The AI dooooooom thread

[frunk]

Claude is insanely good. Especially compared to 6 months ago when we still had to babysit it constantly.

The result is that we've been burning through our backlog as well as quarterly road map. Which is both good and bad. Good in that we can do more, bad in that our qa can't keep up.

We've been using Devin, and it is spectacular for code development.  We used Copilot before and it was barely worth the time investment but Devin is a completely different story.

[DGuller]

I feel like I've been the only one going in the opposite direction with AI.  In my old company we had ChatGPT Enterprise with access to pretty strong models.  In my new job we have Copilot.    Microsoft's ability to create fucking useless products is unmatched.  I'm actually doing more by hands now than I did a year ago.

[Crazy_Ivan80]

Claude is insanely good. Especially compared to 6 months ago when we still had to babysit it constantly.

The result is that we've been burning through our backlog as well as quarterly road map. Which is both good and bad. Good in that we can do more, bad in that our qa can't keep up.

We've been using Devin, and it is spectacular for code development.  We used Copilot before and it was barely worth the time investment but Devin is a completely different story.

I'll query my colleague,  he's an Ai enthusiast so he'll know about Devin.

Copilot... yes, but no. Don't need a copilot who'll gladly steer the plane into a mountain. We've cancelled that subscription

[Syt]

We ran a test last week. Someone asked if there's an easy way to create a seating chart for 400 people on tables of 10 if you want to keep teams together as much as possible. I suggested putting the task into ChatGPT 5.4 pro with max thinking (I've been using it for my project work with decent success). After an hour it was still crunching the problem.

The "fast" option had a solution in under one minute that was deemed "excellent" by our colleague.

[HisMajestyBOB]

I feel like I've been the only one going in the opposite direction with AI.  In my old company we had ChatGPT Enterprise with access to pretty strong models.  In my new job we have Copilot.    Microsoft's ability to create fucking useless products is unmatched.  I'm actually doing more by hands now than I did a year ago.

That matches my experience with Copilot enterprise. It's useful as an enhanced search engine to point me in the right direction, but it won't give me anything useful directly.

[crazy canuck]

I feel like I've been the only one going in the opposite direction with AI.  In my old company we had ChatGPT Enterprise with access to pretty strong models.  In my new job we have Copilot.    Microsoft's ability to create fucking useless products is unmatched.  I'm actually doing more by hands now than I did a year ago.

This is exactly the problem, people find a use case for a particular niche function, and the folks who don't know better say, see I told you so, all AI is useful.  By the way, another lawyer is heading to being disbarred in Ontario for using generative AI. This time the lawyer checked to make sure the case names were real, but the quotes from the cases he included in his brief were entirely fabricated. 

[Zanza]

MS Copilot is grounded based on your Outlook, Teams, SharePoint and OneDrive content. That makes it a fairly powerful engine to search and aggregate your conversations and files. But beyond that, especially those things integrated onto Office, it feels utterly useless. I don't understand why it does not have proper skills to actually do something with your office documents.

[Jacob]

I thought this was an interesting read:

A sufficiently detailed spec is code

This post is essentially this comic strip expanded into a full-length post:



For a long time I didn't need a post like the one I'm about to write. If someone brought up the idea of generating code from specifications I'd share the above image with them and that would usually do the trick.

However, agentic coding advocates claim to have found a way to defy gravity and generate code purely from specification documents. Moreover, they've also muddied the waters enough that I believe the above comic strip warrants additional commentary for why their claims are misleading.

In my experience their advocacy is rooted in two common misconceptions:

Misconception 1: specification documents are simpler than the corresponding code

They lean on this misconception when marketing agentic coding to believers who think of agentic coding as the next generation of outsourcing. They dream of engineers being turned into managers who author specification documents which they farm out to a team of agents to do the work, which only works if it's cheaper to specify the work than to do the work.

Misconception 2: specification work must be more thoughtful than coding work

They lean on this misconception when marketing agentic coding to skeptics concerned that agentic coding will produce unmaintainable slop. The argument is that filtering the work through a specification document will improve quality and promote better engineering practices.

I'll break down why I believe those are misconceptions using a concrete example.

Full article here: https://haskellforall.com/2026/03/a-sufficiently-detailed-spec-is-code

[crazy canuck]

There is an organization that now tracks the cases in which a court or tribunal comments on the fact that AI used in the submission presented by the parties has generated fabricated cases or legal principles.

In BC alone it happened in 10 cases LAST WEEK.

[The Minsky Moment]

There is an organization that now tracks the cases in which a court or tribunal comments on the fact that AI used in the submission presented by the parties has generated fabricated cases or legal principles.

In BC alone it happened in 10 cases LAST WEEK.

You see, that just demonstrates the superiority of the American legal system.  Our Department of Justice is fully capable of generating fabricated legal principles completely on its own, without any assistance from AI.

[crazy canuck]

There is an organization that now tracks the cases in which a court or tribunal comments on the fact that AI used in the submission presented by the parties has generated fabricated cases or legal principles.

In BC alone it happened in 10 cases LAST WEEK.

You see, that just demonstrates the superiority of the American legal system.  Our Department of Justice is fully capable of generating fabricated legal principles completely on its own, without any assistance from AI.

 

[CountDeMoney]

From Palantir's Youtube:

Cameron Stanley, Chief Digital and Artificial Intelligence Officer of the Department of War, shares how the DoW is driving enterprise-wide adoption of data, analytics, and AI to generate decision advantage—and what it takes to move cutting-edge technology from the lab to the warfighter at speed.

I saw this movie before, except it was the RAND Corporation, the war was Vietnam and it ran on a mainframe, not a graphics card.  These pencilneck fuckmonkeys never learn.

The use of "enterprise-wide" for the Department of Defense WAAAGH seems weird but fitting with this administration. (Though I guess corporate influence on defense purchasing has always been strong )

When you stuff your government with quasi-libertarian crypto-brah autism-maxxing techno-Marxists, that's what you're going to get.

Problem with you people is you should've beaten the shit out of them all in high school when you had the fucking chance.  That's what we did.

Now they're roaming the earth, destroying everything in their paths like the United States Government, a division of SalesForce(tm).

[Syt]

https://www.cnbc.com/2026/03/20/nvidia-ai-agents-tokens-human-workers-engineer-jobs-unemployment-jensen-huang.html

Nvidia's Huang pitches AI tokens on top of salary as agents reshape how humans work

The perks of working in Silicon Valley have long included high salaries. Now, some engineers may be offered a new incentive: artificial intelligence tokens.

Nvidia CEO Jensen Huang on Monday floated a novel compensation model that would give engineers a token budget on top of their base salary, effectively paying them to deploy AI agents as productivity multipliers.

Tokens, or units of data used by AI systems, can be spent to run tools and automate tasks and are becoming "one of the recruiting tools in Silicon Valley," Huang said.

″[Engineers] are going to make a few hundred thousand dollars a year, their base pay," Huang said at the chipmaker's annual GPU Technology Conference.

"I'm going to give them probably half of that on top of [their base pay] as tokens ... because every engineer that has access to tokens will be more productive."

The pitch signaled Huang's broader vision of the workplace, in which engineers oversee a fleet of AI agents capable of completing complex, multi-step tasks autonomously with minimal user input.

It is a vision that Huang has been building toward publicly. Last month, he told CNBC that Nvidia's employees would one day work alongside hundreds of thousands of AI agents.

"I have 42,000 biological employees, and I'm going to have hundreds of thousands of digital employees," he said.

The comments come as concerns grow that AI agents — software systems capable of independently executing complex, multi-step tasks — will hollow out white-collar work.

In a memo to investors, Howard Marks, founder of Oaktree Capital Management, warned of "an incredible leap ahead in AI's capabilities" that now allows it to "act autonomously" — a distinguishing point that determines its ability to substitute human labor.

"That difference is what separates a $50 billion market from a multi trillion dollar one," the veteran investor said.

Goldman Sachs estimates AI could potentially automate tasks accounting for 25% of all work hours in the U.S., enough to fuel fears of what some have grimly dubbed a "job apocalypse."

The bank sees a 15% productivity boost from AI, which could lead to 6% to 7% of jobs displaced over the adoption period.

"Risks are skewed toward greater displacement if AI proves more labor-displacing than prior technologies," said Joseph Briggs, Goldman's senior global economist.

Some 60% of today's workers are employed in occupations that didn't exist in 1940, Briggs said, citing a study by economist David Autor, suggesting that AI will render some roles obsolete while creating others that don't yet exist.

AI agents drive software demand

Huang has taken an optimistic view of the impact of AI agents on the software industry, describing it as "counterintuitive." Rather than reducing demand for software, AI agents will become its most voracious customers.

His logic goes: more AI agents mean more demand for the underlying software infrastructure they run on — the programs, tools, and computing resources that power them.

"The number of C-compilers that we use, the number of Python programs that we have, the number of instances, are growing very, very fast — because the number of agents we have that use these tools are going up," he said.

Bruno Guicardi, president and founder of the information technology company CI&T, described the change as nothing short of a paradigm shift. "A new layer of abstraction is being created through agents," he said.

"Now software engineers can 'tell' what computers should do, not in a programming language but in plain English. Work that used to take months to be done now takes a couple of days. And we see it only accelerating from here."

'Talent paradox'

The AI-fueled anxiety over labor displacement has been hard to contain, even as companies struggle to find skilled workers.

The job market is currently experiencing a "talent paradox" where 98% of C-suite executives expect AI to lead to headcount reductions over the next two years, while 54% cite talent scarcity as their top macro challenge, said Lewis Garrad, career practice leader at consultancy Mercer Asia.

Around 65% of executives expect 11% to 30% of their workforce to be redeployed or reskilled due to AI by 2026, Garrad estimated.

Entry-level jobs face the greatest risk as AI eliminates the "stepping-stone" tasks historically used to train new workers, further widening the skills gap at a time when demand for AI-literate workers is accelerating, Garrad added.

Roles involving data analysis, document processing, information comparison, and drafting initial reports are at risk of being "first in line" for displacement, said Andreas Welsch, founder of consultancy Intelligence Briefing and author of The Human Agentic AI Edge.

Goldman's Briggs also acknowledged the transition won't be frictionless, even under the most optimistic scenario, anticipating a peak gross jobless rate that will increase by around half a percentage point as the job market transitions into a new era.

But new jobs will emerge, Briggs said, stressing that technological change has always been a main driver of job growth in the long-run through the creation of new occupations.

Tens of millions of people are now employed in sectors such as computing, the gig economy, e-commerce, content creation and video games — industries that were science fiction a generation ago.

That said, integrating AI capabilities into existing corporate workflows may ultimately prove harder than the technology itself. Roughly 80% to 85% of AI projects have failed since 2018 — a sobering statistic for an industry awash in enthusiasm, noted Intelligence Briefing's Welsch.

"It would be undesired to have hundreds of thousands of agents that create more problems than they solve," he said.

[garbon]

Biological employees 

[Syt]

I'm sure that - as always in history - increased productivity will mean more free time and shorter work hours for all.