Using a router model (GPT Realtime) to direct tasks to appropriate models (Fable 5 for vision, GPT-5.5 for agentic) reduces costs and improves latency, enabling sustainable unit economics.

Agentic AI automates the technical parts of data migrations, reducing timeline dramatically from years to quarters, though change management remains a challenge.

Snowflake aims to be in the token path by providing coding agents (Cortex) for data preparation and Co-work for data consumption, capturing value across AI data workflows.

Cloudflare's isolates architecture is more efficient than containers for running millions of AI agents, enabling inference at the edge in 350 cities with lower latency, cost, and power cons…

AI agents drive exponential growth in web traffic, with each agent visiting thousands of sites per task, while web creation accelerates; bot traffic will be 1000x human traffic within 5 yea…

Autoformalization converts human intent into machine-checkable formal languages (Lean), enabling provably accurate AI in domains where hallucination is unacceptable, addressing specificatio…

Converting operating procedures into formally verified code (Lean) allows AI agents to execute complex workflows with mathematical proofs of correctness, unlocking high-stakes automation.

Charging only when AI successfully resolves a call or makes a sale aligns incentives, accelerates deployment, and solves token maxing concerns by making vendors partners in outcomes.

Gap between best frontier models (GPT-5.5, Anthropic) and others is widening; most enterprise tasks need cheaper, specialized models, leading to a constellation architecture with routing.