The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch 20VC: Scale, Surge, Turing, Mercor: Who Wins & Who Loses in Data Labelling | Is Revenue in Data Labelling Real or GMV? | Why 99% of Knowledge Work Will Go and What Happens Then? | Why SaaS is Dead in a World of AI with Jonathan Siddharth @ Turing
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Dec 1, 2025 
Jonathan Siddharth, Founder and CEO of Turing, dives into the future of AI and data labeling. He predicts that 99% of knowledge work will be automated within a decade, reshaping job markets. Siddharth discusses why traditional SaaS models are becoming obsolete in an AI-driven world and the critical need for custom, fine-tuned models in enterprises. He also highlights the importance of data-driven feedback loops as the new competitive moats, and shares insights into Turing's unique research-focused approach that sets it apart from legacy labeling firms.
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Create Realistic Simulated Workflows For Training
- Build RL environments that mimic real apps and instrument state so agents can practice workflows.
- Use synthetic databases and verifiers to reward successful multi-step tool use during training.
Knowledge Work Is A Massive Workflow Matrix
- Every role equals a set of workflows across industry, function, role, and task dimensions.
- Siddharth frames this as a massive matrix requiring time and capital to populate.
AI Progress Is Slow And Steady, Not Rapid
- We're in innings one of data acquisition and a slow, steady takeoff toward AGI.
- Siddharth argues the breadth of domain data will take significant time and investment.