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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.
27:09ENWhy Theo Values Reliable Coding Agents Over Peak PerformanceTheo Browne · T3Theo Browne argues that a model’s weakest moments matter when a coding task stretches from investigation through testing and review.
38:21ENHow Theo Works With One Hand: Dictation and Coding AgentsTheo Browne · T3After a hand injury, Theo Browne combines voice input, one-handed navigation and agents to reduce friction in his daily work.
1:02:53ENShopify’s Return to Native: What AI Changes for React NativeTheo Browne · T3Theo Browne weighs Shopify’s move to Swift and Kotlin against over-the-air updates, tooling, platform limitations and his own AI-assisted port.
49:22ENTheo’s AI Agent Workflow: Parallel Investigations, Review Loops and Safer MergesTheoA walkthrough of how Theo uses agents, remote previews and release safety nets to keep coding while running a company.
28:36ENTheo on Partial Understanding: Working in Large Codebases With AITheoReading Sean Goedecke on theory-building, Theo explains why engineers need useful mental models without memorizing an entire system.
55:06ENFable 5.1 in Practice: Theo on Costs, Agent Workflows and PR QualityTheoTheo reviews the launch, prompting guidance and his early coding experiments, including an observational comparison of pull requests.
39:28ENTheo’s Case Against Automatic Coding-Agent MemoryTheo Browne, Mario, Armin, Uncle Bob · Ping LabsAfter examining Claude Code memories on his machines, Theo explains his preference for maintained project context, architecture and automated checks.
0:42ENTheo on the Mental Overhead of Terminal WorkflowsTheo Browne · Ping LabsA longtime terminal user explains why keeping track of multiple simultaneous tasks can become difficult.
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.
0:32ENTheo on the Friction of Using a Terminal on a PhoneTheo Browne · Ping LabsTheo appreciates SSH but finds mobile terminal workflows frustrating, even with alternatives such as SSH3 and Mosh.
31:48ENWhy File Systems Slow Down Coding Agent WorkflowsTheo Browne · t3.ggTheo Browne compares worktree creation, package installs and storage use across Mac and Linux setups, and explains why he moved his agent workflow to XFS with VDO.
0:24ENTheo on SSH and the Frustration of Unstable ConnectionsTheo Browne · Ping LabsA network interface mix-up caused lag while Theo was working remotely, illustrating a drawback he sees in SSH workflows.
38:21ENHow Theo Evaluates AI Agent Skills: Matt Pocock’s Collection and PStackTheo Browne · t3.ggTheo Browne tries skills for clearer writing, project interviews and code review, and explains how he selects instructions for his own agent workflows.
0:28ENTheo on Working Without Opening a TerminalTheo Browne · Ping LabsA reboot helped Theo realize that a more readable, organized interface had changed his coding workflow.
31:17ENWhy Theo Moved From Terminals to Graphical Agent WorkflowsTheo Browne · t3.ggTheo Browne explains how parallel coding agents changed his tool preferences, and why he helped build the open-source T3 Code interface.
25:31ENGrok 4.6: Better Agent Benchmarks, With Tradeoffs in Speed and CostTheo Browne · t3.ggTheo Browne tests Grok 4.6 on design, games and real code, weighing reported benchmark gains against his experience of slower and costlier tasks.
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.
0:42ENTheo on Using an AI Agent to Test Debugging HypothesesTheo Browne · Ping LabsWhen a model could not find a problem on its own, Theo asked it to build a tool for testing his theories.
44:29ENTheo’s Opus 5 Review: Coding Style, Cost and Model TradeoffsTheo Browne · Ping LabsAfter a day of coding with Opus 5, Theo compares it with Fable and GPT-5.6 Sol across plans, benchmarks, costs and real work.
24:11ENTheo on Disposable AI Code and Verifying Important SoftwareTheo Browne · Ping LabsTheo argues that generated code can serve experiments and verification while critical production changes retain careful review.
19:12ENTheo on Boris Cherny’s Advice for Engineering with AI AgentsTheo Browne · Ping LabsTheo argues that the skills behind good tooling, tests and onboarding remain valuable when agents join the development workflow.
57:39ENFable 5 vs GPT-5.6 Sol: Theo on Cost, Coding and Model JudgmentTheo Browne · Ping LabsTheo compares two coding models through benchmarks, design work and long-running tasks, explaining why his favorite model is not always the one he uses first.
30:48ENWhy Theo Runs GPT-5.6 Sol in Claude CodeTheo Browne · Ping LabsA hands-on comparison of coding-agent workflows, historical system prompts and the practical limits of changing a model’s harness.
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