You’re on the wrong message board then haha

Yeah, for me, that's what parsing huge volumes of LLM-produced text like "direct model calls as replaceable semantic workers" does to my brain. Maybe others don't really have this issue, but after any long output, I prompt the agent "Go back and decompress any LLM-speak in light of the higher level task goals. Eliminate deictic language."

The revised output documents are solely for my personal usage to expedite understanding. The LLMs can slowly converge on their own language for all I care; I retain raw agent output for future agent usage (to avoid the "lossy" problem the author mentions), but that doesn't eliminate the need for some intermediate translation I can use to actually help get my work done instead of spending hours attempting to understand what a "load-bearing pinned gate" is.

Comments URL: https://news.ycombinator.com/item?id=49137399

Points: 6

# Comments: 1

So my two choices are basically “YOLO, LGTM” and hope I can revert if it breaks something, or to just write all the code by hand from the start. With the increased pressure for output, I’ve noticed both myself and coworkers tending more toward “commit and hope it works” over time. It’s sort of perverse incentives in a way...

I think the solution is toward more formalization of the behavior we expect of various systems. E.g., produce a Lean proof that a program never behaves in a certain way, and if you can’t, iterate on the program until it satisfies such a proof. I’ve only tinkered around with this a little bit, but it seems promising on toy problems. Scaling up to tech-company level infra is going to take quite some time however I think.

I've been using a SQLite DB to organize actionability so I don't get stuck in the way that GitHub issue tries to work around. Any questions about which route to take that arise during agentic work are logged to a queue along with a set of plausible candidate routes, a probability assigned to each candidate of whether I will choose that option (including "other/none"), a "resource cost" assessment of the route (e.g., token spend, time), a "stability cost" (e.g., high potential to disrupt things or mainly self-contained), and a set of tasks that describe any downstream work that is dependent on the route chosen.

What Claude does next then depends on the results of a tiny optimization program that tries to maximize the expectation value of agent productivity per unit resource (tokens, time, etc.) conditional on how long it will take me to answer the question (e.g., if Claude has a question for me at 1 AM, there probably won't be a response for another 6-7 hours).

"Agent productivity" is of course a bit nebulous, consisting of a somewhat ad-hoc amalgamation of factors, but in general Claude's actionability loosely corresponds to cases like:

- 2-3 possible routes, each with roughly equal probability of being the one I select, low resource costs, minimal risk of instability, few downstream dependencies: implement each route in parallel

- 2-3 possible routes, one with a much higher probability of being chosen, minimal risk of instability, many downstream dependencies: implement just the top route

- Hundreds of possible routes: block until user response

- 1 possible route, high risk of instability, many downstream dependencies: block until user response

Generally speaking, there should be an active queue at all times and agents should be working on anything that's not blocked in the queue with maximal parallelization.

Funny how people are independently converging on similar patterns of "what works" here. Still feels like we're in the wild west with all these ad-hoc patterns of agent orchestration that people are coming up with.

On the other hand, if you send someone a very personal and heartfelt message and receive a reply like "Yeah, it was so nice spending time with [niece] today!", well, that's a bit different...

Set theoretic questions like AC or CH are much more difficult for me to intuitively grok in the same way, because they don’t seem to “obviously” be either true or false. You can take either and still end up with a (presumably) consistent theory.

> I know for sure what I am perceiving

This reflects my view. And I’ve always found it mildly amusing that beings I cannot prove to myself are perceiving attempt to convince me that I’m not perceiving, when that’s exactly what I’m maximally sure of. Imagine arguing with an LLM designed to convince you that you’re not real. It would be weird, wouldn’t it?

Comments URL: https://news.ycombinator.com/item?id=48123801

Points: 88

# Comments: 18

I suspect that sustained creativity may be a result of continuous exposure to new experiences and concepts (which younger people are naturally situated to encounter quite often), so I try to consistently add novelty to my life as I get older, specifically targeting things way outside my comfort zone or previous interests.

For example, I’ve always been sort of uneasy with flying, so I figured I would sign up for general aviation classes and learn to fly myself, which is something I never would have had the slightest inclination toward when I was younger. I ultimately didn’t go through with it, as while signing up, my wife strongly insisted that I find a different form of “novelty” to pursue, but I think it decently illustrates what I was attempting to accomplish.

Some more mundane examples include listening to music that I don’t enjoy, completely mixing up how I dress after decades of wearing the same thing, reading books opposite my interests, taking classes in fields different than what my degree was in, and trying to constantly meet people who are very different from myself.

I guess we’ll see if this has any effect or not.

Comments URL: https://news.ycombinator.com/item?id=48050284

Points: 2

# Comments: 0