The AI Honeymoon Is Over
Building is the easy part.
We've made building things with AI incredibly fast. Now we have to deal with the much harder problem: getting people to actually care.
AI Can Build Your App in a Weekend, But Can't Find You a Single Customer
A viral Reddit discussion pulls back the curtain on the unsexy truth of SaaS: distribution is the only thing that matters now.
AI has made building a product comically fast. A Reddit thread from a founder this week served as a sobering reminder that AI has done nothing to make getting customers any easier. We've optimised the easy part, leaving the brutal, unsexy work of distribution, marketing, and sales just as hard as it ever was.
The uncomfortable truth is that accelerating development just creates a more crowded market. Simply having a great, AI-built product is no longer an advantage when thousands of others are doing the same. The real moat isn't your tech stack; it's your ability to get your product in front of the right people and convince them to care, a task that involves costly acquisition, high churn, and building trust AI can't automate.
This changes the game for founders. The new challenge isn't speed-to-MVP, it's proving you have a viable distribution strategy from day one. If your entire plan is to build it and hope they come, you're building a beautiful product that no one will ever see.
The New PM Power Tools
While AI struggles with distribution, it's definitely changing how we build and prototype products.
Alloy: Your prototype is now indistinguishable from the real product
This collapses the design-to-feedback loop from days to minutes, blurring the line between a mockup and a live feature. That's powerful, but also means bad ideas can look deceptively real, faster.
Screen Ruler: The pixel-perfect police for your browser
As we build faster with AI, the demand for precision and quality control only increases. This is the necessary counterbalance to rapid, sometimes sloppy, iteration.
Your AI Cofounder's Toolkit
The smartest developers are treating AI less like a magic code generator and more like a tireless workflow assistant.
Ultracite v6: The code linter that gets your AI pair programmer in line
This isn't just about clean code; it's about creating a consistent environment where human and AI-generated code can coexist. It's essential plumbing for the future of collaborative development.
PRs MenuBar: Never lose a pull request in your browser tabs again
Focused tools that reduce context switching are becoming invaluable. AI can create more work, like more pull requests, so we need simple utilities to manage that new volume.
Quick hits
Sheets Organizer: Your spreadsheet's digital Marie Kondo
Finally, folders for your chaotic Google Sheets tabs because we all have that one workbook that's a digital junk drawer.
Swetrix: The anti-Google Analytics
This open-source tool offers cookieless web analytics, letting you understand your users without being creepy.
Retro App Icons: Retro is the new modern
Iconcraft now generates 2010s-style skeuomorphic icons, because in a sea of flat design, a little texture really stands out.
My takeaway
Technology consistently solves the wrong problem first.
We celebrated AI making product development ten times faster, creating a flood of new tools. But we ignored that the market's capacity to absorb new products didn't also grow ten times. The real bottleneck was never the building; it was, and still is, earning attention and trust.
This forces a shift in focus from engineering velocity to distribution strategy. The most successful founders won't be the ones who can build the fastest. They'll be the ones who can build a community, a narrative, and a distribution channel just as efficiently as they build code.
What happens when the best builders aren't the best marketers?
Drop me a reply. Till next time, this is Louis, and you are reading Louis.log().