“Most teams ask build or buy when they should be asking how reversible is this decision? I run a five-question filter with founders: is it core to differentiation, are requirements stable, what's the extraction cost, is the category stable, and can you maintain it long-term. More often than not the answer is buy first, learn, then build later.”
“I buy when the workflow is generic and the team can learn fast; I build when the real value sits in connector scope, review placement, and exceptions a packaged product will never absorb cleanly. The test is not the model, it is whether the system can read, write, approve, and recover inside our actual stack without creating shadow cleanup work.”
“At Meta we bought the labeling and serving stack, but built the model and review routing ourselves, because the product was the judgment of what stayed up. Buy what commoditizes, build what decides your margin.”
“At AI Creator Labs we mostly buy the AI layer and build the glue around it, because our 10,000 creators care more about a workflow that actually pays them than about a model we trained ourselves.”
“At Industrial AI, I bought the LLM layer and vector search and built the agentic reasoning around factory repair workflows myself, because the product edge was in how the tool asked the right follow-up question to a maintenance tech, not in the model itself. Buy what is already a commodity, build what makes your customer feel like you read their mind.”
“I buy the plumbing and build the differentiator. At Stride we run on managed streaming and LLM APIs so the team can focus on the sub-second market-data layer that actually protects our traders, and that discipline is why we hit half the typical burn rate.”
“I buy the commodity layer and build the parts that touch proprietary data and regulatory judgment. At STEM Lending we bought LLM APIs and vector search, but built the mortgage-specific retrieval, abstention logic, and NMLS-grounded fact pipelines because frontier models hallucinated on long-tail brokers.”
“I start with an API key for speed, then move to managed hosting or self-hosted inference once the bill becomes a line item. At TVT we self-hosted chat and sign-in for 8,000 linguists because per-user pricing would have killed us.”
“I buy what commoditizes fast and build what moves the needle on our actual product. At MrBeast, that meant buying the obvious AI scaffolding and owning the parts that made our content, distribution, and creator tools defensible.”