No, learning to code is still worthwhile because the AI cannot do useful abstraction well at all. If you don't know how to code, then you'll fail to build useful tools and useful reusable components that can (a) further accelerate your development speed, and (b) reduce token spend.
As others have commented, this is an obvious application of event sourcing. It's irritating to see the claim of "deterministic replay" in the abstract along with the caveat "we can't actually do deterministic replay, so we store all of the model's responses and reproject off of that". Sure, ok, whatever. You're doing session recording and calling it replay.
I think this is why reasoning chains and reasoning chain verifiers are so important. We need to be able to see an argumentation, not just an answer. The paper below goes into this in more detail.
HeavySkill: Heavy Thinking as the Inner Skill in Agentic Harness
It helps me to think about it like a different type of function call. We've got normal functions, async functions, there's a Go project that turns HTML templates into "templ" functions. JSX functions. LLMs are just a new `infer` function type.
A few years ago if I suggested that you should write a program to help you with time tracking, I imagine that might get a few responses with pointers to some existing open source projects. In a few years, someone might point to support for infer functions in nightly rust.
In other words, I think that we're dealing with really poor packaging right now and it's stressful, and that in the future this will all be normalized and integrated into our existing workflows.
Hey Joe, I think the solution to your problem is in your post. You said that when you were tracking your time it killed your idea, and that when you stopped tracking your time you became unfocused.
Try letting AI classify your idea into a time-tracking bucket for you, and to generate a beginning of day report describing how you spent your time yesterday.
If you write down your idea, then it'll be harder to forget it. You can let the AI figure out where to put it and fix it the next day if it's wrong.
If you look at where you spent your time yesterday each morning, then hopefully it'll help you figure out a better place to spend your time today.
You can easily set this up with any harness. Just copy and paste my comment and tell the AI to make some skills.
It's clear that you understand that releasing a schema with this much documentation makes the AI-assisted reverse engineering loop trivial. I'm interested in understanding why I should trust/use/pay for your hosted runtime versus rolling my own to run on cheap VPS?
The article supposes that there exists people that fear their data being misused but don't fear their taxes being misused on welfare for a random population of benefit seekers.
The article would have been better without the self-own "problematic baggage" language.
Which is mightily funny because in the opening paragraph the article equates "anti-free movement" with "problematic baggage". It's a problem if people can't move freely in and out of Europe, but not data -- that's our red line!
"ethical" is not a word that carries the connotation of a universally agreed upon set of behaviors. Different peoples, groups, and cultures vary in what they consider acceptable behavior.
I wonder how many gallons of polluted wastewater are discharged per day by overseas refineries. Does anyone know where Tesla stacks up in the global list of lithium refiners?
_underscore_ for italics conflicts with most identifiers in most languages.
Markdown was created in an era before the web had easily used components for structural syntax highlighting (tree-sitter) and where reliance on regex-based approaches was more common.
I think we'll be able to quantify sentiment from the data, and I look forward to doing so. There's a few other datasets that I want to look at such as whether there is evidence of participation suppression via rate limiting on a per-profile basis.
This is great. I've soured on this site over the past few years due to the heavy partisanship that wasn't as present in the early days (eternal September), but there are still quite a few people whose opinions remain thought-provoking and insightful. I'm going to use this corpus to make a local self-hosted version of HN with the ability to a) show inline article summaries and b) follow those folks.
You’re not missing anything. I’ve worked with many developers that are clueless about error handling; who treat it as a mostly optional side quest. It’s not surprising that folks sees the explicit error handling in Go as a grotesque interruption of the happy path.