Lalit Maganti

Here's a great example of something written by a human that otherwise seems to have a similar structure to the OP: https://lalitm.com/post/building-syntaqlite-ai/ Flags for LLM vs human drafting: - Subtitles have the rhetoric turned to 11 with LLMs. (Note: Who has ever had multiple sentences as a blog post heading? It's bizarre) : - LLM "The Demo Works. Production Does Not." - Human "AI is why this project exist, and why it's as complete as it is" - Sources for claims that call for evidence - LLM "Six months ago, a practitioner could name a preferred OCR engine with confidence. Based on what I read, that confidence is gone." - *What was read?* - Human "AI coding tools and playing slot machines"[ref] - Variable paragraph lengths, where things that need more explanation have longer paragraphs (and vice versa) - LLM *Scroll through—each thing is about the same length* ---- There are lots of tells like this. This is a moment to get good at detecting LLM text in case it's surreptitiously used to your detriment.

Interesting, though I disagree on basically all points... > No Silver Bullet As an industry, we do not know how to measure productivity. AI coding also does not increase reliability with how things are going. Same with simplicity, it's the opposite; we're adding obscene complexity, in the name of shipping features (the latter of which is not productivity). In some areas I can see how AI doubles "productivity" (whatever that means!), but I do not see a 10x on the horizon. > Kernighan's Law Still holds! AI is amazing at debugging, but the vast majority of existing code is still human-written; so it'll have an easy time doing so, as indeed AI can be "twice as smart" as those human authors (in reality it's more like "twice as persistent/patient/knowledgeable/good at tool use/..."). Debugging fully AI-generated code with the same AI will fall into the same trap, subject to this law. (As an aside, I do wonder how things will go once we're out of "use AI to understand human-generated content", to "use AI to understand AI-generated content"; it will probably work worse) > just ask AI to rewrite the code This is a terrible idea, unless perhaps there is an existing, exhaustive test harness. I'm sure people will go for this option, but I am convinced it will usually be the wrong approach (as it is today). > Dijkstra on the foolishness of programming in natural language So why are we not seeing repos of just natural language? Just raw prompt Markdown files? To generate…

There's a good article about it. Saying no is a budget. In other words you don't have enough veto power to stop all bad projects so you need to be strategic about spending this budget. https://lalitm.com/post/why-senior-engineers-let-bad-projects-fail/

I also wrote recently [1] about Exponential Search [2] which is another algorithm if you need to repeatedly binary search in an array where the elements you're searching are themselves are sorted. It allowed for an 8x speedup in our workload! [1] https://lalitm.com/post/exponential-search/ [2] https://en.wikipedia.org/wiki/Exponential_search

Accounts (in the accounting sense) are unitless, and refer to whatever meaning we ascribe to them, so we can transfer value from $ to shares, or USD to GBP or whatever. Lalit describes this I think really well in his article https://lalitm.com/post/one-number-i-trust/#chapter-4-investments

> So in the open source community maybe, but it's use in the Android organization in Google is ubiquitous. Yes I know, I used to work on Android ;) > By split off, do you mean from a "branding" perspective? > And in practice, we've been working on the last year or so on "pluginizing" the UI - basically turning the UI into a modular set of components and separating the "core" of the UI (which doesn't know anything about Android or Chrome and reasons purely in terms of "tracks", "slices", "counters" etc). Yeah this is what I mean ^ > It's just that sometimes what we want to do for open source conflicts with what Google wants from us as a team in prioritisation. I actually talked about this in detail recently: https://lalitm.com/perfetto-oss-company-prio/ Yeah this is basically exactly what I mean, in fact I am kind of impressed that you nailed it down so precisely. I actually ran into that very bug and saw it get resolved in real time. I think this is a really good sign. > So this is one reason Apple Instruments is so good at what it does: it's a focused profilier helping you debug problems on Apple devices and so they can deeply bake that intelligence in the tool. No I don't actually care about this part, I am mostly talking about usability for general workflows… > At least for this example, Perfetto has this feature: when zoomed out, click on a slice in an area you want to zoom to and then press "f". It wil snap zoom into that section …like this one. I learned…