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Matthew Berman

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State of Enterprise AI 2026: Aaron Levie on Tokenmaxxing, The Rise of Headless, and AI-Proofing Your Job 00:00 Intro 01:18 Silicon Valley engineering vs. everyone else 05:35 Are enterprise CIOs actually bullish on AI? 08:51 Tokenmaxxing & why your AI bill is about to explode 11:34 The myth of falling token costs and AI spend escaping IT budgets 17:37 The $5B startup hiding in AI compute 18:14 The mosaic of models inside every enterprise 21:28 Why coding works and the rest of knowledge work doesn't 25:53 The Bob and Sally problem: access control breaks agents 30:31 Will enterprise AI really take 10 years to roll out 32:24 The capability overhang: why faster models slow diffusion 34:23 Data is the bottleneck (it always was) 39:02 The rise of internal forward-deployed engineers 41:23 Why the AI doomers are wrong about jobs 43:43 Headless software is inevitable 46:14 What replaces per-seat pricing 47:37 How Box itself is going headless 49:42 How the org chart actually evolves 1:00:33 Future-proofing yourself as an enterprise employee 1:06:40 Are we all just going to work for OpenAI and Anthropic? 1:07:11 Where startups can still win as the labs move up

Matt Turck

49,373 Aufrufe • vor 2 Monaten

How to become an AI researcher with Charlie O'Neill Charlie co-founded Parsed to build specialized open-source models that can outperform frontier labs. I first met Charlie when Parsed was acquired by Baseten, and now he leads our model development team. Charlie is one of the smartest people I know, and I had the pleasure of talking to him about: 0:00 Intro 3:13 Leaving Oxford to start a company 6:37 Becoming an AI researcher 15:37 Developing a unique POV as your moat 22:04 Parsed origin story 26:01 Big Token, the case for open-source models 33:40 Post-training, fine-tuning, specialization 46:52 Will open models catch up with closed models? 51:50 AI-led job replacement vs job creation 54:45 How to get into inference engineering This is one of my favorite conversations I’ve had in a long time. Made with Lan behind the scenes. Enjoy!
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How to become an AI researcher with Charlie O'Neill Charlie co-founded Parsed to build specialized open-source models that can outperform frontier labs. I first met Charlie when Parsed was acquired by Baseten, and now he leads our model development team. Charlie is one of the smartest people I know, and I had the pleasure of talking to him about: 0:00 Intro 3:13 Leaving Oxford to start a company 6:37 Becoming an AI researcher 15:37 Developing a unique POV as your moat 22:04 Parsed origin story 26:01 Big Token, the case for open-source models 33:40 Post-training, fine-tuning, specialization 46:52 Will open models catch up with closed models? 51:50 AI-led job replacement vs job creation 54:45 How to get into inference engineering This is one of my favorite conversations I’ve had in a long time. Made with Lan behind the scenes. Enjoy!

Madison Kanna

129,409 Aufrufe • vor 18 Tagen

Most people experience AI through apps. Those apps run on infrastructure owned by a handful of companies. Ben Fielding and Harry Grieve of gensyn on why that needs to change, and what it's going to take to rebuild AI as crypto-native open infrastructure. 00:00 – Intro 00:29 – Misconceptions about AI infrastructure 01:20 – Why centralization in AI is a deeper problem than people realize 04:19 – Why AI needs crypto 05:51 – How AI models are trained 08:15 – The rise of autonomous AI agents with onchain identities 10:37 – Lightning round
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Most people experience AI through apps. Those apps run on infrastructure owned by a handful of companies. Ben Fielding and Harry Grieve of gensyn on why that needs to change, and what it's going to take to rebuild AI as crypto-native open infrastructure. 00:00 – Intro 00:29 – Misconceptions about AI infrastructure 01:20 – Why centralization in AI is a deeper problem than people realize 04:19 – Why AI needs crypto 05:51 – How AI models are trained 08:15 – The rise of autonomous AI agents with onchain identities 10:37 – Lightning round

a16z crypto

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