Second for second, @tylercowen packs more substance into a talk than anyone I'm aware of. This is a clear, non-hysterical, and somewhat soothing discussion of our AI future.
Wilson wrote this in 1998. It is unbelievably prescient about not just the internet but how AI now dominates information/knowledge today + the idea that information itself becomes nearly free, but synthesis still depends on the prior knowledge a person brings to it.
Aluminium was once the most expensive metal on Earth - costlier than gold
Not because it was rare (it's the most abundant metal in Earth's crust, ~8% of it), but because extracting it from its ore was incredibly difficult
The Hall–Héroult process, invented in 1886 by two 22-year-olds, changed that — and with it, aluminium went from a luxury metal to something you wrap your sandwich in
Abundance is an interesting kind of censorship. Each day you know more and can answer less. Your search gets an AI answer, the answer turns into a chat, and the original question dies in the abundance of information.
We build India's AI infrastructure layer.
@Nyas_Io is live — Instant Postgres, no config, no DevOps.
This is just the start. Database → Agents → Memory → Judgment.
From Bharat 🇮🇳 for the world.
→ https://t.co/7Qw94QKZbi
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"When you solve a problem, you do not reduce the number of remaining problems. You increase it. Every solution unlocks new problems that were invisible before. Antibiotics solved bacterial infection and created antibiotic resistance. The internet solved information access and created misinformation, attention economics, and cybersecurity as entire fields. The car solved transportation and created traffic engineering, urban planning, insurance law, and emissions regulation."
The obvious path for designers in the AI age is to move closer to code.
But the more valuable path may be upstream: closer to the customer, the business, and the problem.
If everyone can prompt agents to code, the scarce skill becomes knowing why, what, and how to build.
Basit ve güzel bir anlatımla " tüm çokgenlerin dış açılarının toplamının neden 360 derce olduğunun ispatı. Hiç bir çocuk bu şekilde anlatıldığında bunu unutmaz.
Sorry to anyone who thought AI would mean we’d work less (at least for now). AI makes it easy to explore more than you did before, and so you start doing far more as a result.
I regularly have seemingly small things that end up quickly consuming 3 hours because the agent made it easy to get started, but you still have to do the rest of the work to complete the project.
This is work that I wouldn’t previously have handed out to anyone else, it’s just stuff that never got done because it took too long to do fully manually. And, counterintuitively, for some of these tasks as AI gets good enough at doing them, it even becomes economically worth it to hire someone to do it on an ongoing basis with agents. But until you could try doing them at a low cost you would never have tried.
This is why AI won’t automatically reduce work in the way we imagine because work isn’t static. Most companies have far more they can do than they have today, it was just hard to get started on it all because of the natural constraints of time and labor availability.
The jump from working with a chatbot to having an agent that actually helps automate a process requires a real amount of work.
Most companies will need to have dedicated people that are responsible for bringing automation to their teams, instead of leaving this up to every individual employee. Partly because the work is more technical than we imagine today, and partly because it’s just hard to do this as a side project.
The job spec is to map out new workflows with agents, implement new systems to deploy agents, make sure the agent has all the right (up to date) context to work with, wiring up internal systems to connect to the agents, creating evals for the agents, figuring out where the human is in the loop, managing the system when there are new upgrades, helping with the change management of the existing business process, and so on.
These jobs may come from IT or engineering, or live directly in the business function itself. They’ll be called different things depending on the company, and in some sense it’s the future of software engineering that you’ll see a huge growth of in non-tech companies.
Most companies will have to be hiring for this now or in the future, and it’s another example of the kind of new jobs that will be created in AI.
Experts aren't stronger because they are thinking harder in the moment.
They are stronger because they can see, almost immediately, what kind of problem they are looking at.
A CEO from one of our portfolio companies shared this with their team. I’m re-sharing it with their permission, because it resonated and reflects what all founders and CEOs should be communicating.
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We are living through a period of compounding change. And in moments like this, the biggest risk is no longer making the wrong decision. It is moving too slowly while the world moves around you.
There are two paths. We can play defense:
- Protect what we have
- Optimize what works
- Wait for clarity
It feels safe. It isn’t.
Or we can play offense:
- Learn faster than the environment changes
- Use new tools to solve old problems in better ways
- And create entirely new strategies and businesses
That’s where the opportunity is.
Challenge yourself to do things faster and better than you have ever attempted. Stay uncomfortable. Stay on the front foot.