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Agentic Coding Recommendations

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141–150 of 210 posts

Re: Agentic Coding Recommendations

#141
post #16

So using agents forces (or at least nudges) you to use go and tailwind, because they are simple enough (and abundant in the training data) for the AI to use correctly. Does this mean that eventually in a world where we all use this stuff, no new language/framework/library will ever be able to emerge? Competing with the existing alternatives will be too hard. You won't even be able to ask real humans for help on platf…

A traditional digital stack's lifecycle is: 1. The previous gen has become bloated and complex because it widened it's scope to cover every possible miche scenario and got infiltrated by 'expert' language and framework specialists that went on an atrotecture binge. 2. As a result a new stack is born, much simpler, back to basics, than the poorly aged encumbant. It doesn't cover every niche, but it does a few newly po…

> It doesn't cover every niche, but it does a few newly popular things realy easy and well, and rises on the coattails of this new thing as the default envoronment for it

How will it ever rise on the coattails of anything if it isn't in the AI training data so no one is ever incentivized to use it to begin with?

Re: Agentic Coding Recommendations

#142

Earlier quoted context omitted.

> Does this mean that eventually in a world where we all use this stuff, no new language/framework/library will ever be able to emerge? That's a very good question. Rephrased: as good training data will diminish exponentially with the Internet being inundated by LLM regurgitations, will "AI savvy" coders prefer old, boring languages and tech because there's more low-radiation training data from the pre-LLM era? The m…

> Rephrased: as good training data will diminish exponentially with the Internet being inundated by LLM regurgitations I don't think the premise is accurate in this specific case. First, if anything, training data for newer libs can only increase. Presumably code reaches github in a "at least it compiles" state. So you have lots of people fight the AIs and push code that at least compiles. You can then filter for the…

> First, if anything, training data for newer libs can only increase.

How?

Presumably in the "every coder is using AI assistants" future, it will be an incredible amount of friction to get people to adopt languages that AI assistants don't know anything about

So how does the training data for a new language get made, if no programmers are using the language, because the AI tools that all programmers rely on aren't trained on the language?

The snake eating its own tail

Re: Agentic Coding Recommendations

#143

> Likewise with AI I strongly prefer more code generation over using more dependencies. I wrote about why you should write your own code before, but the more I work with agentic coding, the more I am convinced of this. This is an interesting statement!

Something I like to do is get Gemini Deepresearch to write a single file manual for any uncommon dependency and include that in my docs/ directory. Helps a bunch.

I also ask it to write specialized guides on narrow topics (e.g., testing async SQLAlchemy using pytest-async and pytest-postgresql).

Re: Agentic Coding Recommendations

#144
'Many hallucinations' may become the new 'poorly documented' when it comes to tech stack decisions. I'm asking myself if it could slow down adoption of new tech in future, since it's harder to provide the equivalent learning material of 10 years of Stack Overflow than writing equally good documentation.

Re: Agentic Coding Recommendations

#145
post #56

Earlier quoted context omitted.

Bunch of unit, functional and E2E tests, just like before LLMs :) Haven't tried with Ruby specifically but works well with JavaScript and other dynamic languages so should work fine with Ruby too.

I wonder if people that loves typescript never wrote tests and that is why they are so fascinated with types for dynamic languages. I guess they have never been really productive.

Or even better, what if you could automate writing half or more of your unit test, and ensure they run not just out of band, but on ever build?

And even better rather than have them off in some far away location annotate the code itself so the tests will be updated with the code.

That's pretty impressive and someone would have to be short sighted to feel the false productivity of constantly manually implementing what a computer can automatically do for them.

Not to mention how much better if you work on any actual large scale systems with true cross team dependencies and not trivial code bases that get thrown away every few years where it almost doesn't matter how you write it.

Re: Agentic Coding Recommendations

#146
post #129

Earlier quoted context omitted.

Literally less than an hour ago, I reviewed a bunch of LLM-generated boilerplate. I then told the agent to show me a plan to refactor it. I suggested some tweaks, and then it implemented the plan and then tested that it didn't break anything. It isn't much different than dealing with an extremely precocious junior engineer. Given how easy it is to refactor now, it certainly makes economic sense to delay it.

But I'm guessing you're doing those refactors because you know they're ultimately worth it, because you have experience programming since before LLMs? Like I know boilerplate and messy code sucks because I've had to work with it, without LLMs, and I know how much it sucks. I think you do too, but I think we know that, because we had to fight with it in the past.

Right now devs around the world are pushing ungodly amounts of reinforcement learning data into the big AI labs. There is no reason to believe these models won't handle this stuff themselves and our priors will become a useless relic.

Re: Agentic Coding Recommendations

#147
post #117

Earlier quoted context omitted.

> Last night I had a file with 38 mypy errors Fixing type checker errors should be one the least time consuming things you do. This was previously consuming a lot of your time? A lot of the AI discourse would be more effective if we could all see the actual work one another is doing with it (similar to the cloudflare post).

> AI discourse would be more effective if we could all see the actual work one another is doing with it Yes, this is a frequent problem both here and everywhere else. The discussions need to include things like exact model version, inference parameters, what system prompt you used, what user prompt, what code you gave it, what exactly it replied and so much more details, as currently almost every comment is "Well, I…

> The discussions need to include things like exact model version, inference parameters, what system prompt you used, what user prompt, what code you gave it, what exactly it replied and so much more details, as currently almost every comment is "Well, I used Sonnet last week and it worked great" without any details...Not to mention discussions around local models missing basic stuff like what quantization (if any) and what hardware you're running it on.

While I agree with "more details", the amount of details you're asking for is ... ridiculous. This is a HN comment, not a detailed study.

Re: Agentic Coding Recommendations

#148

Earlier quoted context omitted.

How is it more expensive?

You pay for aider with per-token pricing. Claude Code comes with a flatrate that gives you deep discounts.

Really depends on the type of coding you plan to do and how much.

The amusing thing is people normally recommend using aider to save money. With Aider, you can control the size of the context window, and selectively add/drop files from the window. I typically aim for under 25K tokens at a time. With Gemini, that's about 3 cents per prompt (and often much less when I have only, say, 10 tokens). So for me, I'd need to do well over 3000 coding prompts a month to get to $100. I simply don't use it that much.

Also, at work, I have Copilot, and one can use Aider with that. So I only pay for my personal coding at home.

Getting to the original question - Aider probably lags Claude Code significantly at this point. It's a fantastic tool and I still use it - primarily because it is editor agnostic. But some of the other tools out there do a lot more with agents.

To give you an idea - my combined AI use - including for non-code purposes - is well under $20/mo. Under $10 for most months. I simply don't have that much time to do coding in my free time - even with an AI doing it!

Re: Agentic Coding Recommendations

#149
post #117

Earlier quoted context omitted.

> Last night I had a file with 38 mypy errors Fixing type checker errors should be one the least time consuming things you do. This was previously consuming a lot of your time? A lot of the AI discourse would be more effective if we could all see the actual work one another is doing with it (similar to the cloudflare post).

> AI discourse would be more effective if we could all see the actual work one another is doing with it Yes, this is a frequent problem both here and everywhere else. The discussions need to include things like exact model version, inference parameters, what system prompt you used, what user prompt, what code you gave it, what exactly it replied and so much more details, as currently almost every comment is "Well, I…

I feel like that would get tiresome to write, read, and sort through. I don't like everyone's workflow, but if I notice someone making a claim that indicates they might be doing something better than me, then I'm interested.

Maybe keeping your HN profile/gist/repo/webpage up to date would be better.

Re: Agentic Coding Recommendations

#150

Earlier quoted context omitted.

As long as interfaces are well defined, comprehensive tests are written, memory is safely handled and time complexity is analyzable, who cares what the rest of the code looks like. I understand programming for the sake of programming, chasing purity and really digging into the creative aspects of coding. But I get that same kick out of writing perfect interfaces, knowing that the messier the code underneath is, the m…

> As long as interfaces are well defined, comprehensive tests are written, memory is safely handled and time complexity is analyzable, who cares what the rest of the code looks like The thing is, code that does all of the things you listed here is good looking code almost by definition If AI was anywhere near capable of producing this quality then it would be so thrilling, wouldn't it? But it's not. The consensus see…

Do you give the agent a style guide?

Do you perform (or have another agent perform) code reviews on the agent's code?

Do you discuss architecture and approach with the agent beforehand and compile that discussion into a design and development plan?

If you don't do these things, then you're just setting yourself up for failure.

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