Tokenless

Evals

Build Hour: Valuemaxxing with GPT-5.6

Build Hour: Valuemaxxing with GPT-5.6

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.

Why building eval platforms is hard — Phil Hetzel, Braintrust

Why building eval platforms is hard — Phil Hetzel, Braintrust

An evaluation platform is more than a simple test runner; it's a complex system for creating shared definitions of quality. This talk explores the evolution of eval platforms from basic spreadsheets to sophisticated, integrated systems, highlighting the hidden data and systems engineering challenges involved in making them credible, scalable, and usable for building trustworthy AI agents.

What OpenAI & Google engineers learned deploying 50+ AI products in production

What OpenAI & Google engineers learned deploying 50+ AI products in production

Aishwarya Naresh Reganti and Kiriti Badam, with experience from OpenAI, Google, and Amazon, share a framework for building successful enterprise AI products. They detail why AI development differs from traditional software, emphasizing the challenges of non-determinism and the agency-control trade-off, and introduce their 'Continuous Calibration, Continuous Development' (CC/CD) lifecycle to build reliable, value-driven AI systems.

Build Hour: AgentKit

Build Hour: AgentKit

A deep dive into OpenAI's AgentKit, demonstrating how to visually build, deploy, and optimize multi-step, tool-calling agents using Agent Builder, ChatKit, and the integrated Evals platform.

Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix)

Al Engineering 101 with Chip Huyen (Nvidia, Stanford, Netflix)

Chip Huyen, an AI expert and author of 'AI Engineering', explains the realities of building successful AI applications. She covers the nuances of model training, the critical role of data quality in RAG systems, the mechanics of RLHF, and why the future of AI improvement lies in post-training, system-level thinking, and solving UX problems rather than just chasing the newest models.

Before Building AI Agents Watch This (Deep Agent Expertise)

Before Building AI Agents Watch This (Deep Agent Expertise)

Nishikant Dhanuka from Prosus Group shares practical lessons on building effective AI agents for e-commerce and productivity. He covers why context engineering is more crucial than prompt tweaking, how to build a modern search pipeline, the failures of pure-chat interfaces, and why a robust evaluation framework is the real competitive advantage.

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