#142 Why LLMs Need Their Own Programming Language: From Assembly to AI with Vaibhav Gupta // Co-founder @ BAML

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#142 Why LLMs Need Their Own Programming Language: From Assembly to AI with Vaibhav Gupta // Co-founder @ BAML

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Sponsored by Blocks: Save at least 20% on your AWS costs with AI-powered optimization and enterprise discounts. Get your free Cloud Check at blocks.cloud/alphalist → https://blocks.cloud/alphalist?utm_source=alphalist&utm_medium=podcast&utm_campaign=blocks-podcast-2026 Vaibhav Gupta built computer vision for the original Microsoft HoloLens, optimized AR at Google, and wrote high-performance assembly at D.E. Shaw, then left it all to start from scratch. After a YC pivot away from a Slack competitor he was told not to build, he landed on something foundational: BAML, a programming language for a world where humans increasingly don't read code. His thesis: every software leap came from a new compute paradigm getting its own language assembly, C, Java, JavaScript and LLMs are the next primitive. They're probabilistic and non-deterministic, which breaks our deterministic tooling. In this episode, Vaibhav explains why "shipping at agent speed" is really a problem of trust and control, why 90% of engineering is plumbing AI will delete, why "English as a programming language" can't work, and why the world has a mathematically infinite appetite for software. Topics covered: - Why LLMs are a new compute primitive and why that justifies a new language - BAML: an embedded, type-safe language for structured LLM outputs across any language - Shipping at agent speed as a problem of trust, locking, and granular control - Why traditional CI/CD breaks in an agent loop - The "data trench" one type system across code, backend, and data - Why 90% of engineering is plumbing, and what changes when AI removes it - Where SaaS pricing and product models are heading

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