- Potential job loss, particularly in the bottom half or so of jobs.
- Further wealth inequality due to so many factors but primarily because the companies providing these tools will capture the dollars that would’ve been spent on the jobs mentioned above.
- NIMBY-ism. AI = data centers and people are overwhelmingly deciding they don’t want these near their homes. I live in the Midwest and it’s been amazing how much opposition has been showing up for these projects.
Of course all of these are based on the speculation and “promises” of the tech. Many feel the time is to act now rather than once it’s too late, on the off chance these things do happen.
>- Potential job loss, particularly in the bottom half or so of jobs.
"the bottom half" of desk jobs, maybe. But most jobs in "the bottom half" overall are not desk jobs, and therefore aren't going to be replaced with AI anytime soon. Think burger flippers, waiters, and retail clerks.
My gut says yes and no. Generally I think jobs pushing atoms are probably safer but there's been headway on this as well. Maybe not total elimination but further skill and human labor intensive reduction seems to be the trend. For example: a fast food restaurant maybe needed 5 employees before and with these advances needs 2. Things like automated order kiosks, automatic fry machines, or bots that restock pre-packed inventory. More labor intensive tasks though like plumbing, electrical, etc already pay somewhere around the 50% mark anyway because of a lack of skilled workers.
On the physical side of jobs, robotics definitely has heavy investment and I think it will continuously and slowly eat away at some of these physical tasks. Look at a modern warehouse for example.
>Things like automated order kiosks, automatic fry machines, or bots that restock pre-packed inventory.
>On the physical side of jobs, robotics definitely has heavy investment and I think it will continuously and slowly eat away at some of these physical tasks. Look at a modern warehouse for example.
None of those are "AI", though. At best it's "tech".
Don’t disagree. It’s no different than how the lay person doesn’t differentiate between LLMs (the new thing) and ML (the thing that’s been around awhile). It’s all just AI.
Blame the marketing and tech leaders who throw “AI” in literally every marketing copy produced in the last 24 months.
The US seems to m mostly look down on blue collar work, service workers and other non-desk jobs. Maybe that's part of the reason why AI as a threat to low-skilled desk work is seen as such an offense. Those affected might slide into the "lower class" of people who use their hands to earn an income, and those in the "lower class" will have a harder time climbing up into a desk job
I wonder how many of those desk jobs actually create value though.
Some paper pushing asshole working for the government demands some paper bullshit. Some other paper pushing asshole working for bigco produces said paper. Is value actually created? Perhaps there's some risk mitigation but enough to justify their respective wages? And the need to push that paper back and forth locks the little guy out of competing in that market.
Yeah, it'll suck for a lot of people in the interim. But that will also put downward price pressure on a ton of things who's cost makes other value producing things not worth doing. If legal, design, engineering, etc, etc, services are made cheap in the "boring" cases then that becomes competitive advantage for the buyers which over time trickles down to their buyers and their buyers.
>I wonder how many of those desk jobs actually create value though.
>Some paper pushing asshole working for the government demands some paper bullshit. Some other paper pushing asshole working for bigco produces said paper. Is value actually created? Perhaps there's some risk mitigation but enough to justify their respective wages? And the need to push that paper back and forth locks the little guy out of competing in that market.
Probably a minuscule (<5%) amount? Think about it. In a 100 person tech company, how many people do you think is doing legal/compliance/security? More than 5?
I was really into this idea a few years ago. Even started logging.
However, I just cannot bring myself to constantly pull the transactions down manually from multiple banks.
Many suggest automating. How is this working in practice? Are there providers like Plaid you can use? Build web scrapers? Build PDF statement parsers?
I ended up just paying YNAB the $130/year or whatever they’re at now. High wife approval factor and everything just connects. They also have an API. In theory I could just constantly backup YNAB with PTA by pulling down transactions from the API.
I went the "build a few PDF statement parsers" route.
Some I wrote by hand using PyMuPDF, some I coerced Claude into writing (again using PyMuPDF) by uploading a sample bill (I'd never put my own data into an LLM but it's nice being able to find a sample bill, gets it close enough to correct that I can do the remaining bits if there are variations in bills over time).
Overall it's effort (and yes certainly a bunch effort for manually downloading transactions). The financial industry is very behind on this stuff clearly. I'm not sure in a few years whether I'll still think it's worth the effort I put in, which has gone down over the past few months as I automate things, but until it stops being fun I'll keep going.
From this post, I just got mine setup this morning. I already enjoy going through my 18 accounts every 2 weeks on pay day (yes, every credit card is the highest for the category of spend). For me, it seems like it would be just one extra step for me to get the data every 2 weeks.
But for most, I understand that they aren’t enjoying what I am doing every couple of weeks. I was using YNAB before but due to how many cards I had something got messed up in the importer all the time. Sometimes my transactions would duplicate or even get triplicated and then I would decline one of them only for it to pop up again a few days later. This lead to a very messed up and not accurate tracking. For me I was just fighting this thing every single day.
This is probably user error but after wiping it 3 times and starting over and over I just gave up and went back to mentally keeping track which worked but I needed something better.
Oooooh I like this a lot! I had Claude Code make me something in python quickly after I looked at the original post because I also prefer viewing time horizontally. I had mine do each month on a line. Sorry, didn't bother to host as a page. Here's the HTML/CSS though https://gist.github.com/bronco21016/d2d188c402b8e70c7bc115f4...
I like your layout a lot though so I might adapt that and there is still probably room to add the month label at the beginning of each month.
Early in the year I picked up "Dark Wire" by Joseph Cox. It was a fascinating dive into the world of "secure phones", particularly a company called Anom.
I also read:
"Digital Fortress" - Dan Brown (not strictly technically plausible but the suspense kept me hooked)
"Never Enough" - Andrew Wilkinson (meh)
Currently working on:
"The Technological Republic" - Andrew Karp
"Designing Data-Intensive Applications" - Martin Kleppmann
I had a tendency of a lot of false starts on books this year. I picked up several recent LLM/AI books and would make it like a chapter before realizing it was mostly just AI generated slop and gave up.
My local dealership adopted one of these for their service department. Prior to the AI assistant, you would call and immediately be placed on hold because the same people serving customers at the desk were answering the phone. The AI picks up right away and can schedule an oil change. It's fantastic and I'd love to see more of this. Of course it also has the ability to escalate to a human for the things it doesn't have capabilities for.
For narrow use cases like this I personally don't mind these tools.
If they have the ability to hook an llm up to a system that can schedule an oil change why can’t they provide a form on their website to do the same thing and save everyone the hassle?
Just ask your LLM to call the dealership. The only downside is spoken word is a bit slow for computers. Maybe we can even work out a protocol where the LLM voices talk faster and faster until they can't hear tokens clearly
At that point we’ll have to convert the voices into a form more amenable to machine to machine communication. Perhaps a system based on high and low signals.
They do, via the manufacturer's app. It works fine as well.
Situational context matters though, sometimes you get in the vehicle and get the alert. Just say "Hey Siri, call dealership" and away you go hands free. No messing with apps.
They do offer the ability to schedule an oil change via the website and yet some people still prefer to call. User preference and multi-channel servicing options are nice to support
Unsure about whether the specific dealership in question supports online booking, but there existing consumers whose preference is for a phone call over a web-based experience is definitely the case, at least in the US.
For example, even with the (digital-only) SAAS company I work at, we have a non-trivial amount of customers who with strong preferences to talk on the phone, ex to provide their credit card number, rather than enter it in the product. This is likely more pronounced if your product serves less tech-savvy niches.
That said, a strong preference for human call > website use doesn't necessarily imply even a weak preference for AI call > website use (likely customer-dependent, but I'd be surprised if the number with that preference was exactly 0)
how about the plainly obvious fact that every call tree system first spends 1-8 minutes going through all the things that you can actually do on the website instead of calling: do you really think they would bother with that if people aren’t calling about stuff that is easily done on the website? sure, we all agree that it is partly designed to get people to hang up in disgust and give up, but that is an obviously insufficient explanation compared to the simpler and more comprehensive explanation that people simply do, as a matter of fact, prefer to use the phone despite it being clearly less useful for easily-computer-able tasks.
fair enough. i totally believe that, and for the record i threw that bit in as an olive branch to the parent commenter… in retrospect, i shouldn’t have even included that rhetorical sludge. major chesterton’s fence area, that.
It's really dependent upon the expected downtime at the hotel for me. I do about 150 nights in hotels a year.
Some of those trips I'll have extended time of 18+ hours of not really doing anything outside of the hotel other than grabbing dinner. For those types of trips I'm definitely more apt to bring additional devices like my GLinet travel router and MAYBE a streaming stick. I've also brought RPis or MCUs for tinkering during my downtime.
However, other trips I'm with you. I bring my phone, laptop, iPad (required for job), and chargers and that's about it for devices. I really try to limit my packing to things I know I will use and honestly for probably 50% of my travel that's clean clothes, toothbrush, phone, and wallet.
My travel I describe above is solo, work related. When the family comes we tend to tow a 9,000 lbs condo on wheels, so literally the "kitchen sink".
Over time, I've taken less and less stuff. I still take my iPad in a keyboard case for longer trips, and as a backup for 2FA incase something happens to my phone, but now I mostly feel like my phone alone is "good enough." Doomscrolling on the phone works just as well on the road as at home :).
I do load my phone up with eBooks for unexpected downtime, and I do have an emulator on it. I would not chose to use my phone for reading or gaming normally, but on the road it's "good enough" - jack of all trades, master of none.
Of course if I'm traveling for work my work laptop comes, but I never put personal accounts on it.
The only trips I've been on with 18+ hours of down time were due to weather events (getting snowed in on a ski trip). That was with a big group. We just played card games, cooked, talked, and consumed copious amounts of alcohol to pass the time ¯\_(ツ)_/¯.
I use AI coding almost daily. I’m able to move my repositories into context easily through the multitude of AI coding tools and I see a massive boost in productivity. I say this as a junior dev. Often the outputs are “almost” and I make the necessary fixes to get it the rest of the way there.
To contrast with this, my org tried using a simple QA bot for internal docs and has been struggled to move anything beyond proof of concept. The proof of concepts have been awful. It answers maybe 60-70% of questions correctly. The major issue seems to be related to taking PDFs laced with images and poorly written explanations. To get decent performance from these RAG bots, a large FAQ has to be written for every question it gets wrong. Of course this is just my org so it can’t necessarily be extrapolated across industry. However, how often have people come across a new team and find there is little to no documentation, poorly written documentation, or outdated documentation?
Where am I going with these two thoughts? Maybe the blocker to pushing more adoption within orgs is twofold, getting the correct context into the model and having decent context to start with.
Extracting value from these things is going to require a heavy lift in data curation and developing the harnesses. So far most of that effort has gone into coding. It will take time for the nontechnical and technical to work together to move the rest of an org into these tools in my opinion.
The big bet of course then is ROI and time to adoption vs current burn rates of the model providers.
Yep. There are a lot of things that apply equally to human engineering teams in terms of productivity. Poor documentation and information architecture is a thing I have seen time and time again, and is always something I put time into course correcting for because it makes performing cognitive work much easier. Same goes for poorly factored codebases. They make doing any work feel like wading through mud. Throughout my career I have done a lot of work on what I would call platform engineering and product re-engineering and it's always to course correct for how difficult an environment has become to work in.
Agents are going to struggle with those same difficulties the way humans do too. You need to put work into making an environment productive to work in, and after having purposely switched my development workflow for the stuff I do outside of work to being "AI first on mobile", that's such a bandwidth constrained setup that it's really helping me to find all the things to optimise for to increase the batting average and minimise the back and forth.
I'm wondering if the ROI will be worth it anytime soon for anything other than coding, and anything that can be publically scraped of the internet. Or more to the point things that are at a enterprise level and require paid staff to train the model for a particular domain at an expert level of quality - and the ROI of such a task to be positive.
The thing is none of this is really happening under typical economic assumptions like ROI, rate of return, net PV, etc.
You see - on a pure ROI basis none of this should of existed. Even for coding I think - a lot of this is fuelled by investor money and even if developers took up the tooling I'm not sure it would pay off the capital investment. DeepMind wouldn't of been funded by Google, transformers would of never been invented if it was just based on expected ROI, etc. Most companies can't afford engineers/AI researchers on the side "just in case" it pays off especially back then when AI was a pie in the sky kind of thing. The only reason why any of this works is because Big Tech has more money than they can invest, and the US system punishes dividends meaning companies can justify "expected bad" investments as long as they can be dressed up and some pay off. They almost operate like internal VC's/funds because they had the money to do so.
This allows "arms race" and "loss leading" dynamics to take hold and be funded - which isn't about economics as much anymore. Most other industries/domains don't have the war chest or investors with very very deep pockets to make that a reality.
Sadly I think we as SWE's think it will also be other professions; what if instead we just disrupted our own profession and a few other smaller targets?
Isn't this just about context management? iOS Shortcuts has access to the same context: Mail, Calendar, Files. You could even add in Notes, Reminders, and Weather.
Use the new models action and write up a prompt and away it goes. Automate to run every morning or trigger it at any time of the day by clicking the Shortcut.
- Potential job loss, particularly in the bottom half or so of jobs.
- Further wealth inequality due to so many factors but primarily because the companies providing these tools will capture the dollars that would’ve been spent on the jobs mentioned above.
- NIMBY-ism. AI = data centers and people are overwhelmingly deciding they don’t want these near their homes. I live in the Midwest and it’s been amazing how much opposition has been showing up for these projects.
Of course all of these are based on the speculation and “promises” of the tech. Many feel the time is to act now rather than once it’s too late, on the off chance these things do happen.
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