Bot detection & human verification will be one of the most urgent demands for businesses over the coming years. Agent swarms will suffocate every website and form; small companies and government websites are most vulnerable.
There is a huge gap in the market for this right now. When we looked at what offerings were in the market to use at X, there was not a single company that brought together all the latest technologies so we had to do it all in-house.
Certainly in the beginning you might think that money is the answer. After that, you might think that more time is the answer. After that, you might think, I simply need to care more for the physical vehicle, or I want to learn more. Then it's really just about acquiring skills, maybe they're productive skills, or maybe they're just for fun.
And then, at some point, you have to sit in a room and be able to live with yourself. At the end of the day, you would want to be able to sit with yourself and not suffer.
If you've checked some of those boxes I just described and you're still suffering, that says to me that something has been missed. Certainly I found myself, after checking a lot of those boxes, still suffering.
It doesn't mean you have to go through that process in that order. In fact, it's much more helpful to dedicate part of your practice and your energies to viewing the psycho-emotional health as a foundation for everything else. And paying more attention to that from the very beginning.
P.S. Compartmentalizing pain and rationalizing it sometimes works. But as I’ve said to a lot of my friends who will sometimes say, “I don’t want to deal with that. I don’t want to open up that Pandora’s Box,” I try to emphasize that, at least from my experience, no matter what, you *are* dealing with it. But you get to choose if you want to deal with it head-on in a proactive way. Or if you want to have these odd side effects leak out the edges, unbeknownst to you, subconsciously sabotaging you day to day.
This is a great post if youre thinking about applied AI in the enterprise. The headline of this post is about what companies have huge upside from AI, but the deepest nuggets are about what AI transformation looks like in an organization.
It’s fundamentally about changing the underlying workflow or business process. As we move from chat tools to agents, those agents actually have to be deployed against workflows, which usually span multiple functions in an org. This is a different way of deploying AI than solely rolling it out to end users. It takes much more work upfront, but the results are the things that actually drive significant ROI.
“Software asks the employee to adopt a tool, but infrastructure changes the operating layer underneath the employee. The employee should still know what happened, and the process owner should still be able to pause the workflow, change a rule, approve an exception, or pull a person back in when needed. But the value should not depend on someone remembering to use the AI every day.”
The winners of this will be the platforms that can be deployed for specific workflows and business processes with a deep domain expertise. The playbook will often heavily require FDE support, change management, getting data well organized, be able to have comprehensive evals for the workflows, and much more to get right.
This is a critical post to read if you’re building an applied AI company right now.
“An application earns its place in the untrainable corner by doing unglamorous work: arranging a company's private reality so a model can act on it, handing the model the tools to act, working with the customer to change the reality of its workforce. A company that brings the translation is tough to copy – and the translation never ends. Integration and maintenance run as long as the relationship does, won by teams that put domain-specialized engineers and tools next to the customer.”
There’s still an insanely large gulf between model capabilities and what it takes to apply them to specific corporate workflows. Some of that is technology that needs to be built, a lot is access to (and formatting of) the right data to work with, and a ton more is on the change management and specific implementation work (FDEs, etc.) it takes to make AI work in any specific corporate setting.
2 things can be very true at once: frontier models and labs will continue to grow an incredible amount, and there will be a vast ecosystem of software and services companies that emerge to bring the power of these models to real enterprises. This makes room for new infrastructure provides, applied AI companies in every vertical, new versions of system integrators, and more players.
Incredibly exciting time on all fronts.
@0xisla Looking at the evolution of industries: transistors, hardware, software...they all had these cycles. For the most part they were the same...it takes decades evolve so we're still early.
https://t.co/scYeIGBbov
1980 but reads like today.
In 2026, Claude Code could finally unleash the golden age of local and decentralized apps.
The reason is that Claude Code allows you to quickly clone any moderately complex cloud-based app into a decent local one that runs on only your files.
This is an important update to Obsidian founder Kepano’s concept of “file over app.” His argument was that files are portable (and hence more reliable) but apps are not.
The new information is that apps are suddenly portable too. That is: apps of moderate complexity without strong global network effects are suddenly easy to clone. The clone won’t be perfect right away, but it’ll be pretty good. And if the cloning dev sticks with it it’ll get better.
So: can we get a local open source Mac app for everything, operating only on your files? Maybe we can make that a reality.
my assessment on where we're at as a society:
0. addiction is the dominant control structure of our late stage capitalism. the smartest algorithms in history are not designed to help us solve problems or become better, they are designed to hijack our reward systems and make us worse and miserable. a species that cannot resist dopamine hijacking cannot align itself and with a superintelligence.
1. loss of agency is more destabilizing than loss of wealth. chaos erupts when people feel powerless. when you can't sleep, can't stop scrolling, and eat junk, you lose self respect. this internal rot is projected outward as rage.
2. psychological breakdown precedes civilizational collapse. psychosis is what emerges when the world changes faster than our shared story can adapt.
3. most modern moral outrage is compensatory.
4. AI will accelerate identity erosion faster than institutions and individuals can respond. our identities are tied to what we do (work) and what we know (intelligence). AI is about to automate both.
5. stability is now a liability, we need plasticity. for thousands of years, success meant creating stability (i.e. building walls, storing grain). with AI, stability is death. success will be rapid adaptation which humans are very good at (though makes them very grumpy).
6. survival must become a conscious and institutionalized value system. this is warriors, caretakers and stewards of existence
7. only a species that values its own continuation can build aligned AI
In 5 years from now, probably 95% of the tokens used by AI agents will be used on tasks that humans never did before.
I just met with about 30 enterprises across 2 days and a dinner, and some of the most interesting use-cases that keep coming up for AI agents are on bringing automated work to areas that the companies would not have been able to apply labor to before.
Most of the world hasn’t quite caught on to this point yet. We imagine AI as dropping into today’s workflows and just taking what we already do and making it more efficient by 20% or something. Yet most companies realize that most of the time they’re doing far less than they could because of the cost or limited capacity of talent.
This shows up in different ways across every industry. In real estate it’s ideas like being able to read and analyze every lease agreement for every trend and business opportunity possible. In life sciences it’s being able to rapidly do drug discovery or improve quality by looking through errors in data. In financial services it’s being able to look through all past deals and figure out better future monetization. In legal it’s being able to execute on contracts or legal work for previously unprofitable segments or projects.
And these are just the Box AI use cases that deal with documents and content. The same is going to be true in coding, where companies tackle software projects they wouldn’t have done before. Security of all systems and events they couldn’t get to. And so on.
If you are working on AI Agents right now, the big opportunity is to bring enterprises “work” for problems that they couldn’t do before because it was nearly impossible to afford or scale.
And if you’re deploying AI agents in an enterprise, consider what things you’d do more of (or differently) if the cost and speed of labor became 100X cheaper and faster. This is going to get you the real upside of automation.
We need to build and accelerate.
But we need to accelerate the right things.
@VitalikButerin brought us some answers with d/acc.
Now, Zuitzerland is building a #dcombinator - a permanent village, and an open-source frontier tech accelerator as pilot for a network of d/acc hubs.
FROM ZUZALU TO ZUITZERLAND
https://t.co/7uPiqEWDVK
If you share d/acc vision and want to build a true decentralized city, bringing minds together to embrace technology, accelerating frontier tech safely...
Join our X Space this Friday at 6 PM UTC, where we’ll share what Zuitzerland 2025 holds and how you can be part of this journey!
Zuitzerland 2025 will focus on seeding long-term communities and bringing Zuitzerland’s vision to life with our residents.
Curious about what’s next? 👀
Just completed my 2nd of 6 "Therapeutic Plasma Exchange (TPE)" treatments at Fountain Life. My "longevity oil change" replacing 2.2 liters of gunk (inflammatory factor etc). Check it out www. https://t.co/ugyNj5IIf3