S12 Bonus: Rickard's Deterministic Return: Converting Scattered Data into Autonomous, Production-Grade Apps with Rickard Hansson, Founder & CEO of Gainable
Summary
Ricard Hansen returns to discuss Gainable, a platform for building deterministic internal tools from data rather than prompts. He explains how Gainable uses AI to generate specs for a compiler, ensuring reliable, error-free app creation. The episode also covers the risks of relying on subsidized tokens and frontier models, highlighting the importance of proprietary infrastructure and air-gapped deployment for enterprise clients.
Topics discussed
Sponsors: .techdomains, Unblocked, Mesmo, and BrainGrid
Intro: Ricard Hansen returns to discuss Gainable and Weavey
From Weavey to Gainable: Focusing on internal tools
Deterministic AI: Using compilers instead of probabilistic coding
Data-driven design: Turning Excel sheets into apps via LLM specs
Free-range coding: Why open-ended AI prompts lead to errors
The economics of AI: Subsidized tokens and future pricing models
Sponsors: Mesmo, BrainGrid, and Unblocked
Gemini shutdown: Political risks and the rise of open models
The moat problem: Why wrappers on rented models are vulnerable
Gainable's future: Custom models, air-gapped enterprise deployment
Outro and Sponsor: Aura identity protection
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