The a16z Show

Terry Angelos × Alex Rampell

Payment credentials turned agents from “spectators to actors,” igniting wallet competition among Stripe Link, Shop Pay, and PayPal.Open-standard agentic tokens rose from zero to a few million weekly in three months; VGS, the largest provider, vaults about a third of e-commerce by GMV.They preserve chargeback rules and follow-on purchases, but liability for agent errors remains unresolved.

Lisha Li × Nathan Lambert

Lambert estimates distillation may give Chinese labs a few months, but its value in RL-heavy post-training remains unclear.Closed labs integrate inference and lead coding, where revenue has gone from zero to $100 billion, while open-model economics fragment builders, inference firms and post-training companies.Open models may still win buyers seeking owned weights and the cheapest adequate model.

Martin Casado × Dhaval Adjodah × Owen He

RSI founders Dhaval Adjodah and Owen He report early signs of performance rising as resource use stays flat or falls, with the model itself as optimizee.They cite retraining GPT-2 in hours for about $100 on the same GPU and data, and target inference efficiency across the stack.Casado has not seen equivalent GPT-5 evidence, leaving scalability beyond fast-evaluation tasks unresolved.

Raghu Raghuram × Guido Appenzeller × Pat Gelsinger

AI is compressing logic design faster than silicon, packaging, and rack deployment, shifting value toward manufacturing, memory, power, cooling, and integration.With roughly 100 AI processor vendors, consolidation is likely as workloads evolve and winners require major capital, software, and customer backing, though agent-generated kernels may preserve some heterogeneity.Memory may be positioned for its first major reset in 30 years, while optical scale-up I/O around 2028–2029 and power shortages, including eight-year turbine lead times, define key catalysts and risks.

Raghu Raghuram × Matt Garman

AWS is underwriting durable AI demand with $220 billion of 2026 capex while reserving scarce accelerators for startups as well as frontier labs.Positive-ROI production workloads and single-digit maximum customer concentration temper demand risk, while AWS plans to buy 2 million NVIDIA GPUs over the next couple of years.Agentic workloads may strengthen AWS’s architectural edge, but power, memory, chips and enterprise evaluation remain constraints to monitor.

David George × Kevin Mandia

AI is shifting cyberattacks from resource-constrained “sniper shots” to scalable swarms, while Armadin continuously verifies exploitable network weaknesses.Since January 2026, Armadin has found more than 90 zero-days across Fortune 500 customer environments, while Blue aims to turn a five-minute lead into autonomous controls.With technical advantages potentially copied in six months, customer execution and the Red-to-Blue feedback loop remain the operating test.

Elena Burger × Olivia Moore × Josh Elman

Consumer AI’s traffic rankings mask monetization: 29 of the 50 products leading on consumer card spending appear on neither traffic list, while the top 10% of paying users generate more than half of revenue.Personal agents are emerging, but Muse’s roughly 5 million U.S.-and-Canada downloads in about 22 days trailed Threads’ 16 million; high serving costs make lower inference costs and trusted advertising pivotal catalysts.

Erik Torenberg × Alex Atallah × Amjad Masad

Stripe’s acquisition of OpenRouter preserves its brand, roadmap, and product autonomy while pairing payments with model-independent inference infrastructure.OpenRouter’s marketplace reduces vendor lock-in, combines models, and pressures inference prices downward as enterprises evaluate task-specific performance rather than feature lists.Specialized decision models could lower model debt and police agent actions, while multi-model fusion reportedly approaches frontier quality at 40–50% of the cost; deception risk and cache reuse remain unresolved.

Seema Amble × Elena Burger × Vladimir Keil

AI procurement startups are targeting the end-to-end work hidden behind an ERP’s “$8,000” result, where 30 meetings, 500 emails and supplier counteroffers determine cost and delivery.Lio’s path from human review to $10,000, $20,000, or $100,000 negotiations highlights the production bottleneck: 70% accuracy can leave humans doing 100% of the work, while complex multimillion-dollar cases still require specialists.

Joel de la Garza × Barrett Lyon

Barrett Lyon argues the Internet’s open model is eroding as corporate servers, carrier-grade NAT, and policy-driven identity and age controls move communication and surveillance into the network layer.Docs.net owns the stack from software to wiring, using AI-operated hardware and private domains for peer-to-peer exchange; scaling under applicable laws while resisting telemetry-driven surveillance remains the key risk.