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What we lost the last time code got cheap

https://www.poppastring.com/blog/what-we-lost-the-last-time-code-got-cheap
32•speckx•1h ago

Comments

andybak•32m ago
Personally I've found one of the biggest gains with coding agents is in helping me read code. Actually - that's a lie. I don't read the code. Mostly (unless my spidey-sense goes off) I ask the LLM to read the code and tell me what it does.

And then I make a decision based on that.

I guess I'm wondering if the article is missing have the picture. Yes - AI is wrong some of the time (and that % varies based on a host of variables). But it can read code as well as just write it. And that does matter as it changes the trade-offs this article is weighing up.

foobarian•6m ago
It's been pretty great for ramping up into codebases too. "Give me a summary of project in current checkout in markdown form."
nabbed•30m ago
I worried this blog post was going to pivot into a marketing pitch for some product, but no, it just describes the issue where the AI tool that generates your code probably won't document its reasons for the choices it makes. That documentation problem exists in the pre-AI era too, except that the reasons might exist in the heads of your co-workers and could possibly be teased out.

I know nothing about AI code generation (or about AI in general), but I wonder if you could include in your prompt a request that the AI describe the reasons for its choices and actually include those reasons as comments in the code.

andybak•28m ago
Isn't one of the common criticisms of AI code that it's a bit too keen to write extensive comments - even when they probably aren't needed?
Semaphor•24m ago
IME the comments are not useful though. I'm not the biggest fan of AI code, but the codes still way higher quality than the "this is what this does" comments
mbauman•21m ago
Well the comments tend to be superfluous "whats" (describing the code itself) instead of the more helpful "whys." And they're almost never the most useful "why nots".
idle_zealot•17m ago
> And they're almost never the most useful "why nots".

Really? I find that Claude really likes to write "why nots" in comments when iterating on implementations and fixing bugs, to the extent that the comments grow into spot-logs of overly-specific documentation of what was tried and why it was scrapped.

jnovek•23m ago
The AI can't really describe its reasoning, though. It can only look at its context history and find a justification (which it will then present as reasoning). In my experience asking the model "why did you do that" carries substantial hallucination risk.
0gs•20m ago
True, though I have found that forcing (I use an agent skill to do this) an LLM's agent to document the reasoning behind each "decision" it makes seems to lead to better decision-making. Or at least, more justifiable decisions (even if the justification is bad).
ddosmax556•17m ago
Perfectly possible IME, it just requires more time. Even if you understand all the (important) parts of your code and validate it, Ai still helps with productivity a lot. It's just not as fast as blindly vibe coding - not at first at least. Agents on their own without checks, and superficial prompts without understanding, result in agents either introducing bugs, or if you have an appropriate test harness, painfully slow, in my experience. It requires skill to use an agent effectively.
localhoster•8m ago
I think the issue that majority of agentic developers don't understand their design fully. Those holes, perviously, were have to be closed by a person eventually, and inherently you gain understanding in the process.

This is not the case eny more. I never thought LLMs write bad solutions, but when you let it think for you you loose something important, understanding. And when something brekas, some people consider this being a proof that the llm is the problem. And in a sense it is. But you are also to blame. And that's exactly the issue with this all industry - in order to move faster you don't need to "type" faster. A person bashing his hands on the keyboard randomly at top velocity can get pretty high wpm. In order to move master you need to _think_ faster, be _snappier_ and _sharper_ and most people aren't.

I like how one of my colleagues phrased it in a company meeting. He asked one of the c levels "for llm s to 10x me, I need to let them make all decitions and dictate intentions. By percentage, how much of the code you want me to _know_?"

rectang•5m ago
By default, Claude is set to avoid comments. Eventually I got tired of it deleting my own explanatory comments and overrode the behavior with an addition to CLAUDE.md.

I think Claude is just behaving like all those programmers who make a VERY BIG DEAL about how much they HATE HATE HATE comments that might reiterate what the code does so will go to any lengths to avoid them.

htx80nerd•17m ago
>The cost of producing code has collapsed. AI tools can generate functional, adequate, perfectly average code at a speed and cost that would have been unimaginable even five years ago. And like the outsourcing wave of the early 2000s, the economics are real and rational. Nobody is wrong for using these tools. The code they produce is often fine. It works. It passes tests. It might ship as-is.

After using AI for months (Claude, Gemini, ChatGPT) it is extremely rare for their code to work 'as is' first shot and almost always requires several iterations and cleaning up edge-cases.

When it does work 'first shot' it's usually when it's transferring existing working code to a new project which is slightly different.

kadhirvelm•10m ago
Curious what other teams are doing to keep encouraging people to think critically about their code? I’ve been finding it harder to keep people motivated, keep them engaged with all the changes coming in. And I can’t blame them, it’s been overwhelming. Is everyone else just using more AI..?

Camera Firmware Engineer, Consumer Devices

https://openai.com/careers/camera-firmware-engineer-consumer-devices-san-francisco/
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