
Curtis contributed to the braintrustdata/braintrust-sdk and braintrustdata/braintrust-proxy repositories, focusing on backend and API development using Python and TypeScript. He delivered a feature that exposes cached token usage for OpenAI Agents, enhancing cost visibility and aligning metrics across wrappers. Curtis also stabilized GPT-5.x Codex model routing, implementing a flexible pattern to support future variants and adding comprehensive tests for reliability. Additionally, he improved observability by introducing explicit span naming for better traceability in logs. His work emphasized robust test coverage and future-proofing, demonstrating depth in backend engineering and a methodical approach to maintaining and extending complex data platforms.
February 2026 monthly summary for Braintrust data platforms. Key focus: stabilizing and future-proofing GPT-5.x Codex model routing and improving observability through enhanced span naming.
February 2026 monthly summary for Braintrust data platforms. Key focus: stabilizing and future-proofing GPT-5.x Codex model routing and improving observability through enhanced span naming.
December 2025 monthly summary for braintrust-sdk: Key feature delivered: OpenAI Agents SDK: Cached Tokens Visibility. Implemented extraction and display of cached tokens to improve token-usage visibility for OpenAI Agents integration; updated processing logic to capture tokens and added tests to ensure accuracy. No major bugs fixed this month. Overall impact: provides developers with clearer visibility into token usage, enabling better cost control and usage auditing; aligns OpenAI Agents visibility with existing wrappers. Technologies/skills demonstrated: instrumentation for metrics, test-driven development, and cross-wrapper consistency.
December 2025 monthly summary for braintrust-sdk: Key feature delivered: OpenAI Agents SDK: Cached Tokens Visibility. Implemented extraction and display of cached tokens to improve token-usage visibility for OpenAI Agents integration; updated processing logic to capture tokens and added tests to ensure accuracy. No major bugs fixed this month. Overall impact: provides developers with clearer visibility into token usage, enabling better cost control and usage auditing; aligns OpenAI Agents visibility with existing wrappers. Technologies/skills demonstrated: instrumentation for metrics, test-driven development, and cross-wrapper consistency.

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