2x, not 10x: coding with LLMs in 2026 • Hacker News Board

Re: 2x, not 10x: coding with LLMs in 2026

#21

Post by dgellow » Thu, Jul 30, 2026, 7:41 PM UTC

forlorn_mammoth wrote: post #9

what_hn wrote: post #3

Does a 60x speedup count? Are you still copying and pasting from chatgpt, because if so your definitely doing it wrong.

Wait, how about an infinite speedup? A friend of mine couldn't code, and now he can. So he is infinity-x better at coding thanks to LLMS! Take that, you mere 10x-ers! Your days are toast!

Left behind, as the infinite-x rockstar developer roars off on their motorbike, trailing a plume of dust behind

Re: 2x, not 10x: coding with LLMs in 2026

#22

Post by [deleted] » Thu, Jul 30, 2026, 7:44 PM UTC

[deleted]

Re: 2x, not 10x: coding with LLMs in 2026

#23

Post by esafak » Thu, Jul 30, 2026, 7:44 PM UTC

This is a dated take to me. I think the next stage in unlocking productivity is so called "loop engineering"; figuring out how to effectively not read all the code while ensuring quality. To me that means implementing statistical quality control and formal methods.

Before I get there I have to figure out how to reliably audit plan adherence. The problem is that when the specs are in natural language, as they are, you need a fallible LLM to verify it.

Re: 2x, not 10x: coding with LLMs in 2026

#24

Post by monknomo » Thu, Jul 30, 2026, 7:45 PM UTC

openasocket wrote: post #20

deergomoo wrote: post #6

> As for documentation, I've found this simple instruction to vastly improve LLMs' output: > Never write READMEs, docstrings, or comments. I will write those myself later. And yes, I really mean this. This is quite validating as I came to the exact same conclusion myself. We’re required to use an LLM for every task at work that touches code†, and I was really struggling to get Claude to stop with the long waffly comm…

+10, I can't stand AI-generated comments. Half the time they are paragraph-length translations of every 5 lines of code into English prose, or just regurgitating whatever prompt they were given. When they actually try making high level comments they are worse than useless. It's really hard to put into words exactly why. It's something about how they are very verbose, but at the same time vague and stated in a slightl…

locally correct and globally incoherent is how they seem to me. I, and a number of folks I have talked to, find some of them incomprehensible. Like each sentence makes sense, but the overall thing does not.

Re: 2x, not 10x: coding with LLMs in 2026

#25

Post by tristor » Thu, Jul 30, 2026, 7:47 PM UTC

My observation is that AI tools generally make people /less/ productive. They are more productive in that they produce more stuff, but they are less productive in that the stuff they are producing has lower inherent value delivery. The primary place where I see this in software teams as a Product person is in document creation. If you are using an AI tool to produce internal documents, this is likely a net-negative value activity that actually reduces the overall productivity of the team. Why? Because writing is thinking. By handing off document creation to an LLM for a document that's supposed to communicate important details between teams (e.g. technical design docs, requirements docs, strategy docs) you are actually handing off thinking, or rather handing off not-thinking as AI tools cannot "think". The outcome of is poorly "thought out" slop that generates more work for everyone involved to resolve /or/ everyone simply ignores the document and the previous processes stop being useful.

If anything, I'd say AI tools in /most/ enterprises as people are trying to use them now are at least a -30% of productivity. If used correctly for taking a human-written/thought requirements doc, converting it into an interactive prototype that can be critiqued and ultimately included as part of the solution alignment within the requirements doc, and then is handed to an engineering team that is effective at using humans and AI to produce code, then it's probably a benefit. But most businesses lack the internal rigor, quality culture, and data governance to support properly applying AI tools in a high context manner internal to their business.

Re: 2x, not 10x: coding with LLMs in 2026

#26

Post by watso » Thu, Jul 30, 2026, 7:49 PM UTC

You still have to know what you’re doing. That came from years of doing it by hand. Where is that necessary experience going to come from for the current and future generations of juniors?

Re: 2x, not 10x: coding with LLMs in 2026

#27

Post by hungryhobbit » Thu, Jul 30, 2026, 7:54 PM UTC

>As such, I use LLMs mainly to produce a rough draft of the code which I then iterate on heavily, at least until I like the general structure

Tell me you just started with agentic programming without telling me you just started using agentic programming.

Look, don't get me wrong: new folks learning tech should absolutely write articles about it! But their claims might very well change once they learn more .. and I strongly suspect that will be the case here.

Re: 2x, not 10x: coding with LLMs in 2026

#28

Post by coffeebeqn » Thu, Jul 30, 2026, 7:56 PM UTC

gashad wrote: post #5

This reminds me of themes I recently saw in [Harness Engineering is not Enough: Why Software Factories Fail]( https://www.youtube.com/watch?v=Ib5GBkD555M ) (Warning: the last 3 slides seem like an advertisement). One thing I liked is how Dex has a little graphic he glossed over showing software development is - 25% planning & aligning with other teams - 25% coding - 25% testing/verifying - 25% code review/rework One…

I use CC to do the testing and verifying in multiple deployment environments. It’s faster at things like coming up a plausible test payload or ten, querying a bunch of metrics from datadog, querying and verifying state from a db before and after testing, scanning all the deployed logs for relevant errors. For me that has been more of an uplift than the coding. I still feel like communication it’s worst at. So writing tickets, getting a decision out of a group, documenting only the important things, etc. it’s still not that good at

Re: 2x, not 10x: coding with LLMs in 2026

#29

Post by dev_hugepages » Thu, Jul 30, 2026, 7:58 PM UTC

lazopm wrote: post #16

The way I see it you should calibrate the way you work with LLMs based on how confident you are on that specific area, and if it's your responsibility to own/understand it. Here's how it feels for me: * Learning stage: 0.5x - 1x. I change my system prompt to teacher mode, taking the productivity hit for actually learning the system/tool pays off dividends later. I change my system prompt to "teacher mode" and slowly…

Hey, could you share the prompt you're using for "teacher mode"?

Re: 2x, not 10x: coding with LLMs in 2026

#30

Post by prmoustache » Thu, Jul 30, 2026, 7:58 PM UTC

what_hn wrote: post #3

Does a 60x speedup count? Are you still copying and pasting from chatgpt, because if so your definitely doing it wrong.

If 60x was a thing, we would see many fantastic products appearing on the market, every product would have improved or goten major new interesting features. Yet it hasn't really happened.