Encord Co-CEO Eric Landau reflects on his transition from a lucrative quant career to founding an AI startup, driven by a deep belief in AI's paradigm-shifting potential. He discusses Encord's slow, compounding path to product-market fit, the pivotal role of Physical AI, and the importance of embracing the emotional rollercoaster of startup life.
Rustem Feyzkhanov discusses the critical need for companies to build private, production-aligned benchmarks for AI agents. He explains how to turn agent traces into repeatable simulations, why public benchmarks are insufficient, and how a CI pipeline for agents, integrating observability and experimentation, can ensure reliable evaluation, continuous improvement, and effective release management, moving beyond simple pass rates to measure cost, latency, and policy adherence.
This talk details how Uber Eats designed and implemented a multimodal AI agent to enhance food photography for independent merchants, addressing challenges like maintaining authenticity, merchant brand, and marketplace diversity while operating at scale. It covers the intricate evaluation strategies for routing and image editing agents, including continuous learning loops, managing drift, countering reward hacking, and balancing creative freedom with rigid safety guardrails. The speakers explain how they built a closed feedback loop combining offline human labeling, internal dogfooding, and online production signals to ensure robust and adaptive performance.
Datadog CEO Olivier Pomel shares his journey, emphasizing the company's evolution from a DevOps insight to a public tech giant. He discusses the resilience required to overcome early rejections, his hands-on leadership style focused on raw customer feedback, and how Datadog is rapidly adapting to the AI revolution by prioritizing automation and faster iteration in product development and internal processes. Pomel also offers candid advice on co-founder relationships and the critical importance of moving quickly in both hiring and firing.
This Build Hour focuses on "value maxing" with GPT-5.6, shifting from simply tracking token usage to measuring the actual outcomes and efficiency gained from AI. It covers how to select the right GPT-5.6 model (Sol, Terra, Luna) based on intelligence, latency, and cost, and provides practical strategies for optimizing cost-performance. Key topics include leveraging programmatic tool calling, prompt caching, persistent reasoning, and context compaction for API users, along with CodeX-specific tips. A customer spotlight on Ploy demonstrates real-world application, showcasing their migration to GPT-5.6 Sol, which resulted in 2.2x faster builds at 27% lower cost through advanced caching and tool optimization techniques.
Jason Liu from OpenAI shares advanced strategies for using Codex to automate complex workflows and manage personal information. He introduces key concepts like "compaction," dictation for input, and "appshots" for contextual awareness. The talk covers bringing context into the system via plugins and a personal memory vault, working with AI through automations, goals, and interconnected threads, and taking actions out in the real world, emphasizing the transformative power of "Computer Use" for broad system control.