Something important ships every week, and it has never been easier or cheaper to try it yourself. That’s a gift and a trap. Curiosity is now one of a product person’s most valuable skills, but without some structure it turns into a flood of headlines and a graveyard of half-finished experiments. Here’s how I’d keep learning fast without drowning.
Most people keep up with AI the way they keep up with the weather: headlines, alerts, a scroll through someone’s thread. It feels productive and leaves almost nothing behind. The people who are actually getting better at this are doing something different. They filter hard, go deep on a few things, build small experiments, and bring what they learn back to their work.
The tools for that have never been better. A research agent can read everything and tell you only what matters to your role. A coding agent and a free hosting tier let anyone build a working experiment over a weekend. The risk is no longer lack of access. It’s lack of focus.
I build a lot of experiments, on weekends, for side projects, for a charity. Many were fun, and I learned less from them than I could have, because I didn’t stop to harvest the lessons. This is the system I wish I’d set up earlier.
The ideaFilter the flood with an agent that knows what you care about. Budget your time across scanning, going deep, building and reflecting. Run small, cheap experiments with a clear question. And harvest them: write down what you learned and bring one thing to work every month.
Illustrative numbers. Switch between reading everything and letting a personal agent filter for your role and questions.
The goal isn’t to know everything that shipped. It’s to know the two things that matter to you, deeply enough to use them.
Four activities make up real learning: scanning what’s new, going deep on a few things, building something, and reflecting on what it taught you. Most people over-invest in the first and skip the last. Pick a pattern to see what happens.
My estimates of how each pattern tends to play out.
Generic news alerts treat everyone the same. A personal research agent can be told who you are, what you’re building, which questions you’re chasing this quarter, and which companies and people to watch. It reads everything and brings back a handful of items, each with the part generic news never includes: what this means for you, and one way to try it.
It can also deliver in the format that works for you: a short written digest, an audio briefing for the commute, or a deep-dive explainer when something deserves an evening.
A sketch of a product manager’s research agent and two items from its weekly digest. The items are illustrative.
Agents can now pause and request sign-off above a configurable risk level, with an audit record of who approved what.
Grounded panels caught most layout problems but missed issues tied to users’ habits.
The fastest way to understand a new capability is to build something small with it. With a coding agent doing most of the typing, you don’t need to be an engineer or a designer. And the infrastructure is close to free: generous free tiers cover hosting, databases, storage and sign-in for anything at personal scale.
What turns tinkering into learning is a question. Every experiment starts with one, and ends with an answer written down, even if the answer is “this doesn’t work yet.”
One example stack. Free-tier limits as published for Cloudflare; check current terms before relying on them.
| Need | What I use | Free tier |
|---|---|---|
| Build it | A coding agent such as Claude Code, with the service’s own docs and skills | Your existing subscription |
| Run it | Cloudflare Workers | 100,000 requests a day |
| Store data | Cloudflare D1 (SQL) | 5 GB |
| Store files | Cloudflare R2 | 10 GB, no egress fees |
| Show it | A personal site that lists every experiment and what it taught | Static pages are free |
After a year of weekends, it’s easy to have dozens of experiments and no idea what they added up to. Once a month, look at them together. Group them by theme, notice where you keep returning, and write down the lesson, the pattern that repeated across experiments, not just what each one did. Then pick one thing to bring to work.
Illustrative. Each dot is one experiment. Pick a theme to see what harvesting it produced.
Sharing is the last step, and an underrated one. Writing up an experiment forces you to understand it, and a personal site that shows what you’ve built and learned is the most honest résumé a curious person can have. It’s also, quietly, what this site is.
Side projects can collide with your employer: check your agreement about outside work and intellectual property, and never put company or customer data into a personal experiment. Free tiers change, and a hobby project with real users needs real security. Curiosity can become avoidance, when building something new is more fun than finishing the hard thing at work. And learning can become one more source of pressure; the point is to stay curious, not to keep up with everything.