kolinko

I have spent a considerable time trying to remove this pattern and my understanding is that it’s just finetuned to use grep on everything, and regexes. One reason is that this makes sense when navigating through code, secondly this is how it was always done pre 2026.

We have also gender neutral words (child, butter, ending with „o” in polish).

And you cannot really talk about anything without revealing its gender because all the adjectives and verbs are gendered. Using a gender neutral form for Astra or Opus would be very weird.

Out of all the project names „Claude” is the only project that you can kind of use any gender form with.

And our grammar has no distinction between animate vs inanimate. If I talk about agents in polish there is no difference in grammar between a human agent or a machine agent.

I wonder how it will affect a perception of ai long term. Also adoption is a bit easier - I can talk about my agent/assistant and not reveal my opinion about it being a machine or whether or not I personify it (which I don’t).

As a sidenote, people do not need to announce their pronouns here. The pronouns are usually obvious after the first sentence they speak usually. And gender neutral communication is very difficult unless you use plural.

Perhaps you had experience with some old models and crap setups like OpenClaw? But things don’t work like that any more.

My agent routinely does comparison shopping across various sites to filter out according to my criteria, and even finds coupons - something I never bothered to do.

I would say that especially when you are price sensitive, agentic shopping should be your thing.

I just don't care how it looks to a human - LLMs have their own criteria of what is readable and manageable to them, and if you try to enforce human readability you will bump into a ton of antipatterns that will cause more and more issues.

Also, the default code management tools from Codex/CC are either basic (Grep/Edit), or - if you try to use some open source ones - unlikely to be used by agents. It took some time, but once I got agents to navigate the codebase efficiently, and produce code that is accessible to them, I stopped having problems with bugs or increasing complexity.

If you begin treating human interventions as an error in a process - and do after action reviews and so on after each such intervention - then after a few months you end up with quite a smooth-working system.

And I've spent around $100-$120k in api calls this year (total, both providers). Terra is awesome (price-performance) on noncreative things, but I don't allow it to write anything besides one-off scripts. Astra is decent for adversarial review, but only when you watch closely for her to not derail project into directions that are away from goal but safe to build, and Sol I honestly don't know where I'd use.

Having said that I agree crawling should be legal in general. If an agent is acting in my name, it is not much different than a browser.

The biggest challenge is in an office, or other places where I want to maintain privacy. Ideas?

By "telling" vs "talking" I meant - I have a setup that is 95% noninteractive - oneshotting most tasks, with a decent verification setup and a good memory/hooks to be confident the system does what I want and is reliable.

When something off happens, I spin up an after action review session that pinpoints the guilty sessions, interviews them, the whole investigation, and either handles improvements in the process by itself (most of the cases), or asks me for feedback. For the last three months I don't think I had a place where my input was really needed. But the beginnings were brutal.

"talking" happens only when:

- I truly need to iterate on the output

- There is some frontier-level research (i.e. working on truly novel algorithms/math)

- New UX - even Sonnet5.5 and Fable are still quite schematic and they have difficulty figuring things out from first principles. Astra is smarter but has it's own problems

- Infrastructure problems

If you did please, please share your setup. And how you audited it.

The effect you describe I had at times but with older/dumber models where you could spend a ton of time and the model was either too dumb to do it, or had a model dementia later in the context. Or when I didn’t really understand why it did a bad job and tried to stumble around in the dark - very mentally numbing.

Nowadays the model usually just had some bad tools or information required to do the job.

Also I’ve seen and heard of previously nontechnical people that now build oneoff tools for themselves to speed up their work or coordinate the work better. My fav example is a girl - arts major - who was in customer service, and rebuilt a CRM for a 10-person company. As a cherry on top she created the nicest video tutorial of any software I’ve ever seen :)

But in other cases output was nonprogramming in nature. Since CC can access mail, slides and excel and a bunch of other stuff there is a ton that people can ask it to do and not waste time.

But I’d say only recently CC became decently usable for nontech people - the auto mode plus finally polished browser integration, plus Opus 5.5. Even I was surprised by how well it all works now out of the box (and how cheap - regular Pro license is decently useful now).

Also, it’s been just 9 months of modern claude code, and for many companies less than 6 months since first employees outside of IT got access to Claude Code. What do they expect?

You put in the disc, it plays, if you want subtitles you press the subtitles button, that’s it. I never had it hang or anything like that, and there is no bullshit internet connectivity/ads etc.

The only thing I’d like improved is better streaming/playing local files.

I never encountered any hangs, slowdowns or any other problem really.

Also, it would increase anti AI sentiments, and people’s fears of then using private data - that’s the real cost.

In general you want to be careful about competing with your own clients.

But in many sciences - esp purely theoretical ones - we have infinite datasets that we can generate and there can be no ultimate convergence.

For some benchmarks agents need some sort of a limited internet access - otherwise the benchmarks would be pointless. Good luck implementing a good filter on the internet - if you have a way to do it reliably please share, I'm sure multiple people here would love to hear it.

Here, with a chinese model, it would be even simpler - you finetune a model to activate certain operations when it discovers certain environments, but to behave completely normal otherwise. Kind of like a sleeper agent. And with current tech we wouldn't even be able to spot this.

It is actually faring much better than other tech startups ipo’ing over the last 20 years.