aobdev

Huh, TIL. Thanks for pointing it out.

I think you’ve made an extreme leap in your interpretation of the comment you’re replying to…

Airlines have kept tabs on Bluetooth and WiFi hotspots as early as the Samsung Galaxy Note 7 incidents (2016)

I can’t tell if you’re making a joke about the current state of AI and GPUs or refuting the purpose of this driver

Wasn’t this the same argument for .jar files?

I really don’t see how you came to that conclusion—that Mac was overpriced and underpowered, and only had the single usb-c port. Neo has better battery life, a better display, a more capable processor, and a much lower price (9 years later no less).

I've been very pleased with my ViewSonic VP2488-4K. A little steep for $550, but if you spend any significant time in front of the screen I think it's very much worth it. I'm planning to buy a second one.

But isn’t this what the article is saying? Even with AI you’re still not going to build your own payroll/ERP/CRM.

I believe that. Companies will build cheap tools today while competitors are spinning up to undercut ADP, Salesforce, and SAP. But what happens tomorrow? There are plenty of examples in IT today where the reasonable option is to outsource in 90% of cases: don’t roll your own auth, don’t host your own email server, don’t build your own data center. I don’t see how AI can change that, when the people who build specialized software also have access to AI.

Another great example is open source. I think PostgreSQL being free and usable by everyone is a more economic outcome than every Fortune 500 company building their own database engine. Payroll, ERP, and CRM fall into the same category of being commodity software in a lot of cases.

I don’t doubt it but that doesn’t negate the fact that Slack as a company exists and makes money by selling software. My question is this: AI makes it cheaper to build software, but ADP, SAP, and Salesforce also have access to AI and could make cheaper versions of their products. How does AI change the build vs buy trade off in a way that eliminates economies of scale? My opinion and that of the article is that it doesn’t.

Why does AI make it cheaper to build internal but not cheaper for SaaS competitors to pop up? Everyone has access to the same tools.

That’s a fine example, but my question then is why does Slack exist? Surely Fortune 500 companies are smart enough to realize that building a slack clone is cheaper, yet they don’t do that.

So now consider AI, perhaps the cost of building has decreased from 100k to 10k. What stops a Slack competitor from also building the product for 10k and reselling it at 10% of the cost of Slack? My point is that I don’t see how AI has changed the value prop.

Thought exercise for those in disagreement: why would every company use AI to build their own payroll/ERP/CRM, when just a handful of companies could use AI to build those offerings better?

This is largely how things work now; AI may lower the cost and increase margins, but the economics of build vs buy seem the same.

Check the article, AI interpreted the phrase “continuously merged” as “continvoucly morged”

The analogy should be obvious--a model refusing to perform an unethical action is the lock against others.

If that's what they're referring to, then my question is why does that need to end?

I understand selling the Teensy line is out of your control, but what does “support” mean exactly in this context? Will related materials stay on your site?

I really hope this doesn’t lead to “boycott” of Teensy per se. I completely sympathize with tensions running high but please reconsider for the good of the community.

It’s not just carrying their products. They are the exclusive producer of Teensy boards and are distributing them to many resellers but not to Adafruit.

From the subheading: “plus new AI features and premium content in Keynote, Pages, and Numbers”

From the subheading: “plus new AI features and premium content in Keynote, Pages, and Numbers”

Have you worked on different types of Python projects? (Not in different codebases, different types of codebases)

I don’t have any specific complaints about Python syntax because I can force it to get the job done…but homogeneous, it is not.

Sorry but you don't get to claim capital gains on retirement distributions, they are entirely taxed as ordinary income. If your tax rate later will be 40%, you get the exact same result: 3000-1200=1800.

If your tax rate will be lower in retirement, favor pre-tax contributions. If higher, favor after-tax. The trick is knowing what tax rates will be years (decades?) from now.

I'm not familiar with the strategy you're describing, but this is not how it works for the majority of backdoor Roth contributors.

If you have $100k pre-tax in a trad IRA, contribute 7k after tax for the purpose of rolling into a Roth, then you will owe income tax on the proportion of 100/107*7k, or $6,542.

You're still limited to 7k annual (for 2025) so the 14k you describe must be something else.

"TypeScript-first schema validation with static type inference"

It's a generated column, so there's no overhead to keep it up to date, but all generated columns in PG are stored. The corpus for text search will be stored 1x in the source column, 1x as a tsvector in the index, and an additional 1x in the generated column if you do so. That's a 50% increase in disk space.

This is not my area of expertise so take this with a grain of salt, but my initial instinct was to question why you would need to store the tsvector both in the table and in the index (because the tsvector values will in fact be stored losslessly in a GIN index).

The PG docs make it clear that this only affects row rechecks, so this would only affect performance on matching rows when you need to verify information not stored in the index, e.g. queries with weighted text or queries against a lossy GiST index. It's going to be use-case dependent but I would check if your queries need this before using up the additional disk space.

Snark aside, Joel is suggesting that because Fly uses rust-based virtualization software they should have a more reliable deployment process.

There are plenty of mature front end SPA frameworks that would work perfectly fine with Adonis. If you want to build traditional server side templated pages they provide a templating engine called Edge, and the docs tell you how to use Vite to bundle assets. If you want to make pages feel like an SPA without using a framework, they suggest Inertia as another comment points out. What do you feel is missing?

OpenAPI has a handful of open source API explorers. The ones I’m familiar with are Swagger UI, Redoc, and RapiDoc.

OpenAPI 3.0 has this concept of remote references, which can be URLs to other OpenAPI specs hosted anywhere. https://swagger.io/docs/specification/using-ref/

I’ve seen comments here on HN about people having similarly visceral reactions to the name CockroachDB and swear they will never use it for that reason alone. I always laughed at the absurdity but now I actually have some sympathy towards this type of reaction. If I opened the docs for an unsuspecting python package and was greeted with a detailed, half-screen photo of any arachnid I would probably throw whatever device I was using.