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anecdotally i'm finally starting to see things actually ship in the past year that aren't just "use the AI to build more AI harness" and it's roughly these categories in order: 1. software made by single programmers with a cohesive vision, that would've previously taken a mid-size startup

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As a non programmer but advanced Excel user I've been able to build an entire alternative program with all the things I ever wanted Excel to do better. It's fantastic

behind the scenes you also see - internal tooling apps that otherwise just dont get built - bespoke infra that replaces decent-but-misfitted open source - a lot of prototypes from members of the staff who otherwise would be blocked waiting for design team

yeah, I've been building an internal gpu+token spend dashboard that's better than any available SaaS product sure it cost $2k in tokens, but even the amortized salary cost to hold meetings to discuss vendor selection would've cost more than that

Yeah, everything cost something. I had to drink the blood of an unblemished ram to get our hosting platform going but the results are better than anything you can get off the market

2. enterprise rewrites of already-working software, to get some enterprise-desirable property, that isn't immediately visible and therefore would've previously been unaffordable 3. software made by non-programmers (academics, hobbyists) that couldn't get programmer resources before

4. rewrites and ports of legacy or even abandonware software that would've never happened otherwise 5. algoslop, like "claude make me a profitable saas app on the app store". exists but it's actually quite rare to *see* it because nobody's sharing this stuff

what I haven't seen as much of, is rapid buildouts to prove out new end to end research programs in software that unlock truly new paradigms in architecture, development, or deployment. that *aren't* just new Gastowns

another one i've wanted to build for a while is a compute environment based on hot reloaded wasm modules with fully qualified namespacing/content-addressing so you can have N branches of any given function or module within the binary and do things like parallel evaluation and shadowing

build seems to be an area ripe for total disruption in this space. imagine a Bazel-like where all components are distributed, mesh-based global caching, worktree oriented, agentic integration - that would've been an intimidating years long buildout. now it seems approachable for a small team

Also anecdotal, but I have been seeing that some companies evolve internal systems for better support of automation with human in the loop processes. This does show up in earnings reports when especially promising-looking, so not exactly secret.

I'd bet #3 is far and away the most common overall, but I supposed your software niche would determine what you see. I work in no-code automation so most of what I see is...you guessed it...no-code automation ("No-code is dead!" they all declare).

I feel that one, projects that would have needed a small team, I can approach myself, as long as I actually truly understand what I am trying to build, which is much harder than most people assume.

I think the reason is twofold: 1) people are building custom solutions for their own workflows that don’t have a big market 2) even with AI, maintaining performant, reliable software is boring and hard and a lot of people with an interest in 1 don’t know or care how to get to 2

indeed, i'm building a project where I had it "working" with agents in the first week and the subsequent several weeks have been making it not be immediately and trivially hackable so I can actually put it online

Yeah and third parties have a lower tolerance for reading error messages than I do, so putting out something even when I find it useful makes those people *my* problem

Matches what I'm seeing. The common thread with the solo builder wave is they're using AI as a force multiplier for taste, not offloading judgment to it. That's the opposite of the AI building AI harness pattern that never ships anything real.