I do the same, but delegate to codex instead via the /smux skill. It's expensive, but I get one long-running Claude context window and one frequently compacting codex, and this saves me from needing to re-gather context all the time.
Per the OP's technique, I'll use Fable for intensive planning moments, then switch back to opus when things are going well.
1. A compiler for real-time tensor processing (arbitrary DSP, ML). In something like LISP or Haskell, the goal is to compile lambda calculus for fast/reliable execution—as such, you can express a program in a fully general language that can represent any computation and execute it without explicitly modeling the lower levels of the machine. I'm building a compiler that does the same thing for the subset of programs that are guaranteed to execute on-budget. The effect: you write code that looks like DSP/ML math and it compiles/runs optimally with execution guaranteed by construction.
2. My take on an agent framework ... append only log + content hypergraph in Elixir, tools that regularly pull data from other services into Postgres—built as a kind of 'exoskeleton' around claude/codex so it's not competing with fast-moving tools.
Ah, interested to dive in—and have a project it could integrate with.
I built a similar thing recently, for agents, aimed at enabling prolog queries over handles in markdown corpora (and code): https://github.com/flowerornament/anneal. A true slopwerk in comparison to this, however.
I suspect most people don't even know there's a there there.
For instance, while I now know that file systems have permissions, before I became a programmer, I spent maybe ten years thinking of permissions as a special, obscure system thing that you should never touch.
For that matter, I suspect many people don't know basic things like that a file system isn't inherently the operating system.
And, where would you go to learn this information? Your Mac doesn't ship with a manual—how would you know one exists? Furthermore, I would wager that perhaps most people have never learned how anything works requiring a manual and are simply unaware that that's a thing.
All to say, I'm not sure "refusal" is the right term.
I don't completely disagree, but that's not the entire story, and the efforts of those who fought for good outcomes matter profoundly.
For instance, we do in fact have global, effectively ad-free, E2E encrypted messaging. A lot of people put in a lot of work on many fronts to design that, prioritize it, and deliver it at world-scale (mostly) legally.
The fact that the ad model became completely dominant is a real tragedy, but I think the deeper mistake with that idea was that "connecting people" is more complicated than it seems and has had many unforeseen consequences.
As a Western well-to-do person, to the extent I can tune out the slot machine, the dream actually has come true in many ways. I have friends and colleagues all over the world, travel is easier, coordination is easier, and politically my voice matters in ways it never would have in the past.
I was reading mailing lists from the early 2000s the other day and it was wild to remember a time when you literally had no idea what was happening in other parts of the world—when nearly all information was mediated through centralized authorities. People were sharing 'suppressed' reports on grass-roots political action other countries with a sense of self-importance that would be cringe today.
Sadly, I think this is true, and it's starting to seem like my own personal political imperative is to remind people that AI can be insanely personally empowering.
Many people around me are just missing the boat, or don't care, but many are also able to finally accomplish all kinds of things they've been barred from in the past.
LLMs are best seen, I think, as an imagination amplifier. If you're in the mindset of finding ways to improve society and help other people, there is no shortage of opportunity, and increasingly, capability.
Opus 3.x building me a productivity system with Obsidian MCP originally.
Next was discovering "create a mathematical model of the problem and derive the solution as a result" type prompts.
But, the real "oh s**" was a longer process of spec'ing a compiler/runtime for real-time DSP (with a lot of novel ideas) and it actually working.
My sequence was: (1) if helps me understand myself, (2) if helps me put together good ideas, (3) it can generate novel ideas given the right inputs, (4) it can build useful tools on my machine, (5) it can compound good ideas into better and better ideas with repeated passes, (6) it can build significant, ambitious machinery that's way beyond my ordinary capacity.
Current frontier: it can compound large codebases into better and better machinery with repeated passes.
The key thing I track is whether I'm running a process that converges and compounds or whether I'm spinning in place / diverging.
- Durable, 'enterprise grade' software patterns are baked into the runtime and into common, stable libraries that everyone uses
- You can use Ash, which pretty much entirely solves architectural considerations for many types of backends
- The tooling for inspecting and enforcing style (tidewave, credo, dialyzer, Dan's "vibe" ecosystem tools) is far beyond what I see in other ecosystems
- Ecosystem coverage for pretty much everything you need, including numerical software
- Excellent performance escape hatches (NIFs)
And, as has been shown in various benchmarks, agents are quite good at it.
My one problem in practice has been that getting tests right is hard. LLMs need a lot of cajoling to not build flaky tests with all the concurrency, and I find myself spending hours rewriting parts of the test suite once or twice a week.
Do the forms etched into stone by weather over millennia in Moab matter to the wind? Certainly yes, in one sense, but not in the same sense we mean when we say things matter to us, or to animals, or even bacteria.
Not optimizing for that. I derive "10x" more satisfaction, because I'm able to work on more ambitious problems. I'm probably making less money than I would otherwise.
I work on self-directed projects that don't make any money, currently. My "day job" (not software development) does not have this '10x' quality, though I imagine it could were I allocating my efforts that way.
Not publicly yet, but I work on a programming language, compiler, and runtime that achieves magical (to me) things in a niche field. I would never have attempted something at this scale otherwise, so it's a very 0-to-1 experience subjectively.
I think it's just hard to know this for the people working on it. AI radically changed my life. I'm doing at least 10 times more, more ambitious, higher quality work. I've been listening to people around me talking about alignment and the singularity for almost a decade. It's strange to imagine that people live in a world where this isn't and hasn't been happening for a while now. "Over-hyped" is not the word I would use if I take my daily experience as an example, nor when I consider even lower-bound projections.