mccoyb

In 2026: frontend web developer reinvents tmux.

Guys, please do us the service of pre-filtering your crack token dreams by investigating the tool stack which is already available in the terminal ... or at least give us the courtesy of explaining why your vibecoded Greenspun's 10th something is a significant leg up on what already exists, and perhaps has existed for many years, (and is therefore, in the training set, and is therefore, probably going to work perfectly out of the box).

It is not a class of labor ... it is all digital labor. Do you or do you not understand this?

It is digital knowledge itself, and then all communication labor, and then all physical labor with robotics.

Is this clear to you?

Try this one: https://code.claude.com/docs/en/overview#run-agent-teams-and...

Or perhaps: https://code.claude.com/docs/en/overview#pipe-script-and-aut...

You know what they say about looking and quacking.

I'm not sure what to say. You're either listening to the actions of these companies, or you're not in a place where you feel the need to be concerned be their actions.

I'm in a place where I'm concerned by their actions, and the impact that their claims and behavior have on the working environment around me.

The disrespect Anthropic has for their user base is constant and palpable.

Ghostty is a great piece of software, with a stellar maintainer who has a very pragmatic and measured take on using AI to develop software.

To your point, why even advertise the number? If that particular number is completely irrelevant in practical usage, why mention it? It seems like the point is to impress, hence my response.

Aside but 12 MB is ... large ... for such a thing. For reference, an entire HTTP (including crypto, TLS) stack with LLM API calls in Zig would net you a binary ~400 KB on ReleaseSmall (statically linked).

You can implement an entire language, compiler, and a VM in another 500 KB (or less!)

I don't think 12 MB is an impressive badge here?

If you are not, let me introduce you to the term: a probability distribution.

Just because it has profound properties ... doesn't make it different.

> has all the trappings of the stochastic parrot-style HN-discourse that has been consistently wrong for almost a decade now

Perhaps respond to my actual comment compared to whatever meta-level grouping you wish to interpret it as part of?

> It contains a number of premises that we have no business being confident in. We are potentially witnessing the obviation of human cognitive labor.

What premises? Be clear.

Less worried about memory, more worried about compute speed? Are they obviously related and is it straightforward to see?

As far as I understand RL scaling (we've already maxxed out RLVR), these machines only get better as long as they have expert reasoner traces available.

Having an expert work with an LLM and successfully solve a problem is high signal data, it may be the only path forward?

My prior is that these companies will take this data without asking you as much as they can.

Before, we didn't have a fast (we had to rely on human cognition) way to try problems - even if the techniques and workflows were known by someone. Now, we've baked these patterns into probability distributions - anyone can access them with the correct "summoning spell". Experts will naturally use these systems more productively, because they know how to coerce models into the correct conditional distributions which light up the right techniques.

One question this raises to me is how these models are going to keep up with the expanding boundary of science. If RL is required to get expert behavior into the models, what happens when experts start pushing the boundary faster? In 2030, how is Anthropic going to keep Claude "up-to-date" without either (a) continual learning with a fixed model (expanding context windows? seems hard) or (b) continual training (expensive)?

Crazy times.

Pass for me.

Where did you get this perspective from?

> I thought pi and its tools were supposed to be minimal and extensible. So why is a subagent extension bundling six agents I never asked for that I can’t disable or remove?

Why do you think a random subagents extension is under the same philosophy as pi?

Your blog post says little about pi proper, it's essentially concerned with issues you had with the ecosystem of extensions, often made by random people who either do or do not get the philosophy? Why would that be up to pi to enforce?

This is quite nice — I do think there’s a version of pi’s design choices which could live in a static harness, but fully covering the same capabilities as pi without a dynamic language would be difficult. (You could imagine specifying a programmable UI, etc — various ways to extend the behavior of the system, and you’d like end up with an interpreter in the harness)

At least, you’d like to have a way to hot reload code (Elixir / Erlang could be interesting)

This is my intuition, at least.

if agents continue to get better with RL, what is future proof about this environment or UI?

I think we all know that managing 5-10 agents ... is not pretty. Are we really landing good PRs with 100% cognitive focus from 5-10 agents? Chances are, I'm making mistakes (and I assume other humans are too)? Why not 1 agent managing 5-10 agents for you? And so on?

Most of the development loop is in bash ... so as long as agents get better at using bash (amongst other things), what happens to this in 6 months?

I don't think this is operating at a higher-level of abstraction if agents themselves can coordinate agents across worktrees, etc.

It's a great idea: really neat take on programmability, and can be reloaded while the agent is running without tweaking the harness, etc -- lots of benefits.

`pi` has a great skills implementation too.

I think skills might really shine if you take a minimal approach to the system prompt (like `pi`) -- a lot of the times, if I want to orchestrate the agent in some complex behavior, I want to start fresh, and having it walk through a bunch of skills ... possibly the smaller the system prompt, the more likely the agent is to follow the skills without issue.

It turns out that "most of the bell and whistles" could amount to instructing models how to use tools like tmux

There is barely any magic in the harness, the magic is in the model.

Try it: write your own harness with (bash, read, write, edit) ... it's trivial to get a 99% version of (pick your favorite harness) -- minus the bells and whistles.

The "magic of the harness" comes from the fun auxiliary orchestration stuff - hard engineering for sure! - but seriously, the model is the key item.