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Any piece of software that depends on open source (which is almost every piece of software) has a network of human beings who are potential attack vectors - everyone with publishing rights to any of the packages in the dependency network for that software.
I guess our best defense right now is dependency cooldowns - giving new package releases a few days before upgrading to them, in the hope that supply chain attacks like this will be spotted by someone else.
One thing that's under appreciated on the website of the demos is the Stanford demo where Ben showed uh anywhere between 3 to 25 images you can reconstruct that entire Stanford quad. But the thing is we had to show it from aerial view. But every single input image is been standing on the ground taking a picture from the ground. So, everything you see are generated but according to the laws of reconstruction.
introducing better-result, my opinionated take on the rust result type for typescript after having written about 100 times
npm i better-result
*disclaimer*: if you can use effect-ts, you should use effect-ts
Their words now
every time i’ve built something without effect over the past almost 3 years ive come to deeply regret it and wish i had just done it from the start
i will never start another typescript application or project without @EffectTS_ it’s reached critical enough adoption, provides distinct tailwinds to agents, and has great cloudflare support
If every uh software engineer knew to watch out for false serial dependency chains, things where they were creating series of dependent operations that could not be optimized away or other sorts of architectural problems like that that cannot be easily fixed, then the world would look more like just wait and optimize the hotspot, right?
New: emulate a GitHub App in a few lines of TypeScript Generated App keys, installation auth and stateful repository APIs Develop locally, test in CI or give sandboxed agents their own isolated GitHub environment
In the era of base LLM scaling (2022-2024), I believed the LLM line of research would reach a capability plateau (as later seen with base LLMs).
In late 2024, after the o3 test-time compute demo, I changed my views: the new models were showing genuine fluid intelligence, and with this new line of work, the LLM line of research could achieve unbounded capability scaling. "There will be no wall."
And a working demo is 1% at best of the work that you have to do. The many nines of performance, the many nines of reliability that follow, that's where the real work happens.
And that's why every hype cycle produces a wave of absolutely spectacular demos and very few real products. And the recurring mistake of every cycle is spending on the demo when you should be saving for the nines.
It took us about 10 more years to begin providing a service, and then 5 more years to scale to half a million trips per week. So, the demo took 18 months, the product took about 15 years.
The governed have something the governors need: labor, tax revenue, military service, consumer spending. This dependency is the source of democratic leverage.
But okay, so to begin with, I think when it comes to TypeScript, Rust fits in as the backend language. That's where I would put it. I wouldn't use it in the front end. I think it's a pretty good fit for backends, API servers.
My opinion is that the least mature area is front end. There have been some attempts to compile Rust to Web Assembly and then run it on the web as a front end as a replacement for TypeScript. But if I was writing a web server, I would totally use Rust for the back end and TypeScript for the front end. I would not really go the web assembly route.
that the language that's most suited for AI is the language that AI has seen the most of in its training set, right? And that's why you could argue AI does really well on JavaScript and TypeScript and Python because it's seen an awful lot of it
But but the thing is like doing programming languages, you come to realize it's a long play. I mean, if if you look back at the the stuff I worked on, it it it goes in 10-year cycles at least. And TypeScript didn't really, for example, or C# for that matter. I mean, it took it it takes 10 years to get to, you know, version one is great, but it has all sorts of issues, and then you got to do version two, and then it's not until version three that it really starts to be great.
The thing that makes it interesting, I think, and and unlike pretty much any other programming language is the gradual typing. This This notion that you can have types, but you don't have to have types.
And we we full well knew that there was absolutely zero chance that we would appeal to the JavaScript ecosystem with a proprietary programming language licensed from Microsoft. No. No one was going to come. It had to be open source. There was just no two ways about it, right?
So, if we're checking 99% instead of 100%, well, heck, that's better than the 0% that JavaScript checked, right? And it gives you like language features that no other languages can provide because they can't get to 100%.
My go-to languages are TypeScript for web stuff, Go for CLIs and Swift if it needs to use macOS stuff or has UI. Go wasn’t something I gave even the slightest thought even a few months ago, but eventually I played around and found that agents are really great at writing it, and its simple type system makes linting fast.
elements, JavaScript reigns supreme. SvelteKit's efficiency and reactivity make it my framework of choice, and TypeScript's type annotations bring a welcome layer of confidence to my codebase.
I think basically what takes the long amount of time and the way to think about it is that it's a march of nines and every single nine is a constant amount of work.
As scholars like Nicolas van de Walle have pointed out, aid can also foster an unhealthy dependency—in his coinage, many African states live in a state of “permanent crisis”, where aid is large enough to reshape (and warp) the political economy around it, but not large enough to be fundamentally transform countries’ economies.
This is perhaps one of the first painful lessons anyone who has built an AI product quickly learns. It's easy to build a demo, but hard to build a product.
One thing that drives me crazy about the React ecosystem, and more specifically "tech influencers" and "thought leaders" in the space, is the infantilization of the developers using and working in it. I’m tired of reading takes like TypeScript generics, mapped types, etc should only be needed and used by library authors for most use cases. Or today’s discourse; Don’t use `useCallback’, ‘useMemo’, and React.memo. If you’re building anything beyond a simple CRUD app or a an incredibly focused app with few features, you _will_ need these features.
This is how I frame it: if the effort required to replace or fork a dependency should it go unmaintained is measured in engineer-months, that’s a critical dependency and retaining its maintainers probably makes good business sense.
Adding a dependency is a serious decision which requires consensus within the team, an audit of the new dependency, an understanding of its health and long-term prospects, and an ongoing commitment to re-audit them and be prepared to change course as necessary.
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