Behind the Craft

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Nan and Jacob built Linear Agent, which has transformed how the $1.25B company gets work done. In this episode, they took me from the initial memo to launch, showing how to give an agent tools to find the context it needs, use evals to improve reliability, and more. This episode is a must-watch if you want a concrete, behind-the-scenes example of how to build a production agent end to end.

We talked about:
(00:00) What’s holding AI agents back as models improve?
(00:51) Three things every good agent needs
(03:00) Demo: The internal memo that started Linear Agent
(09:50) The biggest mistake to avoid when building agents
(11:29) Demo: From Slack to code in 6 minutes with the agent
(17:01) When prototyping, “use the biggest model until it works”
(24:02) Give agents tools to find context, not more context
(34:07) The first thing to do before building an agent

Thanks to our sponsors:
Oceans: Hire AI-native EAs http://oceanstalent.com/peter
Riverside: All-in-one AI studio for podcasts and video https://creators.riverside.com/PeterYang
Linear: The AI agent platform for modern teams https://linear.app/behind-the-craft

📌 Get the takeaways: https://creatoreconomy.so/p/5-rules-for-building-ai-agents-in-production-linear-nan-jacob

Where to find Nan and Jacob:
Nan on LinkedIn: https://www.linkedin.com/in/thenanyu
Jacob on LinkedIn: https://www.linkedin.com/in/jacob-shumway-314a8366
Linear Agent: https://linear.app/docs/linear-agent

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Karan co-founded Nous Research, the company behind Hermes, the #1 personal agent and AI app overall on OpenRouter. I found him incredibly down to earth as we discussed why open-source AI must win, how Hermes gets better the more you use it, and even a live demo of how Hermes can mod your favorite childhood games.

Karan and I talked about:
(00:00) How Hermes differs from Claude Code and Codex
(02:20) Why every AI model now sounds exactly the same
(11:16) How to stop AI from saying “you’re absolutely right”
(15:16) How Hermes creates skills without bloating its context
(16:40) The open vs. closed-source debate on AI safety
(23:40) Using one Kanban board for humans and AI agents
(26:45) Demo: Rebuilding a childhood Sonic world with Hermes
(36:07) How two Discord friends built a self-improving agent
(42:40) How Hermes became its own biggest contributor

Thanks to our sponsors:
Riverside: All-in-one AI studio for podcasts and video https://creators.riverside.com/PeterYang
Linear: The AI agent platform for modern teams https://linear.app/behind-the-craft
Wispr Flow: 4x faster than typing with your voice https://ref.wisprflow.ai/peteryang

📌 Get the takeaways: https://creatoreconomy.so/p/hermes-co-founder-on-building-an-ai-agent-that-improves-itself-karan-malhotra

Where to find Karan:
X: https://x.com/karan4d
Website: https://www.karan4d.com/
Hermes Agent: https://github.com/NousResearch/hermes-agent

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Jason is a DevEx engineer on the Codex team. In our episode, he showed me how he runs his entire workday using Codex, from his chief of staff thread to the way he builds skills that learn how he works. Jason wrote the official OpenAI guidebook on how to get the most out of Codex, so don’t miss this episode.

Jason and I talked about:

(00:00) The only job left after AI can do the work
(02:40) Turn pinned threads into long-running workspaces
(05:50) Build a chief of staff across Slack, email, and Linear
(10:12) Teach Codex to write like you for every audience
(13:33) Mine past sessions for new skills and workflows
(20:01) How Codex revised a launch video while Jason was out
(24:23) Build a drum practice site around how you learn
(25:59) Goal, plan, and worklog for long-running Codex tasks
(33:52) Why taste starts with knowing what feels wrong

Thanks to our sponsor:

Google AI Studio: The fastest way to go from prompt to production https://aistudio.google.com/?utm_source=peteryang&utm_medium=partner&utm_campaign=26Q3-peteryang_ais

Riverside: All-in-one AI studio for podcasts and video
https://creators.riverside.com/PeterYang

📌 Get my personal AI OS with useful AI skills, $270 in AI tool credits, live monthly workshops, and courses on Hermes and Codex agents: https://www.behindthecraft.com/

Where to find Jason:
X: https://x.com/jxnlco

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Thariq works on the Claude Code team, and I’ve wanted to see how he builds for a long time. In our episode, he showed how to use /goal to keep Claude working, how he plans with Claude to remove unknowns before building, and how he runs a team of agents in Slack. He also shared why his team cut Claude Code’s system prompt by 80% and how he creates polished launch videos with Claude.

Thariq and I talked about:
(00:00) Goals, loops, and workflows to make Claude work longer
(04:48) Live demo: Creating a polished video with one prompt
(08:17) Plan by removing unknowns before you build
(14:32) How Anthropic uses HTML artifacts for planning
(18:35) Running parallel Claude tasks through Slack
(27:34) Using separate creator and verifier sub-agents
(31:08) How Thariq stays focused while Claude works in parallel
(34:07) Why Anthropic cut Claude Code’s system prompt by 80%
(37:01) How to become more technical when AI writes the code

Thanks to our sponsors:
Riverside: All-in-one AI studio for podcasts and video https://creators.riverside.com/PeterYang
Linear: The AI agent platform for modern teams https://linear.app/behind-the-craft
Wispr Flow: 4x faster than typing with your voice https://ref.wisprflow.ai/peteryang

📌 Get the takeaways: https://creatoreconomy.so/p/how-i-plan-build-and-run-loops-with-claude-code-thariq-shihipar

📌 Get my personal AI OS with useful AI skills, $270 in AI tool credits, live monthly workshops, and courses on Hermes and Codex agents: https://www.behindthecraft.com/

Where to find Thariq:
LinkedIn: https://x.com/trq212
Website: https://www.thariq.io/

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Jared is a Builder in Residence at Cognition, the team behind Devin. He showed me why teams often overbuild their first agents, and how simple prompts, better tools, and self-testing work together instead. Then he demoed one manager agent breaking down a task, directing 10 cloud agents, and deciding what a human needs to review.

Jared and I talked about:
(00:00) Why teams overbuild their first AI agent
(02:50) Let the model cook before adding rules
(03:16) Why tools matter more than better prompts
(10:51) Why you should build evals after shipping
(16:06) What cloud agents can do that local agents can’t
(20:30) How to get one agent to manage other agents
(25:39) Demo: One agent launches a team of 10
(28:03) How agents prove their work before you review it
(33:18) The best tasks for agent teams to work on

Thanks to our sponsors:
Riverside: All-in-one AI studio for podcasts and video https://creators.riverside.com/PeterYang
Linear: The AI agent platform for modern teams https://linear.app/behind-the-craft
Wispr Flow: 4x faster than typing with your voice https://ref.wisprflow.ai/peteryang

📌 Get the takeaways: https://creatoreconomy.so/p/how-to-build-ai-agents-that-check-their-own-work-jared-cognition-devin

📌 Get my personal AI OS with useful AI skills, $270 in AI tool credits, live monthly workshops, and courses on Hermes and Codex agents: https://www.behindthecraft.com/

Where to find Jared:

X: https://x.com/imjaredz
Devin: https://devin.ai

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