Sarah Guo
Founder of Conviction, an AI-focused venture capital firm, and co-host of the No Priors podcast, where she interviews AI builders, researchers, founders, and technology leaders.
Private Evals Are Becoming the Core IP of Enterprise AI
Microsoft chief executive Satya Nadella argues that the AI frontier is shifting from single models to company-specific systems built from private evals, traces, tools, data and multi-model harnesses. In a Microsoft Build conversation with Sarah Guo, Elad Gil and Shawn Wang, Nadella says those private evaluation loops may become a company’s most important intellectual property, allowing enterprises to build their own specialist intelligence rather than merely consume frontier models. He also frames the broader test for AI as legitimacy: whether customers, workers and communities see measurable gains from the technology and the infrastructure behind it.
Companies Can Build Frontier Intelligence Without Owning the Frontier Model
Satya Nadella used Microsoft’s Build 2026 AI announcements to argue that the next phase of AI will be defined by ecosystems, not by companies consuming a single frontier model. In a crossover conversation with No Priors and Latent Space, Microsoft’s chief executive said enterprises and startups should be able to build their own “frontier intelligence” from models, tools, data, context, and private evaluations. His case is that durable value will accrue to companies that control those loops, rather than simply rent intelligence from a general-purpose provider.
Enterprise AI Security Is Moving From Chat Monitoring to Action Control
Maxim Bar Kogan, founder and CEO of Onyx Security, argues that enterprise AI security is shifting from policing chatbot data leaks to controlling autonomous agents that can use credentials, call APIs, edit code and alter production systems. In a conversation with Sarah Guo, he makes the case for an independent AI control plane that can judge whether an agent’s actions match its assigned intent, rather than relying on traditional permissions, proxies or the model vendors themselves. Kogan says the hard problem is doing that supervision cheaply and quickly enough for enterprise deployment.
SpaceX IPO Pitch Seeks $2 Trillion Valuation on AI and Mars
Bloomberg Technology’s Ed Ludlow framed SpaceX’s Nasdaq IPO filing as a test of whether public investors will underwrite Elon Musk’s farthest-reaching claims: a company seeking a valuation above $2 trillion, as much as $75 billion in proceeds and a $28.5 trillion addressable market built largely on AI, Starlink and Mars. Bloomberg reporters and guests said the filing asks investors to look past large losses, debt and Musk’s continuing control, while treating Starship and space-based infrastructure as central to the valuation case rather than speculative side projects. The program placed that pitch alongside Nvidia’s effort to prove AI demand is broadening beyond hyperscalers and possible OpenAI and Anthropic filings that could bring similar public-market scrutiny to frontier AI.
Startups Are Treating Nvidia Compute as the First AI Bottleneck
Conviction founder Sarah Guo told Bloomberg’s Ed Ludlow that Nvidia’s compute shortage is showing up directly in startup behavior: young AI companies want current-generation chips first because that is where they discover new capabilities, and only later optimize for cost. Guo said demand stress now spans small on-demand users and buyers seeking $100 million commitments, reinforcing Jensen Huang’s argument that supply remains far behind AI compute demand. She also framed the larger enterprise-AI opportunity as an automation bet whose value may accrue across infrastructure, models and applications.
Cerebras’ Wafer-Scale AI Bet Fuels a $63 Billion IPO
Cerebras founder and CEO Andrew Feldman argues that the company’s roughly $63 billion public-market debut is the result of a decade-long wager on wafer-scale computing: a dinner-plate-sized chip architecture built for AI rather than a modified GPU. In a discussion with Elad Gil and Sarah Guo, Feldman says Cerebras survived years when the technology worked before the market cared, and that demand arrived only once AI became daily work and fast inference became commercially decisive.
Pax Silica Aims to Secure the Full AI Supply Chain
U.S. Under Secretary of State for Economic Affairs Jacob Helberg argues that AI dominance depends on securing the full industrial supply chain behind compute, not just advanced semiconductors. In an interview with Sarah Guo and Elad Gil, Helberg presents Pax Silica as a 14-country economic-security coalition meant to build commercially viable allied supply-chain platforms, starting with a 4,000-acre industrial zone in the Philippines. He frames the strategy as a private-sector-led alternative to China’s Belt and Road model, combining domestic reindustrialization with partner-country specialization in critical inputs such as minerals, robotics components, and processing capacity.
Long Lake’s $6.3 Billion Amex GBT Deal Tests AI-Led Buyouts
Long Lake Management co-founder and CEO Alexander Taubman argues that AI can change the economics of services businesses when the buyer owns the workflow, not just the software layer. In a conversation with Elad Gil about Long Lake’s announced $6.3bn take-private of American Express Global Business Travel, Taubman presents the firm’s model as acquiring trusted services companies, embedding its Nexus AI platform into day-to-day operations, and using productivity gains to drive growth, customer service and employee retention rather than short-term cost cuts.