OpenAI Product Strategy (senkorasic.com)

This year OpenAI has doubled down on product-layering to turn models into a sticky platform rather than a commodity. Beyond big infrastructure deals with NVIDIA, AMD, Oracle and Broadcom, the company has rolled out higher-level APIs and tooling — from Assistants and the Responses API to a more robust Agents SDK, Agent Builder and ChatKit (now unified as AgentKit) — that provide richer abstractions for building agents and chatbots and tightly integrate them with OpenAI’s stack. On the consumer side ChatGPT evolved from a demo into a monetization challenge (custom GPTs underperformed, a much pricier Pro tier still loses money), while enterprise offerings gained standard controls (SOC2, SSO, MFA). OpenAI also responded to developer competition with Codex-specialized models and devtools (Codex CLI, Codex Cloud). Facing fierce rivals (Anthropic’s Claude, Google’s Gemini in Chrome, Perplexity’s Comet), OpenAI launched Atlas — a Chromium-based browser that embeds ChatGPT — and an Apps SDK that lets third‑party apps run “inside” ChatGPT, aiming to make ChatGPT the primary UI for web and app interaction. Technical implications: MCP/Data Connectors broaden integrations but Apps SDK is a deeper platform play that could lock in workflows. Risks remain: embedding AI in a browser is costly per query (inferencing budget), ad monetization would pit OpenAI against Google’s entrenched ad stack, and the approach is easy to copy. The Apps SDK, if it attracts a rich developer ecosystem fast, is the most defensible lever for growth.