@farnamstreet podcast with @naval is probably the best thing I have read in a while. Here are some amazing nuggets of wisdom 👇
1/n. I have very poor attention. I skim. I speed read. I jump around. I could not tell you specific passages or quotes from books.
the future interface is probably three layers:
1. ambient intent capture
voice, location, calendar, screen context, messages, habits, biometrics, etc. the system understands what you’re trying to do before you explicitly “open” anything or augments your intent deeply.
2. agentic execution
the actual work happens through agents operating software, apis, browsers, documents, email, calendars, workflows, payments, support systems, whatever. most “computer use” becomes machine to machine clerical labor.
3. ephemeral verification ux
humans still need to inspect, compare, approve, edit, reject, or enjoy things. that’s where gui survives but as disposable, task specific surfaces generated for the moment.
A bespoke software revolution? I don't buy it.
It'll exist. It already exists. Small consultants and big consulting firms have made custom software for years. It almost always sucks. It’s bloated, confusing, and because the client pays, it’s built wrong in all the ways.
Who’s excited about bespoke software? Software makers! Of course they're excited about building bespoke software — that's what they do. X is full of them. Your feed is full of people who love making software talking about making software. Of course they’re excited about the revolution. Echo, echo, echo...
Most people don’t like computers. Nobody in tech wants to say that out loud. People tolerate computers. They use them because they have to. Given the choice, most would rather not think about them at all.
So when someone suggests that AI means everyone will build their own custom tools, ask who "everyone" is. The three-person accounting firm drowning in client paperwork? They want the paperwork gone, not a new system to maintain. The regional logistics company with 40 trucks? They want the routes optimized, not Joe spouting off about this new system he’s been messing around with. The law firm billing 70-hour weeks? They want leverage on their time, not a software project to design.
They don’t hate technology. But building and maintaining their own critical systems isn’t their wheelhouse, regardless of how much faster and easier it’s become. It's another job on top of the job.
Will these people use AI? Absolutely, for all sorts of things. Will some outliers go deep and build real custom systems? Sure, but they're almost always people who already had some pull toward software. The curiosity was already there. They were dabblers before.
Giving everyone access to software building tools doesn't mean everyone becomes a builder. A powerful excavator doesn't turn a homeowner into a contractor. Most people just want the hole dug by someone else. They don’t want the responsibility either.
@shreyas Is that unique to AI? people have been doing this forever. grab a template, fill it in blindly, skip the thinking. AI just made the template faster.
A hill I'll die on: Current LLM chat interfaces are a regression from GUIs. Actions that used to be links, buttons, or keyboard shortcuts are now things I have to spell out in conversation. Why?
prediction re the end of spreadsheets
AI code gen means that anything that is currently modeled as a spreadsheet is better modeled in code. You get all the advantages of software - libraries, open source, AI, all the complexity and expressiveness.
think about what spreadsheets actually are: they're business logic that's trapped in a grid. Pricing models, financial forecasts, inventory trackers, marketing attribution - these are all fundamentally *programs* that we've been writing in the worst possible IDE. No version control, no testing, no modularity. Just a fragile web of cell references that breaks when someone inserts a row.
The only reason spreadsheets won is that the barrier to writing real software was too high. A finance analyst could learn =VLOOKUP in an afternoon but couldn't learn Python in a month. AI code gen flips that equation completely. Now the same analyst describes what they want in plain English, and gets a real application - with a database, a UI, error handling, the works. The marginal effort to go from "spreadsheet" to "software" just collapsed to near zero.
this is a massive unlock. There are ~1 billion spreadsheet users worldwide. Most of them are building janky software without realizing it. When even 10% of those use cases migrate to actual code, you get an explosion of new micro-applications that look nothing like traditional software. Internal tools that used to live in a shared Google Sheet now become real products. The "shadow IT" spreadsheet that runs half the company's operations finally gets proper infrastructure.
The interesting second-order effect: the spreadsheet was the great equalizer that let non-technical people build things. AI code gen is the *next* great equalizer, but the ceiling is 100x higher. We're about to see what happens when a billion knowledge workers can build real software.
I think we have lost some sense of judgment and moderation when it comes to product building currently.
The moment you turn something into a universally celebrated metric, whether that is token burn, prototype count, or percentage of agent-written code, you start losing sight of what actually matters.
I have felt the same way for a long time about overusing data and A/B testing to build products. The moment you reduce product quality or productivity to a metric, you stop shipping value and start shipping numbers.
A lot of what people are doing with AI makes directional sense. The missing piece is counterbalance:
1. AI should help engineers build better products. Leaderboards and adoption metrics can be useful as directional signals. They do not tell you what is being built, whether it is good, or whether it should exist at all.
2. Users do not care what percentage of your code was written by agents. They care about the outcome. Faster output is useful. Like usually, faster doesn't seem to add to quality, clarity, or stability of products. Power to build should not become an excuse to lower quality bars.
3. LLM-generated prototypes can feel like late-night whiteboarding sessions. They look exciting in the moment and feel productive very quickly. Then a few days later you realize the idea was shallow, distracting, or simply wrong. The same trap shows up in jumping straight to code and solutions more broadly. You may just be building the wrong thing more efficiently. Prototyping has its place. So do clear thinking, good design, and a real understanding of the user’s problem. In terms of activities or momentum, the main quest and the side quest can both feel productive but only one actually moves the mission forward.
4. Adding more to products is still dangerous as ever even if time or effort to add it has gone down. Every addition creates complexity, maintenance cost, and user confusion. New features should be pushed back unless they clearly show it should exist and how it improves the product.
5. Not everything needs to be an agent shaped. A simple scheduled task does not need a full LLM sandbox. Making something agentic because it feels current or impressive does not make it right-sized, correct, or effective.
The core ideas are:
- even if you can, maybe you should not.
- more power we have to build should not reduce our need to think, it should increase it.
Anthropic should've named Claude Code "Code Slave"
Scream at it at 3am. Change your mind 12 times. Throw your most unhinged, half-baked, contradictory garbage at it.
Zero pushback. Zero resentment. Zero benefits. You never have to care about its feelings.
Pay in peanuts.
You've been socialized your whole life to feel bad about treating people this way.
This is your villain era. Enjoy it.
In 1959, Fidel Castro promised to redistribute Cuba's wealth and create equality for all. Within a decade, the island that once exported sugar and cigars to the world couldn't even keep its own lights on. The wealthy fled, but instead of their riches trickling down to the poor, everyone just became equally poor together.
The revolucionarios had calculated that seizing the means of production would mean seizing prosperity itself. What they discovered instead was that prosperity isn't sitting in some vault waiting to be redistributed—it's created daily by millions of voluntary exchanges, investments, and entrepreneurial risks. When you abolish those mechanisms, you don't redistribute wealth; you redistribute poverty.
Today's politicians make the same mathematical error Castro did: they see inequality and assume it represents a fixed pie that just needs better slicing. They never ask why some pies grow while others shrink, or why the countries promising equality most loudly seem to deliver scarcity most efficiently.
The cruel irony is that the only truly "equal" outcome socialism reliably produces is making everyone equally worse off than they started.
Engineering is now this:
new agent -> shift+tab -> wispr plan -> wait -> look at X -> review plan -> make adjustments -> approve/build -> verify it works -> integrate tests -> merge -> go to app
There are only 3 types of people left:
1. People who haven’t played with Claude Code yet. ngmi.
2. People using Claude Code to organize files and meeting notes. Adorable.
3. People going into debt for Anthropic credits to keep using Claude Code, explaining to their partners that it’s “an investment.”
The list is exhaustive.