The Tab Problem
Last Tuesday, I had 34 browser tabs open. All AI-related. A new ChatGPT model announcement. Some guy on X claiming Claude just replaced half his team. A paper about code generation benchmarks that contradicted everything I’d read the week before. Three YouTube videos saved in “watch later” — where videos go to die. An n8n workflow template that looked promising but required an API I’d never heard of.
I closed all of them. Went back to work. Shipped the feature I’d been building.
Then Wednesday came and I did the exact same thing.
This has been my life for the past year and a half. I suspect it’s been yours too. The amount of AI-related news, tools, techniques, and hot tips that show up every single week is genuinely impossible for one person to track. And I don’t mean “difficult.” I mean impossible. There are people whose full-time job is writing AI newsletters, and even they miss things.
But here’s what actually bothers me. It’s not the volume. It’s the uncertainty. When I see a new tool or technique, I can’t tell whether it’ll save me 10 hours a week or waste an entire weekend. The signal-to-noise ratio in AI content right now is maybe 1:20 on a good day. And most of the “signal” comes packaged in breathless Twitter threads that make everything sound like it’ll change the world.
I needed a filter. Not an algorithm. A human filter.
What Happened When I Started Talking to Other Devs
About six months ago, Karolína Vyskočilová and I started having regular calls. Karolína runs her own WordPress and WooCommerce business — she’s been in the game for 15+ years, originally came from linguistics, and has been using Claude Code and other AI tools daily since they became usable.
The calls started as informal check-ins. “Hey, have you tried this?” “Yeah, it’s hype.” “What about this workflow?” “That one’s actually great — here’s how I modified it for client work.”
Within a few weeks, we’d saved each other probably 20 hours of trial and error. Not because either of us is smarter than the other. Because two people covering different ground and comparing notes is exponentially more efficient than one person trying to cover everything.
That’s when it all clicked. If two people sharing notes saves this much time, what happens with ten? Twenty? A hundred?
That’s where Dílna.AI is heading. Not from a business plan or a launch strategy. From a simple observation that this works, and more people should have access to it.
Why a Community and Not a Course
We actually had a course planned. Dílna.AI was originally going to be a structured online course about using AI in professional development workflows. We’d built the curriculum, outlined the modules, figured out pricing.
Then we realized something that should have been obvious from the start: a course about AI tools is outdated before you finish recording it.
We recorded a module about prompt engineering patterns in December. By January, two of the five patterns were irrelevant because the models had gotten good enough to not need them. By the time we’d edited the video, Claude had shipped three major updates that changed how half the features worked.
A course is a snapshot. AI development right now isn’t a snapshot — it’s a live feed. What we actually needed was a format that could keep up.
A community keeps up. Every call can reflect what happened that week. Every Slack conversation can be about what someone tried today. The knowledge stays current because the people in the conversation have current information.
And honestly? The most useful thing in our calls with Karolína was never a prepared presentation. It was one of us saying, “I tried X on a real project and here’s what actually happened.” That kind of feedback doesn’t come from a course. It comes from a room full of people who work with AI.
What We’re Building
A Czech-language community for developers who use AI in their daily work. That’s the one-line version.
The longer version: we’ll run live calls twice a month where we break down the most important AI news and tools. Not everything — the stuff that matters for people who write code for a living. I’m already building an automated pipeline that pulls from about 50 sources, scores everything for relevance, and gives me a pre-filtered list to review. The actual human preparation will take about an hour per call instead of the full day it takes now when I try to keep up on my own.
Each call will follow a structure. Top headlines with context — what happened and why you should care (or shouldn’t). One deep dive into a specific tool or technique with a live demo. A section where members share their own discoveries. Open discussion. And at the end, a list of things to try before next time.
Between calls, there’ll be a Slack workspace for sharing tips, asking questions, and — knowing developers — arguing about whether AI-generated tests are actually useful. (They are, with caveats. I expect this will be a recurring debate.)
We’ll also publish a newsletter every two weeks with the key takeaways for people who can’t make every call.
The whole thing will run in Czech because that’s our audience. Czech developers solving Czech-market problems, discussing things in a language where they can be precise and natural instead of showing off their English fluency.
Three Levels, Because One Size Doesn’t Fit All
We’re structuring Dílna.AI into three tiers. Each one exists for a specific reason.
The open community will be free. Public Slack channels, the bi-weekly newsletter, and access to older call recordings. This is the entry point. If you just want to stay informed without committing to anything, this is all you’ll need. No strings, no credit card, no “free trial that auto-converts.”
Paid Professional membership. That’ll get you into the live calls, the full recording archive, private Slack channels, monthly deep-dive workshops on specific tools, quarterly state-of-AI reports, and early access to things like our prompt library and experimental workflows. We’re launching this tier in about two months — we want to build up a solid content archive and nail the format before we charge for it.
Paid Mastermind group. Maximum 10 people. Weekly calls with a hot-seat format where each person brings a specific problem or project and the group helps solve it. Direct access to the organizers. Quarterly in-person dinners with a talk and discussion. Joint experiments and projects.
The Mastermind is the part I’m personally most excited about. There’s something that happens in a small group of people who are all pushing in the same direction — you move faster than you would alone, and the accountability means you actually do the things you said you’d do. I’ve been in mastermind groups before for other things, and the ROI on time invested has always been disproportionately high.
Both paid tiers are opening soon. If you’re interested, you can register on dilna.ai and check the box for whichever tier you want — we’ll let you know when it goes live.
Try Before You Pay
One thing I feel strongly about: I don’t want anyone paying for something they haven’t experienced. Membership communities have a trust problem because too many of them sell access to a Slack channel with two messages a week and call it a “premium community.”
So we’re building a trial into the Professional tier. You’ll get two live calls as a guest. Full participation — ask questions, join the discussion, see exactly what you’d be getting. After the second call, you decide. No auto-charge, no “forgot to cancel” gotcha.
Who This Is For (and Who It Isn’t)
The ideal Dílna.AI member is a developer or tech lead who’s already using AI in some capacity and wants to get better at it — faster. Someone who’s tried Claude or Codex or Cursor but suspects they’re barely scratching the surface. Someone who reads AI news but can’t tell what’s worth their time.
It’s specifically for people who build things. React, WordPress, Laravel, Python — we don’t care about your stack. We care that you’re shipping real projects and want AI to help you do it better.
It’s probably not for you if you’re looking for a beginner’s guide to “what is ChatGPT.” We assume baseline competence. The conversations will move quickly, and nobody’s going to explain what a prompt is.
It’s also not for you if you want someone to tell you AI is going to replace all developers. We don’t believe that, and that debate isn’t interesting. AI is a tool. A remarkably powerful one that’s changing how we work, but still a tool. Dílna.AI is about getting better at using it, not philosophizing about whether it’ll take your job.
What Our Calls Already Taught Me
Even just the regular calls with Karolína have changed how I think about AI in my own work.
Before we started talking, I evaluated tools in isolation. I’d try something, form an opinion, and move on. Now I hear how someone else used the same tool on a completely different type of project, and my understanding is dramatically more nuanced. Cursor is incredible for greenfield React work but fights you on legacy PHP codebases. Claude Code handles large codebases better than anything else but needs very specific instructions for WordPress conventions. GitHub Copilot is still the fastest for autocomplete but falls behind on architectural decisions.
None of those are opinions I could have formed alone. They came from comparing notes with someone doing different work.
Scale that up to a room of twenty, thirty developers — each working on different stacks, different project types, different client demands — and the compounding effect is what I’m betting the whole community on.
Sign Up
We’re launching the open community soon. Free to join, no obligations.
Head to dilna.ai, fill out the short registration form, and you’ll be first to know when the Slack opens and the calls start. If the Professional or Mastermind tiers sound interesting, check those boxes on the form and we’ll reach out when they go live.
I’ll be there. Karolína will be there. And if our calls so far are any indication, at least one person on every call will say something that saves you a weekend of pointless experimentation.
That’s worth showing up for.