one thing it did massively for me was save me time from questions like should i go with X or Y option questions. before i used to just think longer about tradeoffs but with AI it became a lot faster. no more procrastination due to decision fatigue.
The gist is the OP went nuts replacing Google and Meta with self-hosted tools, and now he's feeding more data than ever into Anthropic or OpenAI (didn't specify, or I missed it. Skimming AI-generated blog posts tires the eyes.)
That's par for the course, honestly. News-cycle-driven anti-big-tech sentiment is weak fuel for a lifelong commitment. Something new was going to come along.
I am always happy for anyone who felt stuck on their side projects and no longer does, though.
Both my personal and social circles experience has been these tools are spotty at best. They often miss important things, overemphasize the wrong things, etc. At a surface level they look good but if you actually scrutinize them they fall apart.
I keep happening across articles claiming that AI doesn’t actually increase productivity and I’m completely confused.
I used to debate with people about this, but it didn’t really change anything. Now, I just shrug and continue on with my work and, if someone asks, I help them use AI better.
My main worry now is when the AI bubble is going to burst, and what’s affordable now becomes unaffordable.
Has anyone else considered that producing code faster isn't necessarily a good thing? There's a lot that goes into getting a solution correct that has nothing to do with programming. Just because you can scale code production doesn't mean you can scale things like understanding user wants and expectations. At a point you're more work for your self/organization because unless you get everything perfect the first time you're creating more work than you're resolving.
I think a better take is from the MIT study last year, the one that found almost all AI pilots failed.
In that study they found that pretty much everyone was using AI all the time, but they were just using their personal accounts rather than the company provided tools (hence the failures)
In light of this, I'd say there is a very good chance that people are offloading their work on AI, and then taking that saved time for themselves i.e. "I can finish the job report in 30 minutes rather than 3 hours now, so by 9:30 I'm done with work until after lunch."
The end result of this will either be layoffs to consolidate work or blocking of non-company monitored AI ensuring they can locate those now empty time slots.
>Now the transcript happens in the background, a summary lands in my Obsidian vault automatically, and I can actually be present in the conversation. That’s 20 minutes a day I got back, every day, without thinking about it.
Honest question: Do you actually read any of these notes?
I think there is a fundamental flaw with not taking notes. I'm convinced taking notes forces you to properly consider what is being said and you store the information in your brain better that way.
For one thing they were just early. Whatever measurements people made of AI six months ago are invalid. It’s a different animal now.
Plus you get a wildly different payoff the more you can take humans completely out of the loop. If it writes the code but humans review, you’re still bottleneck. If it designs and codes and reviews and goes back to designing, and so on, there’s no effective speed limit.
Big businesses aren’t going to work that way though. Which is why we shouldn’t be looking to them as thought leaders right now.
A lot of anecdotes here and in the article so I’ll add my own.
AI isn’t a silver bullet. It takes many iterations to get right. Yes, there is a lot of on-the-surface-it-looks-correct-so-ship-it stuff going on. I cringe when someone says “Well AI says..”
I don’t care what AI says! Unless you have done the research yourself and applied your own critical thinking then don’t send me that slop!
That is to say, there are some really good LLMs out there. I started using Claude and it is better for code than ChatGPT. But, you must understand and appreciate the code before you push it.
Another article claiming productivity without providing evidence of the quality of the work. How do we know these meeting summaries are accurate? And why are meeting summaries so great, anyway? I never had them before.
I had a thought about this coming from the book "Seeing Like a State."
Productivity in large organizations has never been and can never be purely of the legible work which is written in Jira tickets, documented, expressed clearly, but is sustained by an illegible network of relationships between the workers and unwritten knowledge/practices. AI can only consume the work which is legible, but as more work gets pushed into this realm, the illegible relationships and expertise becomes fragmented and atrophies, which puts backpressure on the system's productivity as a whole. And reading said book, my guess that attempting to impose perfect legibility for the sake of AI tooling will ultimately prove disastrous.
Show what you build; prove the productivity gains by working out through the extra 20 minutes you save everyday. Prove all this stuff instead of just saying "oh yeah bro I'm totally more productive with AI." It is trivial to track these metrics if you're serious about your productivity as an individual. The article is big on words but fails to show even 1 good effect of increased productivity or if it even exists.
The article mentions that the survey is wrong because the productivity gains do not show up in the metrics, etc. But what about your personal metrics? What projects did you ship, how many per week, what was the total amount of minutes saved per week, how did you use those minutes instead?
Otherwise its just productivity theater.
Most people never use a LLM assistant beacuse their lives aren't complicated enough to require a dedicated 24x7 assistant.
I don't want to put OP on blast here, but this is unfortunately just complete slop writing.
The points being made are fine, I think, but look, if it's faster for you to generate than it is for us to read, I think this qualifies as denial-of-service-lite.
I'm glad that this is making this individual more productive, but to quote the Fortune article:
> “AI is everywhere except in the incoming macroeconomic data,” Apollo chief economist Torsten Slok wrote in a recent blog post, invoking Solow’s observation from nearly 40 years ago. “Today, you don’t see AI in the employment data, productivity data, or inflation data.”
So I don't feel like TFA is a necessarily a rebuttal to this. The proof would be in the pudding.
I’d take this a step further and say that the deployment failure isn’t just management failing to provide training etc
If you take 100 people not all of them will have the intellectual curiosity, enthusiasm and flexibility to turn their ChatGPT license into productivity gains. No amount of training will overcome a fundamental lack of curiosity & willingness to experiment
And in very corporate environments there are lots of people like that who thrived just fine thus far because everything is written down in a step by step policy etc.
I don't really understand what it is with CompSci graduates and their bizarre aversion to handwriting, note taking, and any kind of skill that's derived from arts disciplines or "average joe" office systems.
Shorthand notation exists and it's more than possible to develop your own. I'd trust a OBS recording going in the background over some AI slop that has some chance to micro-hallucinate what it's hearing. It also sounds like a skill issue that the author can't control the pace of his own meetings to where being able to take good notes is seemingly impossible.
The author's AI use cases seem like a band-aid to cover bigger problems. Let's not even get into the part of the blog post where the author has started delegating internal thinking and reflection to conversations with a LLM.
> Meeting notes are the obvious one. Before Granola, I’d either scribble while half-listening or pay attention and try to reconstruct things afterwards from memory. Both were bad. Now the transcript happens in the background, a summary lands in my Obsidian vault automatically, and I can actually be present in the conversation. That’s 20 minutes a day I got back, every day, without thinking about it.
Yikes. So, 1) meetings at your company suck. In general, you should be engaged and take short, summary notes and todos while you're there; no need to have a transcript or AI summary. Talk to your manager about getting meetings right. 2) "without thinking about it" might not be the best phraseology in this overall context. :)
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[ 3.1 ms ] story [ 35.1 ms ] threadWhat products? This blog post is long on vibes and short on evidence.
> The actual gains are granular and personal, which makes them hard to count and easy to dismiss.
It also means the trillion dollar valuations might be bunk?
That's par for the course, honestly. News-cycle-driven anti-big-tech sentiment is weak fuel for a lifelong commitment. Something new was going to come along.
I am always happy for anyone who felt stuck on their side projects and no longer does, though.
Both my personal and social circles experience has been these tools are spotty at best. They often miss important things, overemphasize the wrong things, etc. At a surface level they look good but if you actually scrutinize them they fall apart.
I used to debate with people about this, but it didn’t really change anything. Now, I just shrug and continue on with my work and, if someone asks, I help them use AI better.
My main worry now is when the AI bubble is going to burst, and what’s affordable now becomes unaffordable.
The only question will be whether or not it gradually develops further from my assistant to my controller and then ... its own HR firing department.
In that study they found that pretty much everyone was using AI all the time, but they were just using their personal accounts rather than the company provided tools (hence the failures)
In light of this, I'd say there is a very good chance that people are offloading their work on AI, and then taking that saved time for themselves i.e. "I can finish the job report in 30 minutes rather than 3 hours now, so by 9:30 I'm done with work until after lunch."
The end result of this will either be layoffs to consolidate work or blocking of non-company monitored AI ensuring they can locate those now empty time slots.
Honest question: Do you actually read any of these notes? I think there is a fundamental flaw with not taking notes. I'm convinced taking notes forces you to properly consider what is being said and you store the information in your brain better that way.
Plus you get a wildly different payoff the more you can take humans completely out of the loop. If it writes the code but humans review, you’re still bottleneck. If it designs and codes and reviews and goes back to designing, and so on, there’s no effective speed limit.
Big businesses aren’t going to work that way though. Which is why we shouldn’t be looking to them as thought leaders right now.
I feel like this applies for many of you.
AI isn’t a silver bullet. It takes many iterations to get right. Yes, there is a lot of on-the-surface-it-looks-correct-so-ship-it stuff going on. I cringe when someone says “Well AI says..”
I don’t care what AI says! Unless you have done the research yourself and applied your own critical thinking then don’t send me that slop!
That is to say, there are some really good LLMs out there. I started using Claude and it is better for code than ChatGPT. But, you must understand and appreciate the code before you push it.
Is this productivity or paper pushing?
Productivity in large organizations has never been and can never be purely of the legible work which is written in Jira tickets, documented, expressed clearly, but is sustained by an illegible network of relationships between the workers and unwritten knowledge/practices. AI can only consume the work which is legible, but as more work gets pushed into this realm, the illegible relationships and expertise becomes fragmented and atrophies, which puts backpressure on the system's productivity as a whole. And reading said book, my guess that attempting to impose perfect legibility for the sake of AI tooling will ultimately prove disastrous.
The article mentions that the survey is wrong because the productivity gains do not show up in the metrics, etc. But what about your personal metrics? What projects did you ship, how many per week, what was the total amount of minutes saved per week, how did you use those minutes instead?
Otherwise its just productivity theater.
Most people never use a LLM assistant beacuse their lives aren't complicated enough to require a dedicated 24x7 assistant.
The points being made are fine, I think, but look, if it's faster for you to generate than it is for us to read, I think this qualifies as denial-of-service-lite.
> “AI is everywhere except in the incoming macroeconomic data,” Apollo chief economist Torsten Slok wrote in a recent blog post, invoking Solow’s observation from nearly 40 years ago. “Today, you don’t see AI in the employment data, productivity data, or inflation data.”
So I don't feel like TFA is a necessarily a rebuttal to this. The proof would be in the pudding.
If you take 100 people not all of them will have the intellectual curiosity, enthusiasm and flexibility to turn their ChatGPT license into productivity gains. No amount of training will overcome a fundamental lack of curiosity & willingness to experiment
And in very corporate environments there are lots of people like that who thrived just fine thus far because everything is written down in a step by step policy etc.
Shorthand notation exists and it's more than possible to develop your own. I'd trust a OBS recording going in the background over some AI slop that has some chance to micro-hallucinate what it's hearing. It also sounds like a skill issue that the author can't control the pace of his own meetings to where being able to take good notes is seemingly impossible.
The author's AI use cases seem like a band-aid to cover bigger problems. Let's not even get into the part of the blog post where the author has started delegating internal thinking and reflection to conversations with a LLM.
> Meeting notes are the obvious one. Before Granola, I’d either scribble while half-listening or pay attention and try to reconstruct things afterwards from memory. Both were bad. Now the transcript happens in the background, a summary lands in my Obsidian vault automatically, and I can actually be present in the conversation. That’s 20 minutes a day I got back, every day, without thinking about it.
Yikes. So, 1) meetings at your company suck. In general, you should be engaged and take short, summary notes and todos while you're there; no need to have a transcript or AI summary. Talk to your manager about getting meetings right. 2) "without thinking about it" might not be the best phraseology in this overall context. :)