Topic
Agentic Systems
Making Cities Awesome: Peregrine’s Nick Noone & Ben Rudolph
Peregrine’s founders argue that public-safety software should connect the data cities already own, not collect more of it, and that safety, privacy, and local data sovereignty have to be designed in from the start. They also show how forward-deployed engineering and AI agents can turn messy municipal data into search, analysis, and even new operational tools for police, fire, EMS, and emergency management.
20VC: The AI Bubble Is Wrong | AI Margins Need to Improve | Revenue Concentration Should be a Concern | Why People Over-Estimate Open Models But Enterprises Still Fear Frontier Models with Aaron Katz, ClickHouse
Aaron Katz argues the AI boom is still early, not a bubble, but says the bigger risk is revenue durability when switching costs are low. He also explains why ClickHouse is leaning into agentic workloads, broad deployment flexibility, and long-term private-company optionality rather than rushing an IPO.
20VC: Is Anthropic's Coding Business Worth $2 Trillion? | Should American Enterprises Work With Open-Source Chinese Models? | Why 80–90% of Neo-Labs Die in the Next 18 Months? with Eno Reyes, Co-Founder @ Factory
Eno Reyes argues AI should be judged by outcome cost, not token cost, and predicts open models will dominate most workflows while specialized enterprise harnesses keep the highest-value intelligence inside the company. He also warns that many neo-labs are economically fragile, that enterprise buyers care deeply about model independence and sovereignty, and that the next software stack will center on stateful agentic systems rather than simple model routing.
Meta CTO Andrew Bosworth: Our Path To Frontier AI, Renting Models, Consumer AI's Struggles
Andrew Bosworth says Meta’s AI comeback is shifting from chasing one giant model to layering frontier, distilled, and task-specific models inside products people actually use. He also argues the company’s long-term edge will come from glasses, distribution, and consumer workflows—not from model benchmarks alone.