The response to the Sal Khan op-ed resonated with me, along with other parts of this article. Something I’ve been digging more into is some of the figures around proposed job losses from AI. I think I even posted a simulation paper last week.
After posting that, I came across numerous papers which critique Frey & Osborne’s approach, who are some of the forefathers for the AI job losses figures we see banded around commonly these days. One such paper is here but i can dig out others: https://melbourneinstitute.unimelb.edu.au/__data/assets/pdf_...
It has made me very cautious around bold statements on AI - and I was already at the cautious end.
A previous company I worked for is San Francisco was very anti remote, but they announced on linked in that they are ok with remote engineers suddenly. It seems it’s still a workers market at least in SF. I’d AI could do it or even reduced head count I don’t think that would be the case.
Pretty ironic that he complains about Kahn citing someone who told him AI agents are capable of replacing 80% of call center employees, right after quoting Gary Marcus of all people, claiming LLMs will never live up to the hype.
If you want to focus on what AI agents are actually capable of today, the last person I'd pay any attention to is Marcus, who has been wrong about nearly everything related to AI for years, and does nothing but double down.
> In one example I cite in my article, ChatGPT Agent spends fourteen minutes futilely trying to select a value from a drop-down menu on a real estate website
Man dude, don't automate toil add an API to the website.It's supposed to have one!
> But for now, I want to emphasize a broader point: I’m hoping 2026 will be the year we stop caring about what people believe AI might do, and instead start reacting to its real, present capabilities.
> So, this is how I’m thinking about AI in 2026. Enough of the predictions. I’m done reacting to hypotheticals propped up by vibes. The impacts of the technologies that already exist are already more than enough to concern us for now…
SPOT ON, let us all take inspiration. "The impacts of the technologies that already exist are already more than enough to concern us for now"!
Cal Newport looked in the wrong places. He has no visibility into the usage of ChatGPT to do homework. The collapse of Chegg should tell you, with no other public information, that if 30% of students were already cheating somehow, somewhat weakly, they are now doing super-powerful cheating, and surely more than 30% of students at this stage.
It’s also kind of stupid to hand wave away, programming. Programmers are where all the early adopters of software are. He’s merely conflating an adoption curve with capabilities. Programmers, I’m sure, were also the first to use Google and smartphones. “It doesn’t work for me” is missing the critical word “yet” at the end, and really, is it saying much that forecasts about adoption in the metric, “years until when Cal Newport’s arbitrary criteria of what agent and adoption means meets some threshold only inside Cal Newport’s head” is hard to do?
There are 700m active weeklies for ChatGPT. It has joined the workforce! It just isn’t being paid the salaries.
a stellar piece, Cal, as always. short and straight to the point.
I believe that Codex and the likes took off (in comparison to e.g. "AI" browsers) because the bottleneck there was not reasoning about code, it was about typing and processing walls of text. for a human, the interface of e.g. Google Calendar is ± intuitive. for a LLM, any graphical experience is an absolute hellscape from performance standpoint.
CLI tools, which LLMs love to use, output text and only text, not images, not audio, not videos. LLMs excel at text, hence they are confined to what text can do. yes, multimodal is a thing, but you lose a lot of information and/or context window space + speed.
LLMs are a flawed technology for general, true agents. 99% of the time, outside code, you need eyes and ears. we have only created a self-writing paper yet.
I've seen organizations where 300 of 500 people could effectively be replaced by AI, just by having some of the the remaining 200 orchestrate and manage automation workflows that are trivially within the capabilities of current frontier models.
There's a whole lot of bullshit jobs and work that will get increasingly and opaquely automated by AI. You won't see jobs go away unless or until organizations deliberately set out to reduce staff. People will use AI throughout the course of their days to get a couple of "hours" of tasks done in a few minutes, here and there, throughout the week. I've already seen reports and projects and writing that clearly comes from AI in my own workplace. Right now, very few people know how to recognize and assess the difference between human and AI output, and even fewer how to calibrate work assignments.
Spreadsheet AIs are fantastic, reports and charting have just hit their stride, and a whole lot of people are going to appear to be very productive without putting a whole lot of effort into it. And then one day, when sufficiently knowledgable and aware people make it into management, all sorts of jobs are going to go quietly away, until everything is automated, because it doesn't make sense to pay a human 6 figures what an AI can do for 3 figures in a year.
I'd love to see every manager in the world start charting the Pareto curves for their workplaces, in alongside actual hours worked per employee - work output is going to be very wonky, and the lazy, clever, and ambitious people are all going to be using AI very heavily.
Part of the problem is that people don't know how to measure work effectively to begin with, let alone in the context of AI chatbots that can effectively do better work than anyone a significant portion of the adult population of the planet.
The teams that fully embrace it, use the tools openly and transparently, and are able to effectively contrast good and poor use of the tools, will take off.
> The industry had reason to be optimistic that 2025 would prove pivotal. In previous years, AI agents like Claude Code and OpenAI’s Codex had become impressively adept at tackling multi-step computer programming problems.
> But for now, I want to emphasize a broader point: I’m hoping 2026 will be the year we stop caring about what people believe AI might do, and instead start reacting to its real, present capabilities.
yes, 100%
I think that way too often, discussions of the current state of tech get derailed by talking about predictions of future improvements.
hypothetical thought experiment:
I set a New Year's resolution for myself of drinking less alcohol.
on New Year's Eve, I get pulled over for driving drunk.
the officer wants to give me a sobriety test. I respond that I have projected my alcohol consumption will have decreased 80% YoY by Q2 2026.
the officer is going to smile and nod...and then insist on giving me the sobriety test.
compare this with a non-hypothetical anecdote:
I was talking with a friend about the environmental impacts of AI, and mentioned the methane turbines in Memphis [0] that are being used to power Elon Musk's MechaHitler slash CSAM generator.
the friend says "oh, but they're working on building nuclear power plants for AI datacenters".
and that's technically true...but it misses the broader point.
if someone lives downwind of that data center, and they have a kid who develops asthma, you can try to tell them "oh in 5 years it'll be nuclear powered". and your prediction might be correct...but their kid still has asthma.
There needs to be a companion to Betteridge’s law that addresses AI-related headlines with “because since the beginning of time the field of artificial intelligence over-promises and under-delivers.”
"People using AI" had a meaningful change when they "joined the workforce" in 2025.
We may not have gotten fully-autonomous employees, but human employees using AI are doing way more than they could before, both in depth and scale.
Claude Code is basically a full-time "employee" on my (profitable) open source projects, but it's still a tool I use to do all the work. Claude Code is basically a full-time "employee" at my job, but it's still a tool I use to do all the work. My workload has shifted to high-level design decisions instead of writing the code, which is kind of exactly what would have happened if AI "joined the workforce" and I had a bunch of new hires under me.
I do recognize this article is largely targeted at non-dev workforces though, where it _largely_ holds up but most of my friends outside of the tech world have either gotten new jobs thanks to increased capability through AI or have severely integrated AI into whatever workflows they're doing at work (again, as a tool) and are excelling compared to employees who don't utilize AI.
Once again, more evidence mounts that AI is massively overhyped and limited in usefulness, and once again we will see people making grandiose claims (without evidence of course) and predictions that will inevitably fall flat in the future. We are, of course, perpetually just 3-6 months away from when everything changes.
I think Carmack is right, LLM's are not the route to AGI.
> I’m hoping 2026 will be the year we stop caring about what people believe AI might do, and instead start reacting to its real, present capabilities.
So well put.
LLMs are useful for a great many things. It's just that being the best new product of the recent years, maybe even defining a decade doesn't cut it. It has to be the century-defining, world-ending, FOMO-inducing massive thing to put Skynet to shame and justify investments in trillion dollars. It's either AI joining the workforce soon, or Nvidia and OpenAI aren't that valuable.
I guess it manages to maximize shareholder value, and make AI feel like a disappointment.
Agents as staff replacements that can tackle tasks you would normally assign to a human employee didn't happen in 2025.
Agents as LLMs calling tools in a loop to perform tasks that can be handled by typing commands into a computer absolutely did.
Claude Code turns out to be misnamed: it's useful for way more than just writing code, once you figure out how to give it access to tools for other purposes.
I think the browser agents (like the horribly named "ChatGPT Agent" - way to burn a key namespace on a tech demo!) have acted as a distraction from this. Clicking links is still pretty hard. Running Bash commands on the other hand is practically a solved problem.
In December of 2025, I took five tickets I was assigned in Jira and threw them at codex, which just did them, and with the help of MCPs, codex was able to read the ticket, generate some code, test the code, update gitlab, create a merge request on Gitlab, and update the Jira with the MR. CodeRabbit then reviewed the MR before a human had to look at it. It didn't happen in 2025, but I see it happening for 2026.
This article seems based in a poorly defined statement. What does "joining the workforce" actually mean?
There are plenty of jobs that have already been pretty much replaced by AI: certain forms of journalism, low-end photoshop work, logo generation, copywriting. What does the OP need to see in order to believe that AI has "joined the workforce"?
Agentic AI companies are doing millions in revenue. Just because agents haven’t spread to the entire economy yet doesn’t mean they are not useful for relatively complex tasks.
I recall someone saying stories of LLMs doing something useful to "I have a Canadian girlfriend" stories. Not trying to discredit or be a pessimist, can anyone elaborate how exactly they use these agents while working in interdependent projects in multi-team settings in e.g. regulated industries?
I follow at least one GitHub repo (a well respected one that's made the HN front page), and where everything is now Claude coded. Things do move fast, but I'm seriously under impressed with the quality. I've raised a few concerns, some were taken in, others seem to have been shut down with an explanation Claude produced that IMO makes no sense, but which is taken at face value.
This matches my personal experience. I was asked to help with a large Swift iOS app without knowing Swift. Had access to a frontier agent. I was able to consistently knock a couple of tickets per week for about a month until the fire was out and the actual team could take over. Code review by the owners means the result isn't terrible, but it's not great either. I leave the experience none the wiser: gained very little knowledge of Swift, iOS development or the project. Management was happy with the productivity boost.
I think it's fleeting and dread a time where most code is produced that way, with the humans accumulating very little institutional knowledge and not knowing enough to properly review things.
I had some .csproj files that only worked with msbuild/vsbuild that I wanted to make compatible with dotnet. Copilot does a pretty good job of updating these and identifying the ones more likely to break (say web projects compared to plain dlls). It isn't a simple fire and forget, but it did make it possible without me needing to do as much research into what was changing.
Is that a net benefit? Without AI, if I really wanted to do that conversion, I would have had to become much more familiar with the inner workings of csproj files. That is a benefit I've lost, but it would've also taken longer to do so, so much time I might not have decided to do the conversion. My job doesn't really have a need for someone that deeply specialized in csproj, and it isn't a particular interest of mine, so letting AI handle it while being able to answer a few questions to sate my curiosity seemed a great compromise.
A second example, it works great as a better option to a rubber duck. I noticed some messy programming where, basically, OOP had been abandoned in favor of one massive class doing far too much work. I needed to break it down, and talking with AI about it helped come up with some design patterns that worked well. AI wasn't good enough to do the refactoring in one go, but it helped talk through the pros and cons of a few design pattern and was able to create test examples so I could get a feel for what it would look like when done. Also, when I finished, I had AI review it and it caught a few typos that weren't compile errors before I even got to the point of testing it.
None of these were things AI could do on their own, and definitely aren't areas I would have just blindly trusted some vibe coded output, but overall it was productivity increase well worth the $20 or so cost.
(Now, one may argue that is the subsidized cost, and the unsubsidized cost would not have been worthwhile. To that, I can only say I'm not versed enough on the costs to be sure, but the argument does seem like a possibility.)
I was at a podiatrist yesterday who explained that what he's trying to do is to "train" an LLM agent on the articles and research papers he's published to create a chatbot that can provide answers to the most common questions more quickly than his reception team can.
He's also using it to speed up writing his reports to send to patients.
Longer term, he was also quite optimistic on its ability to cut out roles like radiologists, instead having a software program interpret the images and write a report to send to a consultant. Since the consultant already checks the report against any images, the AI being more sensitive to potential issues is a positive thing: giving him the power to discard erroneous results rather than potentially miss something more malign.
I don't see how AI can bring about 10%+ annual economic growth, let alone infinite abundance, without somehow crossing the bit-to-atom interface. Without a breakthrough in general-purpose robotics - which feels decades away - agents will just be confined to optimizing B2B SaaS. Human utility is rooted in the physical environment. I find digital abundance incredibly uninspiring.
It pretty much did join the work force. Listen to the fed chair, listen to related analysis, the unexpected overperformance of GDP isn’t directly attributed AI but it is very much in the “how did that happen?” conversation. And there’s plenty of softer, more anecdotal evidence in addition to that to respond to the headline with “It did.” The fact that it has been gradual and subtle as the very first agent tools reach production readiness, gain awareness in the public, start being used…? That really doesn’t seem at all unexpected as the path than “joining” would follow.
> So, this is how I’m thinking about AI in 2026. Enough of the predictions. I’m done reacting to hypotheticals propped up by vibes.
A lot of the predictions come from interviews and presentations with top tech executives. Their job is to increase the perceived value of their product, not to offer an objective assessment.
I've gotten a lot of value out of reading the views of experienced engineers; overall they like the tech, but they do not think it is a sentient alien that will delete our jobs.
I have also gotten a lot of value out of Cembalest's recent "eyes on the market", which looks at the economic side of this AI push.
> Their job is to increase the perceived value of their product
I don't agree. Your job cannot be "lie to the customer." They may see this as the easy way to get more money and justify their comfy position, but it is not their job.
> I've gotten a lot of value out of reading the views of experienced engineers; overall they like the tech, but they do not think it is a sentient alien that will delete our jobs.
I normally see things the same way you do, however I did have a conversation with a podiatrist yesterday that gave me food for thought. His belief is that certain medical roles will disappear as they'll become redundant. In his case, he mentioned radiology and he presented his case as thus:
A consultant gets a report + X-Ray from the radiologist. They read the report and confirm what they're seeing against the images. They won't take the report blindly. What changes is that machines have been learning to interpret the images and are able to use an LLM to generate the report. These reports tend not to miss things but will over-report issues. As a consultant will verify the report for themselves before operating, they no longer need the radiologist. If the machine reports a non-existent tumour, they'll see there's no tumour.
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[ 2.7 ms ] story [ 75.3 ms ] threadAfter posting that, I came across numerous papers which critique Frey & Osborne’s approach, who are some of the forefathers for the AI job losses figures we see banded around commonly these days. One such paper is here but i can dig out others: https://melbourneinstitute.unimelb.edu.au/__data/assets/pdf_...
It has made me very cautious around bold statements on AI - and I was already at the cautious end.
If you want to focus on what AI agents are actually capable of today, the last person I'd pay any attention to is Marcus, who has been wrong about nearly everything related to AI for years, and does nothing but double down.
Man dude, don't automate toil add an API to the website.It's supposed to have one!
> So, this is how I’m thinking about AI in 2026. Enough of the predictions. I’m done reacting to hypotheticals propped up by vibes. The impacts of the technologies that already exist are already more than enough to concern us for now…
SPOT ON, let us all take inspiration. "The impacts of the technologies that already exist are already more than enough to concern us for now"!
It’s also kind of stupid to hand wave away, programming. Programmers are where all the early adopters of software are. He’s merely conflating an adoption curve with capabilities. Programmers, I’m sure, were also the first to use Google and smartphones. “It doesn’t work for me” is missing the critical word “yet” at the end, and really, is it saying much that forecasts about adoption in the metric, “years until when Cal Newport’s arbitrary criteria of what agent and adoption means meets some threshold only inside Cal Newport’s head” is hard to do?
There are 700m active weeklies for ChatGPT. It has joined the workforce! It just isn’t being paid the salaries.
I believe that Codex and the likes took off (in comparison to e.g. "AI" browsers) because the bottleneck there was not reasoning about code, it was about typing and processing walls of text. for a human, the interface of e.g. Google Calendar is ± intuitive. for a LLM, any graphical experience is an absolute hellscape from performance standpoint.
CLI tools, which LLMs love to use, output text and only text, not images, not audio, not videos. LLMs excel at text, hence they are confined to what text can do. yes, multimodal is a thing, but you lose a lot of information and/or context window space + speed.
LLMs are a flawed technology for general, true agents. 99% of the time, outside code, you need eyes and ears. we have only created a self-writing paper yet.
There's a whole lot of bullshit jobs and work that will get increasingly and opaquely automated by AI. You won't see jobs go away unless or until organizations deliberately set out to reduce staff. People will use AI throughout the course of their days to get a couple of "hours" of tasks done in a few minutes, here and there, throughout the week. I've already seen reports and projects and writing that clearly comes from AI in my own workplace. Right now, very few people know how to recognize and assess the difference between human and AI output, and even fewer how to calibrate work assignments.
Spreadsheet AIs are fantastic, reports and charting have just hit their stride, and a whole lot of people are going to appear to be very productive without putting a whole lot of effort into it. And then one day, when sufficiently knowledgable and aware people make it into management, all sorts of jobs are going to go quietly away, until everything is automated, because it doesn't make sense to pay a human 6 figures what an AI can do for 3 figures in a year.
I'd love to see every manager in the world start charting the Pareto curves for their workplaces, in alongside actual hours worked per employee - work output is going to be very wonky, and the lazy, clever, and ambitious people are all going to be using AI very heavily.
Similar to this guy: https://news.ycombinator.com/item?id=11850241
https://www.reddit.com/r/BestofRedditorUpdates/comments/tm8m...
Part of the problem is that people don't know how to measure work effectively to begin with, let alone in the context of AI chatbots that can effectively do better work than anyone a significant portion of the adult population of the planet.
The teams that fully embrace it, use the tools openly and transparently, and are able to effectively contrast good and poor use of the tools, will take off.
Both of these agents launched mid-2025.
yes, 100%
I think that way too often, discussions of the current state of tech get derailed by talking about predictions of future improvements.
hypothetical thought experiment:
I set a New Year's resolution for myself of drinking less alcohol.
on New Year's Eve, I get pulled over for driving drunk.
the officer wants to give me a sobriety test. I respond that I have projected my alcohol consumption will have decreased 80% YoY by Q2 2026.
the officer is going to smile and nod...and then insist on giving me the sobriety test.
compare this with a non-hypothetical anecdote:
I was talking with a friend about the environmental impacts of AI, and mentioned the methane turbines in Memphis [0] that are being used to power Elon Musk's MechaHitler slash CSAM generator.
the friend says "oh, but they're working on building nuclear power plants for AI datacenters".
and that's technically true...but it misses the broader point.
if someone lives downwind of that data center, and they have a kid who develops asthma, you can try to tell them "oh in 5 years it'll be nuclear powered". and your prediction might be correct...but their kid still has asthma.
0: https://time.com/7308925/elon-musk-memphis-ai-data-center/
Very few people do
so neither Altman, the many CEOs industry wide, Engineering Managers, Software Engineers, “Forward Deployed Engineers” have to actually inspect
their demos show good looking output
its just the people in support roles that have to be like “wait a minute, this is very inconsistent”
all while everyone is doing their best not to get replaced
its clanker discrimination and mixed with clanker incompetence
We may not have gotten fully-autonomous employees, but human employees using AI are doing way more than they could before, both in depth and scale.
Claude Code is basically a full-time "employee" on my (profitable) open source projects, but it's still a tool I use to do all the work. Claude Code is basically a full-time "employee" at my job, but it's still a tool I use to do all the work. My workload has shifted to high-level design decisions instead of writing the code, which is kind of exactly what would have happened if AI "joined the workforce" and I had a bunch of new hires under me.
I do recognize this article is largely targeted at non-dev workforces though, where it _largely_ holds up but most of my friends outside of the tech world have either gotten new jobs thanks to increased capability through AI or have severely integrated AI into whatever workflows they're doing at work (again, as a tool) and are excelling compared to employees who don't utilize AI.
I think Carmack is right, LLM's are not the route to AGI.
So well put.
LLMs are useful for a great many things. It's just that being the best new product of the recent years, maybe even defining a decade doesn't cut it. It has to be the century-defining, world-ending, FOMO-inducing massive thing to put Skynet to shame and justify investments in trillion dollars. It's either AI joining the workforce soon, or Nvidia and OpenAI aren't that valuable.
I guess it manages to maximize shareholder value, and make AI feel like a disappointment.
Agents as LLMs calling tools in a loop to perform tasks that can be handled by typing commands into a computer absolutely did.
Claude Code turns out to be misnamed: it's useful for way more than just writing code, once you figure out how to give it access to tools for other purposes.
I think the browser agents (like the horribly named "ChatGPT Agent" - way to burn a key namespace on a tech demo!) have acted as a distraction from this. Clicking links is still pretty hard. Running Bash commands on the other hand is practically a solved problem.
There are plenty of jobs that have already been pretty much replaced by AI: certain forms of journalism, low-end photoshop work, logo generation, copywriting. What does the OP need to see in order to believe that AI has "joined the workforce"?
This matches my personal experience. I was asked to help with a large Swift iOS app without knowing Swift. Had access to a frontier agent. I was able to consistently knock a couple of tickets per week for about a month until the fire was out and the actual team could take over. Code review by the owners means the result isn't terrible, but it's not great either. I leave the experience none the wiser: gained very little knowledge of Swift, iOS development or the project. Management was happy with the productivity boost.
I think it's fleeting and dread a time where most code is produced that way, with the humans accumulating very little institutional knowledge and not knowing enough to properly review things.
Is that a net benefit? Without AI, if I really wanted to do that conversion, I would have had to become much more familiar with the inner workings of csproj files. That is a benefit I've lost, but it would've also taken longer to do so, so much time I might not have decided to do the conversion. My job doesn't really have a need for someone that deeply specialized in csproj, and it isn't a particular interest of mine, so letting AI handle it while being able to answer a few questions to sate my curiosity seemed a great compromise.
A second example, it works great as a better option to a rubber duck. I noticed some messy programming where, basically, OOP had been abandoned in favor of one massive class doing far too much work. I needed to break it down, and talking with AI about it helped come up with some design patterns that worked well. AI wasn't good enough to do the refactoring in one go, but it helped talk through the pros and cons of a few design pattern and was able to create test examples so I could get a feel for what it would look like when done. Also, when I finished, I had AI review it and it caught a few typos that weren't compile errors before I even got to the point of testing it.
None of these were things AI could do on their own, and definitely aren't areas I would have just blindly trusted some vibe coded output, but overall it was productivity increase well worth the $20 or so cost.
(Now, one may argue that is the subsidized cost, and the unsubsidized cost would not have been worthwhile. To that, I can only say I'm not versed enough on the costs to be sure, but the argument does seem like a possibility.)
He's also using it to speed up writing his reports to send to patients.
Longer term, he was also quite optimistic on its ability to cut out roles like radiologists, instead having a software program interpret the images and write a report to send to a consultant. Since the consultant already checks the report against any images, the AI being more sensitive to potential issues is a positive thing: giving him the power to discard erroneous results rather than potentially miss something more malign.
If my manager said to me tomorrow: "I have to either get rid of one of your coworkers or your use of AI tools, which is it?"
I would, without any hesitation, ask that he fire one of my coworkers. Gemini / Claude is way more useful to me than any particular coworker.
And now I'm preparing for my post-software career because that coworker is going to be me in a few years.
Obviously I hope that I'm wrong, but I don't think I am.
A lot of the predictions come from interviews and presentations with top tech executives. Their job is to increase the perceived value of their product, not to offer an objective assessment.
I've gotten a lot of value out of reading the views of experienced engineers; overall they like the tech, but they do not think it is a sentient alien that will delete our jobs.
I have also gotten a lot of value out of Cembalest's recent "eyes on the market", which looks at the economic side of this AI push.
I don't agree. Your job cannot be "lie to the customer." They may see this as the easy way to get more money and justify their comfy position, but it is not their job.
I normally see things the same way you do, however I did have a conversation with a podiatrist yesterday that gave me food for thought. His belief is that certain medical roles will disappear as they'll become redundant. In his case, he mentioned radiology and he presented his case as thus:
A consultant gets a report + X-Ray from the radiologist. They read the report and confirm what they're seeing against the images. They won't take the report blindly. What changes is that machines have been learning to interpret the images and are able to use an LLM to generate the report. These reports tend not to miss things but will over-report issues. As a consultant will verify the report for themselves before operating, they no longer need the radiologist. If the machine reports a non-existent tumour, they'll see there's no tumour.
https://www.worksinprogress.news/p/why-ai-isnt-replacing-rad...