nerptastic

If you don't mind me asking, what are "good agentic engineering practices"? To my knowledge, we are still exploring many techniques of using agents within a codebase, and have not widely agreed on "best practice".

Do you mean "good code" and "good documentation"?

Careful, you might just get turned into an H100 along with everything else in the observable universe

Well - I think the writing was on the wall when they announced they were going to be for-profit. Slippery slope and all that, but I’m sure some of this is because they’ve been giving out free tokens for years.

What are the first and fourth?

“The limits now are so bad that a business that relies on it would need bigger plans.”

Isn’t this the goal to some extent? They’ll probably have the standard “light” usage plan for weekend warriors or normal folk looking to play around. Companies that mandate usage and provide the subscription for hundreds of employees will have to cough it up, and will have no problem doing so if they want to compete with the others (or so the hype would allude to).

Is this not the case for OTC drugs? Specifically, the two mentioned in the article. I rarely take either of them, but if my doctor tells me to take 1 ibuprofen every 6 hours or so, if I halve that am I actually doing more damage?

I have a degree in design - it's one of those frustrating fields where laypeople really do believe they are experts. Mostly because... they can "see" it. It's easy to propose a change to a design. "Just move it to the right. Or left. Or make it green".

The end product is SUPPOSED to be simple to digest and understand, but the process behind that artifact is enigmatic. It may have taken months to determine the proper layout structure for a government website, but a certain end user can still say "Well... I would rather have the navbar on the right side."

Some of it is probably vocabulary as well. Software has jargon - design has jargon, but laypeople know how to say "bigger, smaller, right, left, red, blue". Frustrating, and part of why I left the field.

I agree — right now it's "all eyes on AI". They are moving fast, I don't think there's some evil plan behind the scenes. They're trying to build software super-weapons, and they're trying all sorts of different things because they can iterate quickly.

Of course the articles are going to get to the top. It's all anyone is thinking about, and has been for the last few years. I keep wondering if we're going to reach some sort of inflection point where the hype starts to die down, but then another "tool" is released and everyone is convinced that this is the one that will take the jobs. It's a bit tiring, but this is the brave new world.

Question for you, did these tools replace software / design consulting as something you relied on in the past?

This is a success story I've been hearing more recently. Restaurants, contractors, plumbing, 1 person startups... I'm wondering if this is because the barrier to entry is now lower - or if these tools are actually moving work away from small software teams or individual devs.

IMO this is the crux of the "AI Eating SWE" scenario (along with other knowledge work...) I'm sure it's a little bit of both. If this was something you were going to pay a designer and a developer for, it changes the outlook.

From my perspective, it feels more likely that with cheaper software we'll see a rush of people building their own, but once it gets sufficiently complex it then needs to be maintained, or improved, and it becomes more work than the initial weekend POC.

Back when I was a lowly web dev intern - I was able to finish most of my work rather quickly. Obviously, instead of going above and beyond - I found a way to browse Reddit in the terminal.

My manager was non-technical, and so anytime he walked past my desk it appeared that I was hackin’ away. I had (and still do) have my terminal set up to be black background with bright cyan text.

I don’t know much at all about materials - but wouldn’t this be a little “fuzzy”? If they’re using heat to expand/contract whatever material, I imagine there’s a degree of variance with the starting state / ending state - depending on the environment the “soft robot” is in.

A static amount of electricity may only be able to move the wings so much in a cold environment, right?

This is what I’m noticing. At my workplace, we have 3 or 4 non-devs “writing” code. One was trying to integrate their application with the UPS API.

They got the application right, and began stumbling with the integration - created a developer account, got the API key, but in place of the applications URL, the had input “localhost:5345” and couldn’t get that to work, so they gave up. They never asked the tech team what was wrong, never figured out that they needed to host the application. Some of the fundamental computer literacy is the missing piece here.

I think (maybe hopeful) people will either level up to the point where they understand that stuff, or they will just give up. Also possible that the tools get good enough to explain that stuff, so they don’t have to. But tech is wide and deep and not having an understanding of the basic systems is… IMO making it a non-starter for certain things.

Agreed. I honestly chose Jellyfin over plex because I preferred the branding, not sure what I’m missing. I really enjoy Jellyfin, and thy seemingly have support for most devices in some way.

My GF has it set up on her iPad, phone, computer. App is on our TV and has no issues. We have Netflix at home. She’s non technical and hasn’t had any trouble once I gave her a login.

The only hiccup was when she tried to watch during one of her lectures. I had to explain that Jellyfin is only at home ;) (for now)

Anthropic today, who next week? If locally run models ever get to the point where they can reliably solve... 85% of what the frontier cloud models can do, I think many would be willing to accept slightly less problem solving ability and just run the thing locally.

All hypothetical, but if compute + AI research continues at pace, in 5 years we should see extremely good local models.

I run Jellyfin on an UnRaid server, it was relatively simple with the containers just being “plug and play”. Think it took me about 2 hours. I did have some trouble when we moved into a new house, as I had to reconfigure all the local network stuff.

I have ended up in the past being in a state of “don’t touch anything, it hasn’t broken in 6 months”. Then an update releases and I have to learn everything again. Beats paying 120 a month for whatever streaming services we would need.

Man I really thought this was satire. It’s phenomenal that you can gain 10x benefits at all layers of the stack, you must have a very small development team or work alone.

I just don’t see how I could export 10x the work and have it properly validated by peers at this point in time. I may be able to generate code 10-20x faster, but there are nuances that only a human can reason about in my particular sector.

I haven’t really been following this, but my understanding is that they’re cancelling this program - I haven’t dug into the “why” too much, seems like something about the Disney deal, “focusing on other initiatives”… My thought was that it’s because they’re not making money on it. Why else would they shut down a revenue stream? If it’s decent they don’t even need to improve it, it would be mostly passive income.

I’ll bite - I’ve been a dev at a new company for about a year and a half. I had mostly done front end work before this, so my SQL knowledge was almost nonexistent.

I’m now working in the backend, and SQL is a major requirement. Writing what I would call “normal” queries. I’ve been reaching for AI to handle this, pretty much the whole time - because it’s faster than I am.

I am picking up tidbits along the way. So I am learning, but there’s a huge caveat. I notice I’m learning extremely slowly. I can now write a “simple” complexity query by hand with no assistance, and grabbing small chunks of data is getting easier for me.

I am “reading, debugging, and maintaining” the queries, but LLMS bring the effort on that task down to pretty much 0.

I guarantee if I spent even 1 week just taking an actual SQL class and just… doing the learning, I would be MUCH further along, and wouldn’t need the AI at all. It’s now my “query tool”. Yeah, it’s faster than I am, but I’m reliant on it at this point. I will SLOWLY improve, but I’ll still continue to just use AI for it.

All that to say, I don’t know where the future goes - our company doesn’t have time to slow down for me to learn SQL, and the tool does a fine job - it’s been 1.5 years and the world hasn’t ended, I can READ queries rather quickly - but writing them is outsourced to the model.

In the past, if a query was written on stack overflow, I would have to modify it (sometimes significantly) to achieve my goal, so maybe the learning was “baked in” to the translation process.

Now, the LLM gives me exactly what I need, no extra “reinforcement” work done on my end.

I do think these tools can be used for learning, but that effort needs to be dedicated. In many cases I’m sure other juniors are in a similar position. I have a higher output, but I’m not quickly increasing my understanding. There’s no incentive for me to slow down, and my manager would scoff at the idea, really. It’s a tough spot to be in.

Maybe I’m missing the point but we have some of these implemented without the tool - the only one that needs an API key is the log scraping. It’s been surprisingly cheap and if we want to swap models we can.

Not arguing, but I just prompted Opus with a made up word and it responded with this:

“There are 4 Rs in the word “burberrorrly.” Here they are highlighted: burberrorrly (positions 3, 6, 7, 9)”

Obviously not a real word, but perhaps the fundamental concept remains

I suppose at that point I’m wondering if it would have just been faster for… you, (I’m assuming) the developer to make that change and deploy it? Is the AI really faster on small changes like that, if you understand the platform/code/CI/CD enough???

Maybe for a non-dev it would be nice to submit a ticket and have it auto-fixed by an agent. But in the devs case, it feels like it would be faster to just do it manually.

Man. Runs like butter on an iPhone 15 (Non-Pro). Impressive!

How many pages of architecture / constraints did you write? I guess I’m curious what type of text input renders 200K lines of code output. It must be a similar level of tokens in just docs / prompting. Have you verified all of that? Was that AI generated?

Would be very interested to see whether it’s not just… regular LLM snowballing a paragraph into 12 pages of “technical design documents” and 10K lines of code. Not sure what kind of niche you’re in or what the business logic is, but it sounds to me like you’ve built a machine that… generates code you don’t need to look at??

Interesting read. Thought I’m not sure I loved the way the graphs were laid out. I didn’t do a deep dive on them but some felt like they were displaying the data in a way that wasn’t rooted in the facts.

Either way. A whole lot of words and sentiments that could have been inferred. People use the new tools, we feel they make us more productive (but by how much), and it’s scary because C suites are bearing down in FOMO.

I would have LOVED if they got some form of stats in here as to how much performance people are getting out of these. I’ve heard 100X, actually. I’ve heard 5X frequently. Some people think it slows us down. Nobody really knows, and I guess it depends on how you’re using it. I personally have said to my CEO that I feel 30-40% faster, though I hate to have numbers associated with it… these tools have been around for years now. 5X faster than… what? It’s just expected to learn the tools and use them where they help. I would love a consensus on actual, regular folk and how much more productive it makes them. I’m doubtful it’s north of 10X. 4-5X seems optimistic? Not sure.

At my company, it’s being essentially shoved down our throats - “be 5X faster, tomorrow, this guy on the AI podcast said this is possible!!” And if you aren’t using the tools to build some useless internal application, you’re looked at as a non-adopter.

It’ll be interesting to see where things go in the next year.

I still see people refer to “FAANG” regularly. Though, there have been times I’ve read “MAANG”… doesn’t quite feel the same.

I’m a newer full stack engineer, previously did mostly web dev. It’s been useful in the areas that I’m not super interested in. We’re working on a 700KLOC legacy monolithic CRUD app with 0 documentation, it’s essentially the Wild West. We’ve found it very difficult to apply AI in a meaningful way (not just code output, reviews, documentation writing, automation). For a small team with lots to do on what is essentially a “keep the lights on” we’re in an interesting place, as it feels the infrastructure / codebase isn’t set up to handle newer tools.

I use the code generation heavily in my day to day, though verification is a priority for me, as is gaining an understanding of the business logic + improving my skills as a developer. There’s a healthy balance between deploying 100% generated code and not using the tools at all.

It’s useful for research tasks, identifying areas I’ll be working in when developing a feature. However, this team has a gigantic backlog and there are TONS of things we are behind on, so it does feel like AI isn’t moving the needle for us, though it is helpful. I’d like to apply it in different areas, but my senior engineer is very anti-AI, so he doesn’t find the tools useful and is actively against using them. Like I said, there’s surely a balance…

I see us using / relying on them more in the future, due to pressure from above, along with the general usefulness of them.

You have a 200K LOC repository and you haven’t written 99.5% of it?

Speculating here, but I don't believe that the government would have the time or organization to do this. Widespread political unrest caused by job losses would be the first step. Almost as soon as there is some type of AI that can replace mass amounts of workers, people will be out on the streets - most people don't have 1-2 months of living expenses saved up. At that point, the government would realize that SHTF - but it's too late, people would be protesting / rioting in droves - doesn't matter how many drones you can produce, or whether or not you can psychologically manipulate people when all they want is... food.

I could be entirely wrong, but it feels like if AI were to get THAT good, the government would be affected just as much as the working class. We'd more likely see total societal collapse rather than the government maintaining power and manipulating / suppressing the people.

I used to handle email development for an accounting firm. HTML in emails is truly dark magic. Working with marketers was soul-sucking, and even further - performing a duty that people actively distrust / hate was an eye-opening realization. I am so glad to be away from that side of things. Email was never meant to house full-blown advertisements…

However, it’s worth noting the ingenuity surrounding the data. Solid article, and a lot of light bulbs went off over the years to get this tech to where it is today. Even though the tech is a black pit of despair.

I can appreciate comparing these immovable political stances to a "religion".

One thing I've noticed, as people get more entrenched in their viewpoint, is that they stop accepting the possibility that they're wrong, and this flawed thinking starts to extend to the wildest corners of their position.

"Well, if I'm right about the person, the person is right about everything too. And anyone who disagrees with me is therefore wrong about EVERYTHING."

It's a very shallow viewpoint, and some people just refuse to accept that they're wrong sometimes.