rad_val

Ok, so, how is Figma still relevant today when agents can write any design in HTML?

Easier to maintain, scale, and can use most of the components of the design system directly if you're doing web.

I don't think you know what discipline means.

I think the answer to this question is deeply uncomfortable in 2026.

Softly put, it's discipline, focus and a sense of greater purpose, far above the monetary value of things, fame and fortune.

In other words, exactly what our current, consumer-oriented society lacks. (for better or worse)

The level of detail can vary while keeping the idea intact. You wouldn't be more overwhelmed than when you walk down on any european old city centers.

There are many ways one can be smart. Having an intuition for solving complex problems is not the same trait as having a good memory or controlling your emotions or being environment and self aware.

Many are overlapping traits sure, but someone that has them all, can easily be the worse at each one, when compared with others that excel in that area. This is why you see so often brilliant people doing idiotic stuff.

So, "everyone's stupid" is a matter of alignment, in the areas you're best, where you can judge best, few around are better. Which can be true while still not making you the smartest person around in all ways.

I don't agree that this iuis an indicator of any kind of intelligence other than social intelligence (e.g. don't say stupid things that affect your life, in other words socially intelligent people keep it to themselves)

Yeah, common knowledge sadly. Can get even worse, a friend had recently an interview with a, not-so-well-known, but you heard of them company and they didn't do any face to face interview, just AI driven via email, all steps. When he failed a step: they offered him some credits on the platform, literally a funnel via a job post (it's a dev platform).

The weird thing is how most of the comments here are from dads saying it's hard but worth it in various ways. I've been scrolling for a while and failed to find an alternative point of view.

After Opus 4.8 intelligence really started to matter less and less for the programming tasks I have. If I have to handheld anyway, why would I wait more or pay more?

kinoto.io/orrery

We're releasing this next week.

I wasn't assuming anything. Generally speaking.

The flow you describe in that comment is rather simple in my opinion and with the right harness even Sonnet would drive most of that.

I judge by the ability to bugfix complex codebases and the direction it takes in architecture. In my opinion, that's a tad more complex (and easier to objectively measure) than orchestrating tickets, no matter how complex.

Step 1: don't trust benchmarks you don't understand - they might measure irrelevant things Step 2: test it on things you know Opus failed

My day-to-day take, for the coding I do (not security related): incremental, modest improvement, if any. Not worth the 2x cost. I've calmly continued to use Opus, happy that it seems like it got an allowance upgrade.

I'm more interested why you think my understanding is flawed honestly. I thought I distilled it decently well in two sentences. The bottom line is, in this hyperdimensional space you can find relationships that are not easily distinguished by human minds, but the corpus is still fixed, a llm can't truly know anything beyond its training data.

The strongest argument for this is structural: what LLMs are.

In a brutal simplistic way: each token is represented in a high dimensional vector. LLMs operate on them. They are the true, underlying meaning of the token for the LLM. Think of it as 1000+ ways to think of that word/token. Those meanings are baked in at training time. So, LLMs might be able to cross-reference them and solve a class of problems that flew under our radar, but can't come up with revolutionary theories that were never in the training set.

Of course, they will help winning a Nobel in the years to come, no doubt, but can't speak mathematics we can't understand (beyond simple obfuscation) and won't discover anything substantial on their own.

AI (in this form) will never be able to solve things we truly cannot solve yet. It might catch things that we didn't project properly or brute force things no human can , but it will never unify general relativity with quantum mechanics. It's amazing at finding hidden truths in large datasets, but won't win a Nobel unassisted.