Hemanth

Introducing Code Review, a new feature for Claude Code. When a PR opens, Claude dispatches a team of agents to hunt for bugs.

Software will proliferate just as videos, music, writing did. The market structure will shift from a “fat middle” to mega-aggregators and a long tail. It’ll be a slower process due to network effects, but many traditional vendor lock-ins will get eaten by AI.

Is Traditional Software Engineering Dead? “Does this mean that traditional software engineering is dead? Absolutely not. Software engineers—even the ones who are not necessarily tuning or training AI models—these are now among the most leveraged people on earth. Sure, the guys who are training and tuning models are even more leveraged because they’re building the tool set that software engineers are using. But software engineers still have two massive advantages on you. First, they think in code, so they actually know what’s going on underneath. And all abstractions are leaky. So when you have a computer programming for you—when you have Claude Code or equivalent programming for you—it’s going to make mistakes. It’s going to have bugs. It’s going to have suboptimal architecture. So it’s not going to be quite right. And someone who understands what’s going on underneath will be able to plug the leaks as they occur. So if you want to build a well-architected application, if you want to be able to even specify a well-architected application, if you want to be able to make it run at high performance, if you want it to do its best, if you want to catch the bugs early, then you’re going to want to have a software engineering background. The traditional software engineer is going to be able to use these tools much better. And there are still many kinds of problems in software engineering that are out of scope for these AI programs today. The easiest way to think about those is problems that are outside of their data distribution. For example, if they need to do a binary sort or reverse a linked list, they’ve seen countless examples of that, so they’re extremely good at it. But when you start getting out of their domain—where you have to write very high-performance code, when you’re running on architectures that are novel or brand new, when you’re actually creating new things or solving new problems, then you still need to get in there and hand code it. At least until either there are so many of those examples that new models can be trained on them, or until these models can sufficiently reason at even higher levels of abstraction and crack it on their own… And remember: there is no demand for average. The average app—nobody wants it, at least as long as it’s not filling some niche that is filled by a superior app. The app that is better will win essentially a hundred percent of the market. Maybe there’s some small percentage that will bleed off to the second-best app because it does some little niche feature better than the main app, or it’s cheaper, or something of the sort. But generally speaking, people only want the best of anything. So the bad news is there’s no point in being number two or number three—like in the famous Glengarry Glen Ross scene where Alec Baldwin says, “First place gets a Cadillac Eldorado, second place gets a set of steak knives, and third place you’re fired.” That’s absolutely true in these winner-take-all markets. That’s the bad news: You have to be the best at something if you want to win. However, the set of things you can be best at is infinite. You can always find some niche that is perfect for you, and you can be the best at that thing. This goes back to an old tweet of mine where I said, “Become the best in the world at what you do. Keep redefining what you do until this is true.” And I think that still applies in this age of AI.”

Pure software is rapidly becoming un-investable.

The leader is not the one who eats first. The leader is the one who has the power to eat first but chooses to eat last.

People who don’t organize into tribes get wiped out by people who do.

Nothing worse than a slow failure.

There is unlimited demand for intelligence.

Envy is the acknowledgment of having lost a secret race.

Moltbook is the new Reverse Turing Test.

"Being unhappy is very inefficient." @naval

"Value your time. It is all you have. It’s more important than your money. It’s more important than your friends. It is more important than anything. Your time is all you have. Do not waste your time." @naval

There’s no point in learning custom tools, workflows, or languages anymore.

Better than being loved is to be in love.

Work with hardcore people on hardcore things.

Choose inspiration over envy.

The solution to anxiety is action.

AI is adapting to us faster than we are adapting to it.

Politicians openly admit that taxing cigarettes, gas, or alcohol is meant to reduce consumption. They understand perfectly well that higher costs discourage behavior. But when it comes to taxing income, that basic logic suddenly disappears. They pretend people will keep working, investing, and taking risks at the same rate while receiving less of the reward. You can’t have it both ways. If taxes discourage behavior, income taxes discourage earning. If incentives matter for consumption, they matter for production. This isn’t ignorance. It’s convenience. They understand incentives when it supports control, and deny them when it exposes the cost of punishing work and success.

Between two thoughts, where are your problems?