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38:47ENTheo’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.
31:47ENTheo on Asking Agents for Outcomes and Building the Tools They NeedTheo Browne · Ping LabsA tool-call report, a troubleshooting playbook and connected data show how prompting can reshape product engineering.
41:32ENUsing Fable 5.1 for Longer Coding TasksTheo Browne · T3Theo Browne shares how he prompts coding agents, sets end states and uses reviews and tests to support longer-running work.
33:48ENIs Coding Solved? Theo Separates Code Generation from EngineeringTheo Browne · Ping LabsA Claude Code UI defect sparks a debate about what agents can implement and what it takes to verify and maintain good software.
51:15ENHow Theo Refined His AGENTS.md and Skills From Real Agent FailuresTheo Browne · t3.ggTheo Browne explains how he audits agent sessions, writes project guidance and shares skills across machines without treating his configuration as a template.
36:00ENGPT-5.6 Reviewed: Strengths, Costs, and Coding-Agent TradeoffsTheo Browne · Ping LabsTheo Browne assesses Sol, Terra and Luna through benchmark results and hands-on coding experience.
37:56ENClaude Code, Codex, and Cursor: Three Approaches to AI CodingTheo Browne · T3Theo compares terminal-first coding agents, local verification, cloud execution, and the trade-offs behind their interfaces.
39:05ENWhy GitHub Copilot Changed Its Billing for Agent WorkflowsTheo Browne · T3Theo explains why one agent request can consume vastly different resources, and what that means for subscription pricing.
45:51ENClaude Subscription Credits and the Debate Over Third-Party Agent ToolsTheo Browne · T3Theo explains why a separate programmatic allowance affects T3 Code and questions the line between interactive and automated use.
39:23ENHow Coding Agents Work: Models, Tools and the Harness LoopTheo Browne · T3Theo Browne explains how a coding agent requests tools, builds context and repeats model calls, then demonstrates a small implementation.









