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Inside AI’s $10B+ Capital Flywheel — Martin Casado & Sarah Wang of a16z
Feb 19, 2026 · 55:31
Martin Casado and Sarah Wang of a16z argue that AI’s capital flywheel—where model labs translate funding directly into capability gains and revenue growth in weeks—is creating a new financing playbook that blends venture and growth, with rounds acting as compute contracts. They warn that frontier labs like Anthropic can potentially raise more money than the entire app ecosystem built on their APIs, allowing them to outspend and consume those layers. The episode examines the AGI vs. product dilemma in GPU allocation, the war for talent where $10M+ packages break early-stage founder math, and Cursor as a case study of building up from the app layer while training down into its own models. They also identify “boring” enterprise software as the most underinvested opportunity and note that robotics lacks a ChatGPT moment that would justify current funding levels.

Why every AI Engineer needs an AI Gateway (ft Portkey.ai CEO)
Feb 5, 2025 · 31:18
Rohit Agarwal, CEO of Portkey, explains why every AI engineer needs an AI gateway: an operational platform that connects to LLMs more efficiently, handling routing, observability, guardrails, and cost management. He notes that 90% of production use cases don't use automatic routing, but reasoning models and agents are driving new routing demands. Portkey's open-source gateway minimizes latency with a 21 MB memory footprint using JSON transformers. Key jobs include routing, observability (monitoring price, performance, accuracy), guardrails (e.g., regex-based, empty output detection, PII redaction), and human feedback tied to business metrics like video download rates. Rohit also highlights MCP adoption for simplifying agent-to-service connections, with bidirectional communication via RPC.
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