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38:47EN
Theo - t3․gg· Oct 28, 2026Theo’s Long-Running Agent Experiments: Verification, Compute and CostTheo Browne · Ping LabsA skateboard game and two compiler projects show how repeated checks and flexible compute can sustain agent work—and how expensive those loops can become.
48:04ENTheo - t3․gg· Oct 16, 2026Theo Explains Scion, Anthropic’s Source-Control System for Agent-Scale WorkTheo Browne · Ping LabsA deep dive into server-side changesets, layered caches, migration results and the limits of a bespoke Git alternative.
18:17ENTheo - t3․gg· Aug 8, 2026MCP’s Stateless Redesign: What Changed and Why Theo Is OptimisticTheo Browne · Ping LabsThe July 2026 MCP specification replaces protocol sessions with self-describing requests. Theo examines the benefits, examples, and the problem of migrating older clients and servers.
28:11ENTheo - t3․gg· Jul 7, 2026The Tradeoffs of Running Open-Weight AI Models LocallyTheo Browne · Ping LabsTheo Browne separates the value of open weights from the hardware, concurrency and cost constraints of local inference.
38:05ENTheo - t3․gg· Jul 3, 2026Why Theo Moved His Agent Work to Linux MachinesTheoLong-running coding agents, laptop CPU load and slow small-file operations led Theo to build a networked fleet. He demonstrates SSH, a hardware KVM and T3 Code for remote work.
22:43ENTheo - t3․gg· Jun 29, 2026Mac Prices, Unified Memory and Local AI: Theo’s Buying Trade-offsTheoTheo explains why high-memory Macs appealed for local inference and how rising component prices changed his comparison with PCs.