Squared Away Life
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AI Agents Are Here: How to Build a Virtual Team for Your Life + Work (OpenClaw, Claude, Obsidian)

What happens when you stop treating AI like a chatbot — and start treating it like a team? In this episode of Squared Away Life, Camden sits down with his brother Kelly Bucey (a software developer) to unpack the seismic shift happening right now: the move from “glorified Google” AI usage to agent-driv…

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What happens when you stop treating AI like a chatbot — and start treating it like a team? In this episode of Squared Away Life, Camden sits down with his brother Kelly Bucey (a software developer) to unpack the seismic shift happening right now: the move from “glorified Google” AI usage to agent-driven workflows that can run reviews, build tools, and execute recurring tasks with minimal supervision.

They walk through how Claude Co-Work can access a folder (like your Obsidian vault) to generate daily plans, summaries, and structured reviews — then step into Claude Code, where AI can refactor, build, and ship real software from high-level intent.

Finally, Camden shares what’s possible with OpenClaw: a semi-autonomous, open-source agent system that can connect to APIs (calendar, tasks, analytics, CRM) and begin operating like a “shadow organization” — producing weekly reports, fixing issues like broken links, drafting content stubs, and generating daily research briefs.

This isn’t hype. It’s a new way of working: systems over stress, structure over chaos, and compounding clarity over time. If you want to build a personal operating system — and leverage AI to protect your attention and amplify your outcomes — this episode will give you a map.

Topics

  • Claude Co-Work skills: daily plan, weekly/monthly reviews, summaries
  • MCP (Model Context Protocol): connecting calendar + task systems
  • Claude Code: building software from intent, faster than traditional dev
  • OpenClaw: autonomous agents, permissions, APIs, cron jobs, and safety
  • The “bespoke software” future: why SaaS is getting disrupted
  • Running local models vs. API costs (and why Mac Minis are sold out)