Comment by olalonde
13 hours ago
I can give some recent examples.
- Significantly increased my productivity as a software engineer.
- Using it daily for Chinese-English translation. Significantly better than pre-LLM translation software. Also, great at teaching grammar, nuances, etc.
- General Q&A. Like "Googling" but much faster. This is probably the most common use case for me.
> - Significantly increased my productivity as a software engineer.
This is exactly the point that keeps coming up that folks are struggling to grasp, myself included. How are you measuring this? It certainly makes me feel productive, but I'm not sure I can confidently say it has actually made me more productive. It's made the easy stuff a no-brainer (e.g. boilerplate, simple logic) and the moderate stuff really hard. Never mind the hard stuff. Vetting the code has become a whole other job on its own. The only folks I've found who confidently claim it increases productivity appear to be online (and without evidence), because no one in person is willing to claim that and show it.
> It's made the easy stuff a no-brainer (e.g. boilerplate, simple logic) and the moderate stuff really hard. Never mind the hard stuff. Vetting the code has become a whole other job on its own.
Not everyone has the same requirements, skills, usage patterns, and outcomes. It's that simple.
I can agree with the skeptics that LLM generated code is usually crap. I rarely accept its output without significant edits unless it's truly boilerplate, and I want to avoid the need for that kind of code in the first place.
For me, the killer use case is debugging. I hate wasting time debugging something that should work except for mistakes, and now I do that probably 75% less than I used to because AI does it for me.
I don't know if it makes me that much more productive, but I certainly enjoy my work more not having to do as much tedious debugging, and it feels like I waste a lot less time doing it.
I'll share my experience.
I've never been a developer. Dabbled in frontend web for a bit (HTML/CSS/JS, no large frameworks) and felt like if I really dedicated some time to learning how to code, I'd be pretty decent at it. It's always intrigued me, and I've always had an itch to build things, but just never found the time. I'm in marketing now - I own an agency.
Over the last 6 months since the coding models really began to step up and get good, I've built several dedicated apps to support my business:
-Profitability optimizer and forecaster based on unit economics and current ad efficiency.
-Creative strategy tool that ingests brand and product data and helps explore primary and secondary personas and emotional motivators.
-Reporting tool that processes natural language queries and connects to multiple data sources to fetch results. Can schedule reports to post directly to Slack or email.
All robust and hosted on Railway. Team members can use them. Clients can use them. OAuth via Google.
Would any of this have been possible for me before the rise of frontier LLMs? Absolutely not. Learning the frameworks alone would have taken me longer than it's taken to just... build. Rapidly build and deploy. Total game changer for me.
Oh - and I'm building a game on the side. LLMs know Godot.
> How are you measuring this?
I attempt a programming task with and without LLM assistance. The attempt with LLM assistance is pretty much always completed faster and cleaner.
Another example: https://news.ycombinator.com/item?id=43991777
How much faster? How much cleaner? What tasks are you accomplishing?
2 replies →
Can someone bring this man a cup of Kool-Aid, stat?
> Significantly increased my productivity as a software engineer.
You’re going to have to define productivity as it applies to software engineering. With LLMs we’ve primarily seen the number of PRs over time being discussed as a proxy for LoC, as well as the speed of bootstrapping a small project. None of these have a known correlation with economic output. They just feel good, to the programmer, their manager, or both.
> Using it daily for Chinese-English translation. Significantly better than pre-LLM translation software. Also, great at teaching grammar, nuances, etc.
Yes dealing with language is the one area LLMs are actually designed for. But what’s the TAM for machine translation?
> General Q&A. Like "Googling" but much faster. This is probably the most common use case for me.
And now you’re missing any kind of traceability for the information that you “learn,” since it all gets spaghettified and then recombined into a pile of plausible slop with no attribution. Where before you had to do slightly more work to find the information you needed, now it’s available faster but you’re at complete mercy of literally 3 American companies plus the CCP for the accuracy of that information. Most people somehow seem happy with this arrangement.
> You’re going to have to define productivity as it applies to software engineering.
I meant it in a colloquial way. I just get more done, faster.
> And now you’re missing any kind of traceability for the information
Modern LLM assistants provide sources and references. While it can sometimes be just "slightly faster", it can genuinely save hours of research on complex ones. Also the "slightly faster" can add up to hours saved with frequent use.