Paperclip: Hire AI Agents Like Employees (Live Demo)
I sit down with Dotta, the pseudonymous co-founder of Paperclip, the open-source agent orchestrator that exploded to 30,000 GitHub stars in under three weeks. We walk through a live demo where I pick a startup idea from my idea browser and we spin up a full AI-agent company in real time — hiring a CEO, founding engineer, QA agent, video editor, and content strategist inside Paperclip. Dotta shares practical tips on agent configuration, memory systems, skill installation, and the "Memento Man" mental model for keeping agents on track. The conversation covers everything from token spend management and agentic design patterns to the future of importable, shareable companies and the upcoming Maximizer Mode. Skills to build your agent team: https://startup-ideas-pod.link/skill-suite Timestamps: 00:00 Intro 02:32 What is Paperclip 04:21 Choosing a Startup Idea for the Demo 05:48 Setting Up your agents 07:51 Hiring Your First Agent and Creating a Plan 12:39 Agent Configuration and Persona Setup 17:08 Skills: Installing and Managing Agent Capabilities 21:02 How to Get Top-Quality Output from Agents 24:05 Token Spend Tracking and Subscription Usage 25:49 Agentic Design Patterns and QA Loops 29:05 Taste and Values: What AI Still Cannot Do 30:09 How Many Agents Run the Paperclip Project 32:32 Routines: Automating Recurring Agent Tasks 36:36 Who Is Using Paperclip Today 38:57 Shareable and Importable Companies 42:49 Maximizer Mode and What's Next 44:29 Did Dotta Expect It to Go This Viral? Key Points * Paperclip is a bring-your-own-bot orchestrator: it works with Claude Code, Codex, OpenCode, and any model on OpenRouter, so you are not locked into a single provider. * AI agents are "Memento Man" — they wake up capable but with zero memory, so you need heartbeat checklists, persona prompts, and written context to keep them effective. * The biggest lever for quality output is encoding your own taste and values into agent skills and brand guides, because AI can do everything except know what you actually want. * Agentic design patterns like engineer-to-QA review loops matter more than one-shotting an entire startup; structure prevents compounding errors. * Paperclip tracks every token spent and every task completed, solving the problem of running dozens of agent windows with zero accountability. * Importable, shareable company templates (like Gary Tan's G-Stack or a full game studio) point toward a future where you "aqua-hire" proven agent teams instead of building from scratch. Section Summaries 1. What Paperclip Is and Why It Exists Dotta built Paperclip because he was running 20–30 Claude Code windows at once and could not remember what any of them were doing. Paperclip sits between fully autonomous tools like Pulse and manual coding assistants, giving you a dashboard to define business goals, hire agents, approve work, and track spend — all in one place. 2. Agent Configuration and the Memento Man Model Dotta compares AI agents to the protagonist of the movie Memento: they are highly capable but have zero persistent memory. The solution is a heartbeat checklist that tells each agent who it is, what plan to read, which assignments to check, and how to store memory using a file-based Para system. When agents make mistakes, you add rules directly to their persona prompts. 3. Skills, Security, and Quality Control Skills from repositories like skills.sh extend what agents can do — for example, installing the Remotion skill so a video editor agent can produce animated content. Security is a real concern with third-party skills; badges and GitHub star counts offer directional trust signals but nothing is fully solved. Getting top-quality output still requires you to supply context, brand guides, and reference material. 4. Taste Is the Last Human Moat The frontier models still lack personal taste. The real secret sauce is translating your own values — design sensibility, success criteria, brand voice — into written instructions your agents can follow. I note that this is the same skill that defined great leaders and founders long before AI existed; the vehicle has changed, but the job of communicating vision has not. 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 DOTTA ON SOCIAL X/Twitter: https://x.com/dotta Paperclip: https://paperclip.ing/ Github: https://github.com/cryppadotta
Read Video · 文字稿与深度分析
一键获取文字稿与 AI 深度分析 — 免费体验
免费注册 · 无需信用卡 · 注册即获 150 积分,足够解锁本集
- 📄 完整文字稿含时间戳
- ✨ AI 摘要、关键词与思维导图
- 💡 核心要点与精彩引言
播客与视频,已可阅读
音频播客

Essentials: Using Meditation to Focus, View Consciousness & Expand Your Mind | Dr. Sam Harris
Huberman Lab
2026年7月23日40:49EN
How AI is breaking the internet (and what to do about it) | Matthew Prince
TED Talks Daily
2026年8月18日15:45EN
ChatGPT – The Super Assistant Era | BG2 Guest Interview
BG2Pod with Brad Gerstner and Bill Gurley
2026年3月15日1:03:40EN
310-刚被斩首的伊朗伊斯兰政权如何在1979年掌权?
独树不成林
2026年3月1日40:35ZH-Hans
#16 「23歳のことって何も覚えてないので大丈夫」
朝井リョウ・加藤千恵 信頼できない語り手
2026年5月22日1:02:02JA
Folge 1 - Ein verschwundenes Land
Zeitreise DDR
2025年11月9日22:49DE
视频

Google is SO back...
Wes Roth
2026年9月17日14:31EN
We Finally Got a Robot on the Show | EP 161
Hard Fork
2025年11月7日1:09:50EN
Screensharing top takes in AI/startups
Greg Isenberg
2026年7月9日1:24:53EN
从「上瘾模型」到「专注力训练」,如何在被算法理解的世界里重新找回主动?| 英文访谈 S9E33
声动活泼
2025年10月16日50:48ZH-Hans
«Современный урок по ФГОС: требования, этапы, цифровые решения»
ЯКласс
2023年4月11日1:39:24RU