Augmented Awakening 2.0: Building AI Skills That Think With You
Most people are using AI to get things done faster. But there’s a deeper question that this session tackles head-on: what does it actually mean to think with AI, rather than just delegate to it?
Augmented Awakening 2.0 is a year-long monthly program co-taught with Anand Rao (developmentalmastery.com) for people who want to develop a genuinely different relationship with AI — one that sharpens your thinking instead of replacing it. We’re past the prompting era. We’re now in the agentic era, where AI can build, execute, and iterate on your behalf. Which means the bottleneck isn’t the AI anymore. It’s your ability to decide what to build, in what order, and why.
This session focused on one of the most practical and underrated skills in the agentic world: prioritization. Not a productivity hack, but a real cognitive skill — the ability to take a genuinely chaotic mental plate and turn it into clear decisions. We built a working AI-powered prioritizer skill inside Claude Code and Cowork, ran it live, and then went a layer deeper: building a meta-skill that improves the prioritizer itself over time. Second-loop learning, in practice.
If you’re someone who could build almost anything right now — and feels the paralysis that comes with that — this session is worth watching in full.
During the class, we:
Launched Augmented Awakening 2.0, the year-long agentic AI program
Explored the shift from prompting to leading AI agents
Introduced the “agent leader” framing — what kind are you?
Demonstrated a live “brain blurt” as the first prioritization step
Ran the Prioritizer skill live with Anand’s real messy project list
Watched 20 projects collapse into 2 decisions and 1 clock
Installed the Prioritizer skill in Claude Code and Cowork together
Introduced a meta-skill that reads your logs and improves the prioritizer
Discussed second-loop learning: skills that evolve how you use them
Answered participant questions on setup, sequencing, and memory logs
Implications
The skill Anand and I demonstrated in this session sounds deceptively simple: dump your chaos, let AI sort it. But what actually happened in the session was more interesting. When participants ran the Prioritizer, the tool wasn’t telling them what to do — it was asking questions that helped them hear what they already knew. That’s a meaningful distinction.
For years, the promise of AI productivity has been “do more.” What this session points toward is different: think better. Anand frames this through adult development research — the ability to make decisions under conditions of ambiguity, without perfect information, without perfect options, is a maturity skill. The Prioritizer isn’t a shortcut around that skill. It’s a way of building it.
The broader implication is one I keep coming back to: as AI agents get more capable, the leverage point shifts almost entirely to judgment. What do you build? What do you not build? What deserves attention this week versus what can wait until July? The people who develop that muscle — who can turn a chaotic mental plate into a clear sequence — will have a meaningful edge. Not because they’re smarter, but because they’ve practiced the skill with the right tools at their side.
