spamizbad

> I simply know that I can solve any engineering problem (that I can come up with) with the help of artificial intelligence. I've tried it a few times — it works.

I think you just need to push yourself to do harder problems. For me, I pushed pretty aggressively into the hardware space, building things as a hobby that I originally felt would be far too time-consuming. This is an area where AI can certainly help accelerate but asking it to make small changes can be an expensive (token wise) proposition, so it forces you think through all the critical decisions and research up-front, and let AI do the boring scut-work.

Yep, I think that's a very pragmatic decision given the state of the KiCad project (not that KiCad bad, but the current stable release lacks agentic-friendly hooks which will hopefully land in 11).

Everyone says this and then when the company experiences a round of layoffs everyone’s job gets harder, service gets worse and delivery slows down

This is very interesting, I'll need to give it a try. Currently been using Backplane (https://backplane.works/) which is a straight-up fork of Kicad.

Consumer-ready LLMs have been widely available to the public now nearly 4 years if you start counting at GPT 3.5. There's certainly some compression here but Karpathy does a good job of outlining how silo'd those experiences are: the bulk of the product penetration (based on headcount rather than token usage) is "derpy chatbots" (his words, not mine). Most of the actual token spend is likely done on the STEM side. We're talking about a technology today that currently only has significant penetration with <25M users.

People need to be patient and put in the work to build great products, rather than lament its slower-than-desired (albeit still quite fast) adoption curve.

I think people in the LLM space are being far too impatient with the general public and their adoption. And I think they need to start thinking harder about building products that genuinely enrich people's lives. Look at how long home computing took to establish itself with the public, then the internet, and finally social media. None of these trends happened overnight, and some were accelerated by other technological advances (social media-> smartphones).

The adoption of these technologies spurned ton of innovation in these spaces, and I feel like with LLMs its the first time I've seen genuine frustration from the industry directed towards users for not adopting the technology fast enough. This attitude did not exist in the 1980s, it didn't exist in the 90s, and it didn't exist in the 00s/early 10s either.

The problem is you won't be faced with a binary choice of certain death or a single unknown AI cure: You will have a choice between several established protocols AND several unknown AI drugs. You doing a dice roll or do you want to make an educated decision?

I think for many projects you're right. One niche where I disagree: reverse-engineering. You'll need to carry context on things cannot be derived from code immediately eg: past experiments, findings, decomposed schematics/firmware etc. Without this, models are prone to re-doing the same work continuously - which sometimes involves "expensive" (in terms of wall time) simulations.

"Vibe shift" is all the rage these days but one area where it's most apparent is modern software.

People of Raskin's vintage had a very humanist approach to computing. The mentality was very much an outgrowth of the cultural revolution of the 60s. Computer usage should be joyful rather than toiling. The computer should help you. It should make you feel good about what you create.

That stands in stark contrast today, where things are more hostile. Not just in terms of "Dark patterns", or writing off user needs for the sake of expediency... but even the way we talk about technology today. You need to use X, do Y or you're "not going to make it" / "escape the permanent underclass". It's bleak.

I recently restored a vintage Macintosh SE I picked up at VCF Midwest and despite its limitations that machine was an absolute JOY to use despite its limitations and nearly 40 years of age. This was a machine and software designed by Raskin's contemporaries and it shows.

It's been a while (well, 8 months) since I used Claude Code, but what I can say is that I greatly enjoy using the plan mode that comes baked into omp (oh my pi), especially for tasks around firmware development. I recognize that has a very different workflow than webapps though.

No quantitative improvements in test scores, but it seems to make kids socialize more: https://www.nytimes.com/2026/05/04/us/did-school-cellphone-b...

Oh I'd say its real. Years ago I worked as that senior who divvied up the work to a team of 4 mid-level engineers in that exact fashion (they were mostly Latin American contractors with limited english). We actually shipped some good stuff too!

Unfortunately, looking back, I could easily see Claude replacing 3 out of 4 of those developers. Myself + one other dev + AI would probably would've shipped a bit more a little faster. With that said tokens aren't free so the net cost savings would've been 2 dev salaries maximum.

I feel like PA-RISC actually landed with a handful of useful somewhat-complex instructions. It always struck me as the best architecture from that era, making the correct trade-off of avoided microcode but adopted stuff like completers and shift-and-add operations to minimize instruction count and maximize work done per pipeline.

One level above junk. Yikes.

Disagree: The era of "<Tech Giant> will eat your startup by throwing capital/devs at it" are over. Anthropic, OpenAI et al are under too much competitive pressure to chase every quixotic product idea.

This is more about the CHIPS act than the tariffs.

There's actually a housing shortage in the US so it's not like this is an architecture that is responsive to consumer or cultural preference and demand - local zoning laws do not even permit such freedom.

To an extent that's true, but while Zuck might be hands on but he doesn't typically micromanage his lieutenants. Alexandr was clearly in over his head, has never run anything resembling a high quality engineering org, and blew it up in less than a year. I think his days are numbered.

Lots of people blame Zuckerberg, but my own view aligns with the author in that much of this is falls on Alexandr Wang's shoulders (Scale AI's founder). It's perhaps somewhat ironic that the "MEI" guy (Merit, Excellence, Intelligence) was permitted to poach high-performing subject matter experts from key engineering orgs and reassigned them to data labeling - something that, let's be honest, is not where you want to allocate your top performers at an org like Meta.

This is one of those things where a (tech) celebrity founder was permitted to blew up a high-performing engineering culture. If shareholders knew the nuances of this they'd demand his ouster. His leadership has been lacking in merit, excellence, and intelligence.

I would say the claim that AI is going to replace most white collar work a very snake-oily term. The technology behind it however is very compelling and interesting.

I'm not sure if this was Flux, but one of those AI EDA tool companies had a somewhat absurd ad where the narrator stated the AI tool told them a capacitor was being used to block DC, and that's something they never learned while getting an EE degree. Now, I don't have an EE degree, but I feel like how capacitors interact with AC and DC are sort of "passive components 101" that even hobbyists learn quite early on.

The EDA space doesn't strike me as being anywhere near as SWE when it comes to AI.

Might be aimed at people who spec out the $5100 Macbook Pros with M5 Maxes and 128GB.

Texas is becoming a hub for educated professionals and Florida is a hub for non-college retirees

Nobody dies if instagram collapses. Might even cause more people to live.

Oh we already had that with a RIF earlier in the year.

I will also tell you, as someone who works at a company that's trying to remain profitable, that token spend has caught the eyes of finance and much like cloud spend they've already started applying pressure to control costs. This May my team is protected to use 30% fewer tokens than we did in April - this was by intention. I suspect we'll drop more in June.

You can’t lobby the Trump or “America First” crowd to not be themselves.

> But rich engineers and lawyers play boutique guitars - almost everyone else, including most professional musicians, still play Fenders (or one of the other big mainstream brands).

I'm familiar with this stereotype but two things:

1) Based on the data I've seen, a higher percentage of a boutique brand's guitars are purchased by working musicians than the mainstream brands. They're such a small segment of the market however those musicians seem rare by comparison.

2) Hobbyists, across all income levels, are responsible for the vast majority of gear sold. The working musician is really just collecting the "discount" from economies of scale afforded by this phenomena.

You have it backwards. You’d benefit tremendously from fixed PTO that pays out because you’re taking fewer than 10 days a year. Its biggest benefactors are low-seniority employees who take 20-30 days annually.

Fender does this with their headstock design for replacement necks only. However they forbid license-holding manufacturers from both selling a complete guitar with a Fender headstock shape and even showing the guitar neck on a finished guitar during the sale process.