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The responses to this are wild. I have worked with and built smaller systems like this and it is an incredible speed up.

So much reflexive hate against a genuinely transformative tech. Yes AI has annoying people and grifters, but it is genuinely incredible at some things and finding out how to use it effectively within a company is the most fun I’ve had in my career.


The issue of it burning through tokens grepping around should be fixed with language server integration, but that’s broken in Claude Code and the MCP code nav tools seem to use more tokens than just a home-built code map in markdown files.


They got so many things right in the beginning but now seem to lose touch with their core fan base, the developers. It's the typical corporate grind, a million competing interests arise where it's not anymore about the user but about politics and whoops, that's when you know you're not anymore a startup.


Haven’t done robotics, but this approach is also much more feasible now with AI, which I appreciate.


That is not a good idea. To deal with LLMs one need to have knowledge about the topic of the query, case contrary one will not be able to detect the errors of their output-prompts. The test is easy, if after one or three queries one do not detect the errors, one is done, the person is reading the output-prompts in passive mode.

The self-learn path require also to cultivate a intuition that comes from searching and reading technical doc that a LLM will not give you, among other things.

Anyway, I observe how the warning of the other user about this got downvoted and critiqued. I expect the same, and leave this thread with peace of mind subscribing to such warning, as a message to the OP.


OP wants to brush up on their skills, not have AI do it for them.


>OP wants to brush up on their skills, not have AI do it for them.

the two things aren't mutually exclusive.

if an AI tells you "solder A to B" you're going to learn some technique whether you want to or not. Extrapolated entirely into a robotics project.. there's a lot to gain just through sheer osmosis of instruction.


the barrier to entry for a lot of playing around is getting a working scaffold to be able to run all your testing from

id expect it could pick you out a breadboard, a micro, some actuators and sensors, along with get a code deploy and run harness going for you, so you can focus on doing the robotics, rather than anything else.


Some people learn by doing, or learn by example, and the faster they can get into doing an example, the faster they will learn.

I am one of those people, and I can't count how many textbooks I own, of which I've read the first few chapters, and lost interest because I wasn't doing anything, only reading.

When I can instead start doing something, as GP emphasized, I can learn the applicable concepts as they're applied, which works well for me. AI helps me do that, because it is like a textbook that follows along with me, rather than asking me to follow it. Also I ask a lot of questions.


Thats where appreticeships come in handy, you can watch and learn by example.


Very true, and doing it this way lets me learn at midnight for no extra cost while I go from zero to one and keep my day job that lets me pursue such passions.

They're very varied, so not a clear path to a job there, and I'm not sure I would want to make a job out of all of them.


I don't think using ChatGPT as a wikihow is going to blunt their skills. As long as what the LLM says is actually correct.


Building a woodworking extension for SketchUp!

I took a course in using it for woodworking, and just kept thinking “this should all be a single extension”, so I’ve been building that.


1. I was prepared my to roll my eyes, but I actually think the framing is correct. AI hasn't replaced legacy vendors yet, but companies are now in a position to at least assess whether "Cheap External Tool + AI" beats "Expensive Tool", which starts to compress margins for existing tooling.

2. A suspicious number of "It's not X, it's Y" in this piece.


I keep thinking about two very different cases wrt existing platforms:

1. My cousin who works for an enterprise real estate SaaS company. He said their main product has iirc 10-20,000 database tables.

2. Evernote users had famously little overlap in which features they used. Everyone use a slightly different subset of Evernote tools.

I wonder if you could create a 2x2 grid of these two scenarios to determine a SaaS tool's likelihood of being replaced with AI.

- Complex Data Model + High feature adoption: Low risk of AI

- Complex Data Model + Low feature adoption: Medium risk short term. High long term.

- Simple data model + High feature adoption: High long term risk risk, but limited ability to grow accouts

- Simple data + low feature adoption: Very high risk


Jonathan Haidt recently made the point on Ezra Klein's podcast that while adults can take a break from phones and reset their attention/hormones in a couple of weeks, we don't know what impact similar addiction has on a developing mind. It's possible the addiction sets in much deeper.

I'm sympathetic to folks who grew up shaped by this. Not for nothing, but The Conversation also has a compelling start/end, but has a long, arguably slow, boring middle. So it's like being forced into withdrawal on hard mode.


I think that's true. Alcohol addiction modifies the brain and it can take over a year to recover dopamine sensitivity, focus, mood, cognitive ability. It's called PAWS (post acute withdrawal syndrome). Given TikTok etc. has a similar profile of long usage over a long period, I'd also expect it to take a long time to fully recover from.


Not snack bars, but tiny bars were absolutely one of my favorite things in Japan. The streets of 3-5 seat bars felt incredibly special and distinct from anything I've seen in the US, regardless of the presumably high % of their business that came from tourists.


> the presumably high % of their business that came from tourists

That's only in the areas frequented by tourists. The vast majority of such tiny bars cater mainly to locals.

Lately I've been taking pictures of bar signs in Japanese cities:

https://gally.net/barsigns/index.html

The sheer number of bars in such dense concentrations continues to impress me.


I think it's pretty unlikely that they visit bars who don't want the tourists.

I often go on food tours in new cities (e.g. Secret Food Tours) and the restaurants they visit seem to like the consistent revenue stream during off-hours.


I actually love the idea of totally new naming schemes for experimental software.

Certain name types are so normalized (agent, worker, etc) that while they serve their role well, they likely limit our imagination when thinking about software, and it's a worthwhile effort to explore alternatives.


This reminds me of Moldbug's Urbit. I can't be bothered to look it up, but his comment was along the lines of "existing words bring assumptions, so safest to make new ones". To which, my comment would be: perflufflington flibnik qupnux.


Not just this, but I’ve been thinking that naming things with aggressively strong connotations might help Claude get out of ‘nice/helpful’ mode. “You are the Deacon, grrrrr”. So there might be actually be a bit of effectiveness added by naming an agent appropriately. I offer no opinion on the word polecats.


Maybe helps the LLM, but at the cost of confusing humans. It would've been better left as an internal implementation detail. I've got better things to keep in my head that remembering wtf deacon is, etc.


yes, totally. AI-luddites see this as whimsy, but it's actually wizard-level power of abstractions and context ascension. if u know u know


I do too, but you can take things too far, which I'd argue has happened the moment "figuring out what the names mean" becomes enough of an intellectual challenge to provide a dopamine hit; at that point, you've (intentionally or otherwise) germinated a cult. It's human nature: people will support the design not on its merits but rather as loss aversion for the work they put into decoding it.


Yes at some point innovative software and naming are at cross purposes, and if your naming gets too extreme ultimately that will get all of the attention.


Anthropomorphizing chunks of your system is kinda weird given interactive chat as the UI to the LLM.

Akka and others have standardized names for all this stuff (and seem to fully know that a code ‘actor’ is code). These wheels don’t need reinventing (much less as ‘the Marvin’s’, a lovable set of bi-racial quadruplets who always get you where you’re going <rocket emoji>).

In fact, I dare say a lot of LLM fascination for orchestration is people unfamiliar with actor models and the level of elegance a properly expressive language lets them have.


That last line is exactly what I was thinking. Find an expressive language and then progressively formalize your workflows in DSLs that enforce correctness by design, not through layers and layers of natural language “skills” and deadweight agentic watchdogs.


Excellent movie. Worth noting that it was written by Tony Gilroy, who created Andor and cowrote The Bourne Identity, so if you enjoyed those you're likely to enjoy this.


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