
Most Valuable Skill of 2026: Managing AI Agents
- 44m
- Transcript
Summary
Written by a model from the transcript; not yet reviewed.
In this episode, the guest Ryan Carson and the host discuss how to operate teams of AI agents effectively to scale output, particularly in a startup environment. Carson shares details from his current startup, Untangle, which builds AI tools for family law, and explains how moving development to cloud environments and utilizing rigorous automations allows a single operator to ship dozens of pull requests daily. Throughout the discussion, the guest details his personal office setup, explains the mechanics of running multiple virtual machine sessions, and argues why traditional local development is obsolete for high-velocity builders.
- Move your software development to cloud-based virtual machines rather than working locally so you can run multiple concurrent agents without code collisions. 10:46
- Keep your production credentials strictly secured in a password manager and make your agents request keys manually rather than giving them write access directly. 5:56
- Set up automated browser testing loops to run recurring end-to-end tests that catch bugs before customers encounter them. 25:00
- Build a daily production watchdog automation that summarizes customer activity and database events so you can review real user behavior every morning. 30:43
- Share what you are learning publicly on platforms like X to build a network, establish credibility, and open doors for future collaborations. 41:53
Chapters
- 0:00Podcast Intro and Guest Introduction
The host introduces the episode, explains the focus on managing AI agents, and welcomes Ryan Carson to discuss his setup and insights.
- 1:00Ryan’s Background and AI Divorce Firm
Ryan shares his 25-year founding experience, current seed‑raised startup, and how he’s scaling a family‑law AI divorce agent.
- 4:23Cloud Agents vs Local Development
Ryan contrasts local development with cloud‑based agents, emphasizing the scalability and mental overhead savings of cloud VMs.
- 7:24Phone‑First Workflow and Remote Setup
Ryan explains his mobile‑centric workflow, detailing how he manages agents from his phone and his home office setup.
- 9:00Key Practices: Secure Keys and Devon Harness
Ryan outlines best practices for key management, introduces Devon, and explains how cloud agents streamline coding and testing.
- 10:25Building a Software Factory and Reputation
Ryan advises on scaling to a software factory, leveraging independent labs, and building credibility through public sharing on X.
- 12:00Automations: QA, Production Watchdog, and Self‑Improvement
Ryan demonstrates various automation loops—QA testing, production monitoring, and chat grading—to continuously improve product quality.
- 34:55Cost Management and Model Routing
Ryan discusses token costs, the importance of choosing the right model, and how independent agent labs help keep engineering expenses low.
- 40:33Wrap‑Up and Takeaways
The hosts recap key points, emphasize the importance of cloud agents and automation, and encourage listeners to share knowledge on X.
Highlights
- 3:01
Running a One-Person Startupstory
The guest explains that his current company, Untangle, provides AI divorce agents for family law firms, and he runs the entire business as a single employee while scaling revenue rapidly.
- 4:13
A Massive Monitor Setupstrategy
The guest describes his home office desk layout, featuring a large 52-inch monitor configured into eight distinct screens to monitor multiple agents simultaneously.
- 7:44
Why Devon Succeededinsight
The guest explains that while coding agents initially struggled years ago due to weak underlying models, the current generation of models paired with cloud harnesses makes them extremely powerful.
- 15:11
High-Stakes Decision Fatigueinsight
The guest explains that operating many agents shifts knowledge work toward making dozens of high-stakes decisions by lunchtime, requiring strict pacing and mental discipline.
- 18:19
Working Locally is Obsoletedebate
The guest argues that developers who code exclusively on local machines are holding themselves back and shipping significantly less than those using cloud-based virtual environments.
- 20:37
Parent and Child Agent Hierarchiesstrategy
The guest outlines his tactic of using a primary parent agent thread to manage and spin up multiple cheaper child agent sessions to handle distinct tasks efficiently.
- 23:06
Engineering is More Technicalinsight
The guest counters the idea that engineering is disappearing, arguing that effective agent managers actually need to become more technical to properly oversee production environments.
- 36:48
Independent Labs vs Frontier Stacksstrategy
The guest advises against building an engineering workflow directly on frontier lab stacks like Claude Code or Codex, arguing that independent agent labs offer better long-term cost optimization.
Quotes
Sponsored segments
- Ryan Carson 44:17–44:21
About this episode
I welcome Ryan Carson back to the show to turn anyone into a world-class agent operator. Ryan spent 25 years founding companies, scaled Treehouse to around 110 employees and a million learners, and now runs Untangle, an AI divorce agent for family law firms, as a team of one while his revenue tracks toward 4x this month. He walks me through his full stack: running cloud agents in parallel, building automations that watch production and improve themselves, and shipping 22 to 40 PRs a day, often from his phone. We also get into keeping token costs sane through model routing and building a durable reputation by sharing your work on X. By the end, listeners hold a clear playbook to run agents, automate the busywork, and ship faster. Timestamps 00:00 – Intro 01:43 – The New Agent Paradigm 04:24 – Inside Ryan’s eight-screen desk setup 07:23 – Why Devin and cloud agents 10:00 – Everyone Is Now a Manager of Agents 13:15 – Local vs Virtual Development 14:50 – Agent Management System 24:22 – 3 Automations to build 32:54 – Self-improvement loop with Grace 34:38 – Token costs and model routing 40:33 – Building reputation on X 44:03 – Closing thoughts Key Points Ryan frames every knowledge worker as a manager of agents, and mastering that role is the new edge. Cloud VMs let Ryan run five to ten agents at once and ship 22 to 40 PRs a day. Roughly half of Ryan's work happens on his phone, which keeps his agents moving in real time. Automations like a production watchdog and a daily self-improvement loop hand Ryan a running summary of what matters. Model routing keeps costs in check: budget around $5k a month per employee and lean on cheaper fine-tuned models. Sharing your work publicly on X compounds into relationships and opportunities over time. Numbered Section Summaries Meet Ryan and Untangle Ryan Carson returns to walk me through his stack. He spent 25 years founding companies, scaled Treehouse to about 110 employees and a million learners, and now runs Untangle, an AI divorce agent for family law firms, solo, with revenue on track to 4x this month. The World-Class Agent Manager Ryan's core premise: everyone is now a manager of agents, and becoming the best in the world at it is the goal. He argues that managing agents makes you more technical over time, much like a skilled engineering manager. The Desk Setup and Key Security Ryan lays out eight screens, a 52-inch monitor, a UG Monk paper to-do system, a vertical mouse, and Whisperflow for voice. He stores all prod write keys in 1Password and hands them to agents only when a task truly calls for it, keeping production safe. Cloud Agents Over Local Machines Ryan explains cloud VMs: click a button, spin up a fresh environment, and run many agents in parallel while the code stays cleanly separated. He credits this shift for his 50x jump in output and urges builders to move work into the cloud as fast as they can. Staying Sane at 50x With 22 to 40 PRs a day, Ryan treats his job as making 10 to 20 high stakes decisions before lunch. He pins his most important threads, checks them on a roughly 25-minute cadence, and works from his phone so his agents keep moving. Automations That Run the Business Ryan shares three automations: an end-to-end signup test that browser-tests three times a week for about $60 in tokens, a 9am production watchdog that summarizes customer activity and links to real UI, and a daily self-improvement loop where an agent named Grace grades chats on a rubric and ships roughly three fixes a day. Token Costs and Model Routing After a $20k token month, Ryan settled on roughly $5k per employee plus heavy model routing, using cheaper fine-tuned models like SWE 1.7 for loop work. He favors independent agent labs such as Devin, AMP, Factory, and Cursor for affordable long-term engineering, while enjoying the subsidized Codex Mac app for everyday tasks. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND RYAN ON SOCIAL Ryan’s Website: https://www.ryancarson.com X/Twitter: https://x.com/ryancarson Untangle: https://untangle.us
Transcript
7,850 words · 2 speakers
Topics
- Devon
- Factory
- Fable
- Codex
- Cursor
- Cognition
- Untangle
- AMP
- Slack
- Claude Code
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