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How to Optimize AI Agents in Production

How to Optimize AI Agents in Production

Engineers building AI agents face a combinatorial explosion of configuration choices (prompts, models, parameters), leading to guesswork and suboptimal results. This talk introduces a structured, data-driven approach using multi-objective optimization to systematically explore this vast design space. Learn how the Traigent SDK helps engineers efficiently identify optimal tradeoffs between cost, latency, and accuracy, yielding significant quality improvements and cost reductions without manual trial-and-error.

Evaluating AI Agents: Why It Matters and How We Do It

Evaluating AI Agents: Why It Matters and How We Do It

Annie Condon and Jeff Groom from Acre Security detail their practical approach to robustly evaluating non-deterministic AI agents. They share their philosophy that evaluations are critical for quality, introduce their "X-ray machine" analogy for observability, and walk through their evaluation stack, including versioning strategies and the use of tools like Logfire for tracing and Confident AI (Deep Evals) for systematic metric tracking.

Designing Claude Code

Designing Claude Code

Anthropic’s Meaghan Choi and Alex Albert explore the design philosophy behind Claude Code, discussing its terminal-first approach, the evolution of developer workflows in the age of LLMs, and how agentic coding empowers both engineers and designers.

Richard Sutton – Father of RL thinks LLMs are a dead end

Richard Sutton – Father of RL thinks LLMs are a dead end

Richard Sutton, a foundational figure in reinforcement learning, argues that Large Language Models (LLMs) are a flawed paradigm for achieving true intelligence. He posits that LLMs are mimics of human-generated text, lacking genuine goals, world models, and the ability to learn continually from experience. Sutton advocates for a return to the principles of reinforcement learning, where an agent learns from the consequences of its actions in the real world, a method he believes is truly scalable and fundamental to all animal and human intelligence.

Early Days of Agile Development & Is Design Dead? • Martin Fowler & James Lewis

Early Days of Agile Development & Is Design Dead? • Martin Fowler & James Lewis

In an interview with James Lewis, Martin Fowler recounts his journey into the Agile movement, starting from the object-oriented community to the pivotal Chrysler C3 project where Extreme Programming (XP) was born. He discusses the shift from upfront to evolutionary design, the creation of the Agile Manifesto, and offers modern perspectives on developer productivity, the role of GenAI in software analysis, and the enduring importance of XP's technical practices.

NVIDIA’s USD 100bn investment and Google's AP2

NVIDIA’s USD 100bn investment and Google's AP2

The panel discusses NVIDIA's $100 billion investment in OpenAI, analyzing the trend towards vertically integrated AI 'tribes'. They also explore the rise of specialized open-source models like Tongyi DeepResearch, Google's new AP2 agent protocol for secure e-commerce, the ongoing debate on AI existential risk, and Apple's practical approach to wearable AI with the new real-time translation feature in AirPods.

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