revenue opportunity available to a product. Tim jokes that Kiteworks' TAM is "anyone with a pulse and a company."
Jazz Fusion in the Agentic EraHear it on the podcast4 episodes
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Related terms in Startups & Fundraising
Solo GPA venture investor running a fund alone, part of Tim's current raise strategy.Sourcing ModelThe traditional growth equity approach of hiring teams of analysts to proactively cold-outreach to founders who haven't raised yet.Strategic InvestorAn investor who brings something beyond capital - usually industry access, customer relationships, or operational expertise.Sweat EquityValue contributed to a company through founder and team labor rather than capital investment. In a bootstrapped company, sweat equity is often the primary funding mechanism — founders and early employees accept below-market compensation in exchange for ownership stakes, betting that the long-term equity value will exceed what they gave up.Tech Moat CollapseThe erosion of competitive advantages historically held by companies with large engineering teams. Before AI, a complex software product - a marketplace, an enterprise workflow tool, a regulatory processing system - required years of development by teams of ten or more engineers. That development time and cost created a moat: by the time a competitor could build a comparable product, the first mover had relationships, data, and distribution. AI has collapsed this dynamic: a marketplace that took two to three years and ten engineers can now be built in twenty-eight days with one engineer. The moat no longer comes from the ability to build complex software - it comes from distribution, customer relationships, proprietary data, and the ability to deliver outcomes reliably. Brennan's corollary: service industries that assumed software complexity would protect them from disruption are now exposed.Technical Co-Founder as a ServiceA fractional or consultancy model providing CTO-level technical leadership on an ongoing basis — architecture decisions, development execution, AI implementation, scaling guidance — without the full-time equity and salary cost. Serves two main client types: existing digital businesses with growing pains (architecture can't handle scale) and new founders building MVPs (deciding what to build, what belongs in v1, what's reasonable scope). AI has made this model more productive: the same team now ships what previously required a larger headcount.The AI Infrastructure Moat ProblemThe existential risk for AI tool startups: foundation model providers (OpenAI, Google, Anthropic) can add a capability in a single product update that renders a wrapper tool irrelevant overnight. OpenAI recently shipped a lightweight Photoshop integration; Google adds Gemini features constantly. The moat question every AI infrastructure investor must ask: what survives a model provider copying the core capability? Defensible answers: depth of workflow integration (high switching cost), proprietary training data or process, and accumulated customer context the model provider can't replicate.The Conviction-Coachability MatrixJesse Marble's framework for evaluating founders. Both axes must score high simultaneously — conviction without coachability produces a bulldozer; coachability without conviction produces a follower.