PERSON DIRECTORY
Sherwin Wu
Sherwin Wu appears in 3 indexed conversations across BG2, Latent Space, The a16z Show. This directory brings every appearance, source, TL;DR, digest, and transcript into one searchable feed.
How OpenAI Builds for 800 Million Weekly Users: Model Specialization and Fine-Tuning
OpenAI is pursuing a two-sided distribution strategy through ChatGPT’s roughly 800 million weekly users and an API embedded across third-party products, while model-specific user preferences and developer harnesses make commoditization less straightforward.Reinforcement fine-tuning can turn proprietary enterprise data into differentiated capability, but adoption increasingly depends on context engineering, deterministic workflows, and efficient inference as specialized models and usage-based pricing reshape the economics of deployment.
DevDay 2025: Apps SDK, Agent Kit, MCP, Codex and why Prompting is More Important than Ever
Apps SDK makes ChatGPT an application distribution layer, combining roughly 800 million weekly active users with developer-controlled UI and brand rather than plugin-style dependence.MCP broadens integrations while AgentKit connects visual workflows, SDK deployment, connectors, ChatKit, and evals into a production stack for complex, weeks-long orchestration.The opportunity depends on connector quality, trajectory-level evaluation, prompt optimization, human review, and API reliability, with identity, inference funding, and widget economics unresolved.
Inside OpenAI Enterprise: Forward Deployed Engineering, GPT-5, and More | BG2 Guest Interview
Apoorv AgrawalSherwin WuOlivier Godement
OpenAI’s enterprise business predates ChatGPT and now embeds Palantir-style forward deployed engineers at T-Mobile, Amgen, and Los Alamos.Across 200 deployments, top-down buy-in, a bottom-up tiger team, and evals first underpin the climb from 46% to 99%.Connectors and RFT could unlock agents and proprietary-data advantages, but GPT-5’s reasoning-token versus latency trade-off remains unresolved.