Grab · 2026
Agent platform (Part 1): How we help Grab build and run AI agents at scale
Grab's internal AI agent work started as a Tech Infra support bot and grew into a company-wide platform: more than 500 services run on its agent framework (LLM-Kit), over 50 Model Context Protocol servers are registered on its remote MCP framework, and a single LLM gateway fronts every model call across the company, handling billions of tokens each month for production agents used daily by millions of merchants, drivers, and consumers. Part 1 covers how the original Go bot's reasoning plane and tool plane became reusable framework building blocks, and how problems that appeared around 500 agents—shared model control, safe tool reuse across teams, and evals after prompt changes—pushed the team toward the GrabGPT Gateway, remote MCP, and an evals platform covered in later parts.
500+ services on the internal agent framework50+ remote MCP serversagent frameworkLLM gatewayremote MCPLLM-KitGrabGPT GatewayModel Context Protocol
OpenAI · 2026
How OpenAI delivers low-latency voice AI at scale
OpenAI rebuilt its WebRTC stack for ChatGPT voice and the Realtime API after one-port-per-session media termination collided with Kubernetes: large public UDP ranges, sticky ICE/DTLS ownership, and global first-hop latency. A lightweight Go relay exposes a small fixed UDP surface, reads ICE ufrag routing hints from the first STUN packet, and forwards opaque media to the transceiver that owns ICE, DTLS, and SRTP state (with Redis-backed recovery). Cloudflare geo and proximity steering place signaling near users while Global Relay shortens the first media hop, preserving standard WebRTC for clients without making inference backends WebRTC peers.
900 million+ weekly active usersWebRTC relay + transceiverICE ufrag routinggeo-steered signalingWebRTCPionGo