The first generation was built on large models, demonstrating what could be done and powering many tools.
The second generation is focused on reducing costs and saving time. Replacing workers or making them more efficient.
But you can’t shrink your way to greatness.
The third generation will be built on a simple premise, one that the internet has proven again and again:
Create value by connecting people.
We haven’t seen this yet, but once it gains traction, it’ll seem obvious and we’ll wonder how we missed it.
Create tools that work better when your peers and colleagues use them too. And tools that solve problems that people with resources are willing to pay for.
Problems are everywhere, yet we often ignore them.
And communities (existing and those that need to exist) are just waiting to have their problems solved.
[Here’s a list of network-based tech companies you may have heard of: Facebook, YouTube, WhatsApp, Instagram, TikTok, Reddit, LinkedIn, Wikipedia, Discourse, Airbnb, Etsy, Stack Overflow, Pinterest, Twitch, eBay, Squidoo, Snapchat, GitHub… You can’t use them alone, and they work better when others use them too.]
So far, most AI projects ignore the very network effects that built the internet. That’s almost certain to change.
For those with paraskevidekatriaphobia, consider this your opportunity to build something worth building instead of just waiting for the negative consequences of this change to arrive…
There is plenty of unintentional harm in our world. We’ve all been bruised or derailed by someone who had no ill intent.
We often respond with intentional harm, to make a point and to teach a lesson.
The alternative is clarity. Shared understanding instead of intentional pain.
Tap is going to keep coming. It’s the tip that’s up to us.
What an admirable goal. Perhaps the overriding goal of all goals.
How often do we measure this? Do we even know how?
Do the systems we’re in push us from considering this? I wonder why.
The challenge of the library is the card catalog. If you don’t know what you’re looking for, it’s hard to find much of anything.
The challenge of the web is the search box, for the same reason. It’s efficient once you’re on a mission, but it requires you to go first.
And the chat interface of Claude and ChatGPT is more of the same. Faced with infinite choice, what we really need is a guide.
By request then, ten places to start on this blog:
“Notes to myself” — 65 principles distilled from 10,000+ posts.
“The smallest viable audience” — This will reframe how you think about mass, about scale and about marketing.
“Seeking yoyu 余裕” — Perhaps we need more humanity and less more.
“Energy and systems complexity” — Systems thinking that connects beans to bureaucracies to solar panels.
“Failing in the trough” — A practical, visual framework anyone with customers can use immediately.
“The AI effort gap” — Six sentences that reframe the entire AI conversation.
“Enrollment” — The deep dive into how change actually happens — not through authority or money, but through people choosing the journey.
“Better than the cheap alternative” — What sort of work is worth doing? Particularly by you?
“The Strategy Questions” — 53 questions from “This Is Strategy.”
“This is number 10,000” — The meta-post.
It would be great if there were a similar service for your project, your work and your interactions with empty search boxes.
One approach: ask the AI what you should be asking about. A good librarian is priceless.
Sure, you made it work this time, but will it work next time?
Can you teach the method to someone else?
Do you have a protocol for what to do when it doesn’t work?
How can someone else contribute to your process to make it better?
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