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

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

#31

Post by Zigurd »

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…

Some domains don't have the established regularity of architecture that it takes to achieve 10X efficiency. Two I can think of off the top of my head are embedded systems, with a variety of sensors, outputs, processing power, and memory, and novel protocols like ATProto, for which training data is thin on the ground.

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

#32

Post by pornel »

esafak wrote: post #23

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…

I agree that removing human from the loop is the next stage, but we're not there yet beyond small programs.

Agents left alone tend to create so much tech debt, that once the program becomes so messy that they can't fix one bug without creating two new bugs, it's too late to even clean that up.

The program will be super tidy in superficial aspects that linters catch (everything neatly formatted and verbosely commented), and roughly appear to do what it's supposed to do, but everything in between will be "I can't even".

We need something else than formal methods, because the problem is usually in lack of simplicity - you get four versions of the problem solved in four times in four in different ways, each uniquely flawed and just incompatible enough with the others that unifying them is too big and hairy for the agent, and will result in eight different glue adapters written in the process.

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

#33

Post by _se »

hungryhobbit wrote: post #27

>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 st…

Tell me you're bad at software engineering without telling me you're bad at software engineering.

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

#34

Post by mckee_plus_plus »

leoedin wrote: post #11
steveBK123 wrote: post #8

Earlier quoted context omitted.

The other hard to measure part is that I see/hear a lot of LLM usage going towards dev work that was never prioritized before. Suddenly devs who were cranking out features with no interest in infrastructure are attacking giant refactors to make the code more understandable to the LLM. Other devs are using LLMs to build themselves quality of life SDLC tools completely separate from the core code base. Plenty of other…

The quality of my bash scripts is 100x what they used to be. Proper help messages, flag parsing, functions, internal variables, using sed all the time (I could never wrap my head around that). Of course, the main issue is that they’re completely undebbugable now. My bash scripts used to be a sequential list of commands, now they’re 500 lines of variable laden functions. Is my life any better? Dunno. But it’s satisfyi…

I switched to js for dev related scripting after seeing how much python scripting is used for portable c++ projects like chromium.

A node glob() or a regexp string.replace call is probably easier to read than spaghetti shell.

And your llm might do a much better job of creating clean, readable and testable code.

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

#35

Post by mckee_plus_plus »

_se wrote: post #33
hungryhobbit wrote: post #27

>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 st…

Tell me you're bad at software engineering without telling me you're bad at software engineering.

Tell me you're bad at people skills without telling me you're bad at people skills

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

#36

Post by Aurornis »

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…

> * Mastered: 10x+

This really needs to be calibrated to the type of work and complexity.

I can actually believe that LLMs would speed up basic web dev work in small, simple codebases 10X for simple requests.

These conversations usually turn into people talking past each other because they’re working on different things. For other less routine and more complex work, expecting a 10X productivity boost is not realistic at all. It doesn’t matter how good you get at writing prompts and reviewing plans. LLMs just don’t solve everything for you in a good way. Some times the true nature of the problem is revealed while implementing it and by deferring everything to an LLM you spend days throwing tokens at the wrong thing. There is a lot of work where the LLM speed up comes from helping you quickly search docs and codebases and double check your code, but handing the entire thing off to an LLM isn’t reasonable. These tasks aren’t going to reach this mythical 10X productivity boost that is genuinely achievable for much simpler work.

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

#38

Post by trey-jones »

msephton wrote: post #37

Does the number × depend on how big your thinking is? If you are only 2× then you need to think bigger, aim higher, etc. I think the limit on the 2× is not the ai? Where is the limit now? I think it's unknown.

Definitely feels like a lot more than 2x to me. Any time it feels like the agent is taking a long time I have to look in the mirror and say to myself "What could you have done in 5 minutes?"

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

#39

Post by cyanregiment »

0.25x because I scope bigger now and then I may get a few "free" React components but largely doing all that work of putting it together.

Wouldn't trade it though. Feel like I can overall do more with less time and energy.

At the end of the day, AI is making me work more (good thing). If you count that as productivity, then sure.

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

#40

Post by gmassman »

nasretdinov wrote: post #17
leoedin wrote: post #11

Earlier quoted context omitted.

The quality of my bash scripts is 100x what they used to be. Proper help messages, flag parsing, functions, internal variables, using sed all the time (I could never wrap my head around that). Of course, the main issue is that they’re completely undebbugable now. My bash scripts used to be a sequential list of commands, now they’re 500 lines of variable laden functions. Is my life any better? Dunno. But it’s satisfyi…

> the main issue is that they’re completely undebbugable now Well, that means the quality actually dropped then :). Looking impressive isn't equal to quality, understandability and reliability is

Not necessarily…. As with all engineering choices there are tradeoffs involved. There can be both advantages and disadvantages to using AI to build scripts. And more likely than not you’ll need AI to help debug the scripts when they have issues. Real tradeoffs to consider.
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