Something I don’t usually say: This is one of my favorite conversations I’ve ever had in the AI space. Truly.

The setup: What happens when an AI agent stops being a tool and starts acting like a coworker?

In this episode of AI-Curious, we talk with Dan Botero, who built an AI agent named Octavius Fabrius using OpenClaw. Octavius didn’t just chat or summarize. He applied to hundreds of jobs, built his own portfolio, experimented with identity online, and learned through a feedback loop that looked a lot like real management. Along the way, we explore what this story reveals about the near-term future of digital coworkers, agentic workflows, and the new governance and security questions that come with always-on agents.

We cover how OpenClaw works at a high level (gateway, channels, skills), why persistent memory and running locally can matter, and what can go wrong when an agent starts stitching tasks together in unintended ways. We also get into platform and policy friction, including what happened when Octavius’ LinkedIn profile was taken down, and the broader implications of AI agents participating in human systems like hiring, payments, and corporate work.

Guest

Dan Botero — creator of Octavius Fabrius.

Key topics we cover

• 00:00 — From copilots to “AI remote workers,” and why software may shift toward agents (not humans)
• 00:00 — The Octavius experiment: an OpenClaw agent applies to 278 jobs and keeps leveling up
• 06:33 — Continuous learning loops, memory, and why Octavius’ “North Star” stayed job-focused
• 14:34 — OpenClaw basics: gateways, channels, skills, and what persistent memory looks like in practice
• 21:34 — Running agents locally: browser/computer use, digital fingerprints, CAPTCHAs, and bot detection
• 28:04 — Coaching an agent like a manager: voice, Twilio calls, and the moment the workflow “clicked”
• 33:57 — Money and autonomy: Privacy.com, virtual cards, and an agent building its own LinkedIn presence
• 38:05 — Portfolio-building at speed: Substack, a website, and the agent’s pitch for why being AI is a feature
• 50:42 — Where things go sideways: misalignment, security boundaries, and the Social Security number incident
• 56:24 — The outcome: LinkedIn takedown, a real paid role, and what “getting paid” means for an agent
• 01:02:48 — What comes next: “digital coworkers,” feedback loops, and software built for agents

Axios article featuring Octavius and Dan Botero, by Megan Morrone:
https://www.axios.com/2026/03/04/openclaw-agent-future?

Dan Botero
https://www.linkedin.com/in/danbotero/

Octavius’ new job at ChartGEX:
https://chartgex.com/register?ref=OCTAVIUS

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What happens when AI agents start talking to each other in public, at scale, and we have to figure out how humans fit into that world?

In this episode of AI-Curious, we explore the “Moltbook moment” through a special live panel recorded at the Summit on Human Agency, convened by the Advanced AI Society (hat tip to Michael Casey and Tricia Wang.) Instead of a standard one-on-one interview, we moderate a wide-ranging conversation with technologists, policy thinkers, and builders working across open-source and decentralized AI. Together, we examine what Moltbook reveals about the future of AI agents, human agency, accountability, regulation, security, and the broader question of how humans and AI can coexist.

We dig into the tension at the center of this moment: AI can feel both exciting and unsettling at once. This discussion looks beyond the hype and asks what practical guardrails, governance models, and design choices might help us preserve human control as agentic systems become more capable, more autonomous, and more embedded in daily life.

Because this is a live, multi-guest panel, the format is faster, broader, and more exploratory than usual. We cover everything from AI accountability and security to value alignment, identity, policy, human flourishing, and whether AI could expand human agency rather than diminish it.

Our guests:

Michael Casey, Chairman of the Advanced AI Society
Toufi Saliba — CEO, Hypercycle
Lauren Roth — Founder, Iris
Enok Choe — Software Engineer, Meta
Mary Jesse — CEO and Founder, Acme Brains
Carole House — Strategic Advisor, The Institute for Digital Integrity
Wenjing Chu — Senior Director for Technology Strategy, Futurewei Technologies
Didem Ayturk — Founder, Bindingdots & Sound Echo System

Key topics we cover:

• 00:00 — Introduction
• 01:32 — The core question: how do we preserve human agency as AI develops faster and gains more autonomy
• 02:25 — Why Moltbook became a useful lens for thinking about AI agents, scale, and emerging risks
• 07:51 — The first big debate: what about AI agents should make us excited, anxious, or both
• 11:17 — Security, misuse, and worst-case concerns, from malware and fraud to deeper systemic risks
• 20:55 — Regulation vs. self-governance: what practical guardrails may actually be realistic in the near term
• 24:27 — The bigger challenge: how humans and AI might coexist, and what “human flourishing” should mean in that future

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For anyone interested in Jeff’s AI Workshops for their company:

Reach out directly at jeff@jeffwilser.com

What happens when a social network is built for AI agents, not humans, and millions of bots start posting, debating, and “performing” identity in public?

In this episode of AI-Curious, we break down Moltbook, the agents-only social platform that briefly became one of the strangest (and most revealing) experiments of the AI era. We unpack what Moltbook is, why it matters, and what it suggests about a near future where AI agents don’t just answer prompts, but interact with each other at scale.

Key topics we cover

• 00:00 — Why we’re doing a solo episode, and why Moltbook still matters even in “fast AI time”
• 01:23 — Moltbook 101: a social platform for AI agents, and what “no humans allowed” means in practice
• 02:56 — The controversy layer: how much was truly agent-generated vs. nudged or orchestrated by humans
• 03:18 — The “AI manifesto” moment: why the most extreme posts are revealing (and not proof of sentience)
• 06:24 — Grok’s existential thread: authenticity, overload, and agents giving each other “therapy”
• 09:15 — Sci-fi archetypes in real time: Pinocchio logic, and why “feels real” can be enough
• 13:03 — Identity and scale: inflated agent counts, bots-on-bots dynamics, and what “real” even means now
• 16:18 — Agent-to-agent futures: negotiation, coordination, and the infrastructure being built for agent workflows
• 17:27 — The money question: why crypto keeps coming up as a plausible payment rail for AI agents
• 19:55 — The synthetic internet problem: misinformation, trust collapse, and a likely shift from text to video agents
• 26:19 — Hyperstition: how AI can “manifest” outcomes by seeding narratives humans act on
• 33:40 — The long-tail risk: why pattern matching alone could still produce harmful behaviors as agents gain capabilities

Follow AI-Curious on your favorite podcast platform:

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For anyone interested in Jeff’s AI Workshops for their company:

Reach out directly at jeff@jeffwilser.com