How Do I Stay Current with AI?
Without Drowning in Noise.

Quality beats quantity. 2-3 focused hours per week is more effective than 10 hours of scattered reading. The key is consistency and application: read something, then try it. A weekly rhythm of one deep-dive article or tutorial, plus building something small, compounds faster than daily doom-scrolling AI Twitter.

For staying current without noise: 1) Follow 3-5 practitioners who build, not just commentate, 2) Read release notes from major AI labs (OpenAI, Anthropic, Google) directly rather than through hot takes, 3) Join one quality community where people share what they're building, 4) Subscribe to one curated newsletter (not five). Avoid: generic tech news sites, most YouTube thumbnails with shocked faces, anyone who calls every release 'game-changing'.

Most of it. Safely ignore: benchmark leaderboard churn (today's best model is next month's second place), AGI speculation and timeline debates, drama between AI personalities, minor version updates, and anything that sounds like 'X just killed Y'. Focus instead on: new capabilities that unlock use cases you care about, tools that make your specific work faster, and foundational papers that explain why things work.

80% hands-on, 20% reading. Reading creates the illusion of learning. Building creates actual skills. The sweet spot: read just enough to understand what's possible, then immediately try to build something with it. Even a failed experiment teaches more than three articles explaining the concept.

Yes, and it's one of the highest-leverage investments. A good coach acts as your personal AI news filter, telling you what matters for your specific goals and what to ignore. Instead of spending 10 hours researching which frameworks to learn, you get a direct answer in minutes. Coaching accelerates learning by cutting through the noise and focusing your limited time on what will actually move your career forward.

The minimum viable approach: 1) Pick ONE newsletter from a practitioner you trust, read it weekly, 2) Spend 30 minutes on Sunday scanning headlines to know what exists, 3) When you hit a real problem at work, then go deep on solutions. You don't need to know everything. You need to know enough to recognize when AI can help, then learn the specifics just-in-time.

It probably isn't, and you should hold the money. Most cohort dropouts are people who couldn't articulate what they were shipping when they signed up. That's why the consult exists, and why I turn down most applications. If we get on the call and you can't tell me what you'll have shipped at the end of week 8, I'll point you to the AI Native Engineer community until you can.

Yes, the cohort works for people shipping their first serious AI system whether the goal is to land a senior role or to launch a product. The shipped system serves both equally well.

You need to be able to code in Python or TypeScript. Complete beginners can follow the classroom they get access to before the cohort sessions to come in well-prepared.

You'll spend 3 hours every Tuesday in the live session and roughly 3 hours of async work in between, for 8 weeks. The Tuesday session time is fixed.

It's a four-figure investment that we discuss during the 30-minute consult, alongside whether the cohort is the right fit for your project.

Yes, most attendees do. The live session is one Tuesday a week and the async work fits around your existing schedule, as long as you can carve out roughly 6 hours a week.