As far as stats go from the provider dashboards I see:

- 7667 lines of Agent Edits accepted on Cursor

- 105 messages (prompts) on Augment Code

Couldn't say it better myself. I think many people get discouraged when they don't get good results without realizing that for good results you need to learn how to interact with these AI agents, it's a skill that you can improve by using them a lot. Also some AI tools are just better than others for certain use cases, you need to find one that works best with what you're doing.

When it finally clicks for you and you realize how much value you can extract from these tools there's literally no coming back.

The reason for my skepticism is the delta between what they're being sold as and what they actually do. All AI solutions, including agents (especially agents!), are effectively worse-than-worthless without guidance from someone experienced. There's very little that's "autonomous" about them, in fact.

The very guy who coined the term "vibe coding" went on stage effectively saying we're putting the carriage before the horse!

Omitting the important caveat that while they are fantastic tools they need to be restrained a lot is effectively lying.

For all the talk of AI hitting a ceiling the latest tools have improved greatly. I'm literally doing things in hours that'd previously take weeks with little issue. I do of course have to think about the prompts and break it down to a fine grained level and i also have the AI integrated well with the IDE.

The biggest wins are the times you hit a new framework/library. Traditionally you'd go through the 'search for code samples on usage of new library/language/framework -> work those samples into a form that accomplishes your task' cycle. AI is much better for this to the extent it even often surprises me. "Oh the library has a more straightforward way to accomplish X than i thought!".

For those who are still skeptical it's time to try it again.

I'd hope most devs are using AI heavily when coding, the last 6 months seem to have reached a level of competence in raw programming skill somewhere around mid- or senior- level with hilarious variance between brilliance and idiocy.

I think you might be seeing the most vocal programmers are terrified for their future prospects and there isn't much room to reason with them so they're let alone.

AI has become three things for me:

(1) A learning tool. What it is really great at is understanding my questions when I don’t have the proper terminology. Because of this it can give me a starting point for answers. It is also really fantastic for exposing me to unknown unknowns; probably the most important thing it does for me.

(2) A tool to do boring or tedious things that I can do but slow me down. I’ve found it good enough at a variety of things like commenting code, writing a config file (that I usually edit), or other text-based adventures.

(3) Search. Just like (1), because it understands what I’m actually after, it is irrelevant if I know what a thing is actually called. I also let it filter things for me, make recommendations, etc.

I think you can let it think for you, but… why would you? It’s not as smart as you. It’s just faster and knows more things. It’s like an FPU for the CPU of your brain.

One of the best comparisons to me is languages.

The old "lisp [or whatever] lets us do more, faster" idea, but with a fun twist where if you can reduce the code you write but still end up with generated code in a fast, high-performance language, without the extra work you would have to do to go add type annotations or whatnot everywhere for SBCL.

But with a gotcha that you are gonna have to do a lot of double-checking on some of the less-easily/obviously-verified parts of the generated code for certain type of work.

And of course highly-expressive languages have resulted in no small number of messy, unmaintainable codebases being built by people without well-specified advance plans. So we're gonna see a lot of those, still.

BUT to me the real, even bigger win - because I spend less time writing 100% new code than integrating old and new, or trying to improve old code/make it suit new purposes, is supercharged debugging. A debugger is a huge improvement over print statements everywhere for many types of things. A machine that you can copy-paste a block of code into, and say "the output looks like [this] instead of like [that], what's going on" and get a fresh set of eyes to quickly give you some generally-good suggestions is a huge improvement over the status quo for a lot of other things as well. Especially the type of things that are hard to attach a debugger to (sql, "infrastructure as code", build scripts, etc, just to start).

A technique that works well for me is to get the AI to one-shot the basic functionality or gameplay, and then build on top of that with many iterations.

The one-shot should be immediately impressive, if not then ditch it and try again with an amended prompt until you get something good to build on.

Where are you reading “a lot of posts” making this specific claim? I’ve never seen any serious person make such a claim

> a strong and thorough idea of what you want, broken up into hundreds of smaller problems, with specific architectural steers on the really critical pieces.

This is how I’ve been using LLM bots since CGPT preview and it’s been phenomenally useful and 100x my productivity

The gap seems to be between people who never knew how to build, looking for a perfect Oracle that would be like a genie in a lamp, then mad when its actual work

The thing the last few years have beat into me is that most engineers are actually functionally bad engineers who only know 1:1000th of what they should know in order to know how to build a successful project end to end

My assumption was that all of the bad engineers I worked with in person were a accidental sample of some larger group of really good ones (who I’ve also been able to work with over the years) and that it’s just rare to find an actual capable engineer who understands the whole process

Turns out that’s a trivial minority (like every other field) and most people are pretty bad at what they do

As a tech lead who also wears product owner hats sometimes: This is how you should do it with humans also. At least 70% of my job is translating an executive’s “Time travel tower game. No bugs” into that long series of prompts with a strong architectural vision that people can work on as a team with the right levels of abstraction to avoid stepping on each other’s toes.

[0] https://news.ycombinator.com/item?id=44463967#44465304

I came back here specifically to ask about Augment Code, after going to their website and not really understanding what it is

> About what I expected.

But then again, you opened the video already with an expectation to see failure, so of course you found it.

Isolating your analysis of this to a single unflattering interaction is intellectually dishonest; you have a bone to pick.

If you want to follow the history of this project as it was created the best way would be to read the prompts file from top to bottom. For example the EnergySystem.ts file was created right after I was done with enemy pathfinding, spawing and tower shooting and it was created from scratch by the AI using the prompt "I want to implement an Energy subsystem where..."

Code is a medium, painting is a medium, piano is a medium, and prompting is a medium.

This sounds a little bitter.

> What did _you_ do? How were _you_ creative? Where in this project is _your_ passion?

My passion is, and was never in the act of typing code. It was put in creating something that's useful or, in this case - fun. It's the end product that matters to me. I've put a lot of thinking into how exactly each element should work, look and behave. Then I verbalized all this thinking and created prompts that got turned into code, which resulted in a game that's apparently fun for people to play. And that's it.

Thank you for taking time to check my project.

There's a prompts.md (link: https://github.com/maciej-trebacz/tower-of-time-game/blob/ma...) that shows what the author did in this project, most of which is providing creative direction and corrective nudges to the AI.

Most people only care about the end result, and vibe coding got the author there much faster and with less effort.

Your comment reads like a carriage driver bemoaning car drivers because they didn't have to feed, groom, harness, and command a team of horses, yet still arrived successfully at their destination.

"Why should I be impressed that you turned a wheel and pushed a pedal?"