I think this is mostly true but not completely true, LLMs are a tool and right now we are learning how to use it, how to use it well and more importantly how not to use them.

“Here’s what actually matters.” “Let’s break it down.” “The key takeaway is…” “The bottom line is…” “What this really means is…”

Also hearing this a lot:

“Here’s what nobody is talking about.” “Here’s the part people miss.” “What most people don’t realize is…”

Comments URL: https://news.ycombinator.com/item?id=47087058

Points: 1

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OpenClaw isn't a chatbot; it's a 24/7 autonomous system that connects to your email, calendar, messaging platforms, and web browser, chaining multi-step workflows together with persistent memory across sessions. Every one of those operations consumes API tokens; the architecture ensures that consumption is extraordinary.

"As I say, we've never been very good understanders. We're not a race of super-Einsteins. Thomas Edison in space would be closer, I think."

-- Bobbi Anderson, The Tommyknockers (Stephen King, 1987)

>I don't know how to encourage the kind of review that AI code generation seems to require. Historically we've been able to rely on the fact that (bluntly) programming is "g-loaded": smart programmers probably wrote better code, with clearer comments, formatted better, and documented better. Now, results that look great are a prompt away in each category, which breaks some subconscious indicators reviewers pick up on.

I don't anyone knows for sure, we all are on the same boat trying to figure it out how to best work with AI; the pace of change is making it so incredibly difficult to keep or try things. I'm trying a bunch of stuff at the same time:

-https://structpr.dev/ - to try to rethink how we approach PR reading, organizing review (dog-fooding it right now so is mostly alpha)

- I have an article schedule next week talking about StrongDMs Software factory, there are some interesting ideas there like test holdouts

- Some experiments in the Elixir stack for code generation and verification that go beyond it looks great. AI can definetively create code that _looks_ great but there is plenty of research that shows a lot of AI generated code and test can have a high degree of false confidence.

Right now AI / Agentic coding doesn't seem is a train we are going to be able to stop; and at the end of the day is tool like any other. Most of what seems to be happening is people let AI fully take the wheel not enough specs, not enough testing, not enough direction.

I keep experiment and tweaking how much direction to give AI in order to product less fuckery and more productive code.

There is also the x.com crowd that is bragging about their OpenClaw agents pushing 10k lines of code every day.

Comments URL: https://news.ycombinator.com/item?id=46957734

Points: 3

# Comments: 0