The Arize team shares lessons from building their AI agent, Alyx, which analyzes its own trace data. They detail their journey from failed attempts like naive truncation and summarization to a successful strategy combining head/tail preservation with a retrievable memory store and using sub-agents to manage context complexity.
A product engineer from Granola shares a candid account of the challenges in moving AI features from the playground to production. This talk covers the pitfalls of "one-shot" solutions like web search and generic prompts, and details Granola's strategy of building custom internal tracing and development tooling to create a tight, effective feedback loop for iteration.
Grant Miller from IBM explains Agentic Consent, a dynamic framework for governing AI agents. The model moves beyond static permissions, using identity, context, and just-in-time user prompts to ensure AI agents act with, not instead of, their human counterparts, enabling trust and safety as autonomy scales.
Samuel Humeau from Mistral explains the dominant architecture for modern text-to-speech (TTS) systems, which mirrors large language models. He details how neural audio codecs solve the information density problem, the autoregressive transformer backbone for generation, and the streaming techniques used to achieve low perceived latency in voice agents. The talk uses Mistral's open-weight TTS model as a practical example.
Neil Zeghidour, CEO of Gradium AI, deconstructs the gap between current voice AI and the "Her" ideal. He argues that while cascaded systems are practical, they are architecturally flawed for natural conversation. The future lies in full-duplex, speech-to-speech models that not only solve latency but also integrate deep paralinguistic understanding and overcome significant cost barriers.
Co-founders of Trigger.dev discuss their journey through three product versions to find product-market fit, how their async infrastructure positioned them perfectly for the AI agent era, and their vision for the future of computing: programmatic checkpoint and restore.