4 ms·

This is the stealth team I hinted at in a comment on here last week about the "Dark Factory" pattern of AI-assisted software engineering: https://news.ycombinat

by simonw 9mo ago

This is the stealth team I hinted at in a comment on here last week about the "Dark Factory" pattern of AI-assisted software engineering: https://news.ycombinator.com/item?id=46739117#46801848 https://news.ycombinator.com/item?id=46739117#46801848 I wrote a bunch more about that this morning: https://simonwillison.net/2026/Feb/7/software-factory/ https://simonwillison.net/2026/Feb/7/software-factory/ This one is worth paying attention to to. They're the most ambitious team I've see exploring the limits of what you can do with this stuff. It's eye-opening.

enderforth 9mo ago
This right here is where I feel most concerned > If you haven’t spent at least $1,000 on tokens today per human engineer, your software factory has room for improvement Seems to me like if this is true I'm screwed no matter if I want to "embrace" the "AI revolution" or not. No way my manager's going to approve me to blow $1000 a day on tokens, they budgeted $40,000 for our team to explore AI for the entire year. Let alone from a personal perspective I'm screwed because I don't have $1000 a month in the budget to blow on tokens because of pesky things that also demand financial resources like a mortgage and food. At this point it seems like damned if I do, damned if I don't. Feels bad man.
- navanchauhan 9mo ago
  I think corporate incentives vs personal incentives are slightly different here. As a company trying to experiment in this moment, you should be betting on token cost not being the bottleneck. If the tooling proves valuable, $1k/day per engineer is actually pretty cheap. At home on my personal setup, I haven't even had to move past the cheapest codex/claude code subscription because it fulfills my needs ¯\_(ツ)_/¯. You can also get a lot of mileage out of the higher tiers of these subscriptions before you need to start paying the APIs directly.
  - rune-dev 9mo ago
    How is 1k/day cheap? Even for a large company? Takes like this are just baffling to me. For one engineer that is ~260k a year.
    - libraryofbabel 9mo ago
      I do not really agree with the below, but the logic is probably: 1) Engineering investment at companies generally pays off in multiples of what is spent on engineering time. Say you pay 10 engineers $200k / year each and the features those 10 engineers build grow yearly revenue by $10M. That’s a 4x ROI and clearly a good deal. (Of course, this only applies up to some ceiling; not every company has enough TAM to grow as big as Amazon). 2) Giving engineers near-unlimited access to token usage means they can create even more features, in a way that still produces positive ROI per token. This is the part I disagree with most. It’s complicated. You cannot just ship infinite slop and make money. It glosses over massive complexity in how software is delivered and used. 3) Therefore (so the argument goes) you should not cap tokens and should encourage engineers to use as many as possible. Like I said, I don’t agree with this argument. But the key thing here is step 1. Engineering time is an investment to grow revenue. If you really could get positive ROI per token in revenue growth, you should buy infinite tokens until you hit the ceiling of your business. Of course, the real world does not work like this.
      - rune-dev 9mo ago
        Right, I understand of course that AI usage and token costs are an investment (probably even a very good one!). But my point is moreso that saying 1k a day is cheap is ridiculous. Even for a company that expects an ROI on that investment. There’s risks involved and as you said, diminishing returns on software output. I find AI bros view of the economics of AI usage strange. It’s reasonable to me to say you think its a good investment, but to say it’s cheap is a whole different thing.
        libraryofbabel 9mo ago
        Oh sure. We agree on all you said. I wouldn’t call it cheap either. :) The best you can say is “high cost but positive ROI investment.” Although I don’t think that’s true beyond a certain point either, certainly not outside special cases like small startups with a lot of funding trying to build a product quickly. You can’t just spew tokens about and expect revenue to increase. That said, I do reserve some special scorn for companies that penny-pinch on AI tooling. Any CTO or CEO who thinks a $200/month Claude Max subscription (or equivalent) for each developer is too much money to spent really needs to rethink their whole model of software ROI and costs. You’re often paying your devs >$100k yr and you won’t pay $2k / yr to make them more productive? I understand there are budget and planning cycle constraints blah blah, but… really?!
- buster 9mo ago
  May be the point is, that the one engineer replaces 10 engineers by using the dark factory which by definition doesn't need humans.
  - FeteCommuniste 9mo ago
    The great hope of CEOs everywhere.
  - falloutx 9mo ago
    And then he get replaced by a new hire when he asks for a raise.
- simonw 9mo ago
  Yeah, that's one part of this that didn't sit right with me. I don't think you need to spend anything like that amount of money to get the majority of the value they're describing here. Edit: added a new section to my blog post about this: https://simonwillison.net/2026/Feb/7/software-factory/#wait-1-000-day-per-engineer- https://simonwillison.net/2026/Feb/7/software-factory/#wait-...
  - deleted 9mo ago
    [deleted]
  - noosphr 9mo ago
    This is the part that feels right to me because agents are idiots. I built a tool that writes (non shit) reports from unstructured data to be used internally by analysts at a trading firm. It cost between $500 to $5000 per day per seat to run. It could have cost a lot more but latency matters in market reports in a way it doesn't for software. I imagine they are burning $1000 per day per seat because they can't afford more.
    - threecheese 9mo ago
      They are idiots, but getting better. Ex: wrote an agent skill to do some read only stuff on a container filesystem. Stupid I know, it’s like a maintainer script that can make recommendations, whatever. Another skill called skill-improver, which tries to reduce skill token usage by finding deterministic patterns in another skill that can be scripted, and writes and packages the script. Putting them together, the container-maintenance thingy improves itself every iteration, validated with automatic testing. It works perfectly about 3/4 of the time, another half of the time it kinda works, and fails spectacularly the rest. It’s only going to get better, and this fit within my Max plan usage while coding other stuff.
      - noosphr 9mo ago
        LLMs are idiots and they will never get better because they have quadratic attention and a limited context window. If the tokens that need to attend to each other are on opposite ends of the code base the only way to do that is by reading in the whole code base and hoping for the best. If you're very lucky you can chunk the code base in such a way that the chunks pairwise fit in your context window and you can extract the relevant tokens hierarchically. If you're not. Well get reading monkey. Agents, md files, etc. are bandaids to hide this fact. They work great until they don't.
- reilly3000 9mo ago
  My friend works at Shopify and they are 100% all in on AI coding. They let devs spend as much as they want on whatever tool they want. If someone ends up spending a lot of money, they ask them what is going well and please share with others. If you’re not spending they have a different talk with you. As for me, we get Cursor seats at work, and at home I have a GPU, a cheap Chinese coding plan, and a dream.
  - r0b05 9mo ago
    > I have a GPU, a cheap Chinese coding plan, and a dream Right in the feels
  - dude250711 9mo ago
    > If someone ends up spending a lot of money, they ask them what is going well and please share with others. If you’re not spending they have a different talk with you. Make a "systemctl start tokenspender.service" and share it with the team?
  - sergiotapia 9mo ago
    I get $200 a month, I do wish I could get $1000 and stop worrying about trying the latest AI tools.
  - zingar 9mo ago
    What results are you getting at home?
- mgkimsal 9mo ago
  I read that as combined, up to this point in time. You have 20 engineers? If you haven't spent at least $20k up to this point, you've not explored or experienced enough of the ins and outs to know how best to optimize the use of these tools. I didn't read that as you need to be spending $1k/day per engineer. That is an insane number. EDIT: re-reading... it's ambiguous to me. But perhaps they mean per day, every day. This will only hasten the elimination of human developers, which I presume is the point.
- christoph 9mo ago
  Same. Feels like it goes against the entire “hacker” ethos that brought me here in the first place. That sentence made me actually feel physically sick on initial read as well. Everyday now feels like a day where I have exponentially less & less interest in tech. If all of this AI that’s burning the planet is so incredible, where are the real world tangible improvements? I look around right now and everything in tech, software, internet, etc. has never looked so similar to a dumpster fire of trash.
  - zingar 9mo ago
    The biggest rewards for human developers came from building addictive eyeball-getters for adverts so I don’t see how we can expect a very high bar for the results of their replacement AI factories. Real-world and tangible just seem completely out of the picture.
  - Garlef 9mo ago
    Maybe think about it like this: A dev is ~1k per day. If the tool gives you 3x then 2x in cost is fine. (The current cost of 1k is "real" and ultimately, even if you tinker on your own, you're paying this in opportunity cost) ((caveats, etc))
  - lubujackson 9mo ago
    Yes, exactly this. My biggest issue is how uncurious the approach seems. Setting a "no-look" policy seems cutting edge for two seconds, but prevents any actual learning about how and why things fail when you have all the details. They are just hamstringing their learning. We still need to specify precisely what we want to have built. All we know from this post is what they aren't doing and that they are pissing money on LLMs. I want to know how they maintain control and specificity, share control and state between employees, handle conflicts and errors, manage design and architectural choices, etc. All of this seems fun when hacking out a demo but how in the world does this make sense when there are any outside influences or requirements or context that needs to be considered or workflows that need to be integrated or scaling that needs to occur in a certain way or any of the number of actual concerns that software has when it isn't built in a bubble?
- DrewADesign 9mo ago
  > No way my manager's going to approve me to blow $1000 a day on tokens, they budgeted $40,000 for our team to explore AI for the entire year. To be fair, I’ll bet many embracing concerning advice like that have never worked for the same company for a full year.
riazrizvi 9mo ago
Until there's something verifiable it's just talk. Talk was cheap. Now talk has become an order of magnitude cheaper since ChatGPT.
belter 9mo ago
Can you make an ethical declaration here, stating whether or not you are being compensated by them? Their page looks to me like a lot of invented jargon and pure narrative. Every technique is just a renamed existing concept. Digital Twin Universe is mocks, Gene Transfusion is reading reference code, Semport is transpilation. The site has zero benchmarks, zero defect rates, zero cost comparisons, zero production outcomes. The only metric offered is "spend more money". Anyone working honestly in this space knows 90% of agent projects are failing. The main page of HN now has three to four posts daily with no substance, just Agentic AI marketing dressed as engineering insight. With Google, Microsoft, and others spending $600 billion over the next year on AI, and panicking to get a return on that Capex....and with them now paying influencers over $600K [1] to manufacture AI enthusiasm to justify this infrastructure spend, I won't engage with any AI thought leadership that lacks a clear disclosure of financial interests and reproducible claims backed by actual data. Show me a real production feature built entirely by agents with full traces, defect rates, and honest failure accounting. Or stop inventing vocabulary and posting vibes charts. [1] - https://news.ycombinator.com/item?id=46925821 https://news.ycombinator.com/item?id=46925821
- AstroBen 9mo ago
  Simon does have a disclosure on his site about not being compensated for anything: https://simonwillison.net/about/#disclosures https://simonwillison.net/about/#disclosures
  - belter 9mo ago
    Thank you. That link discloses there was at least one instance where OpenAI paid for his time. I will reformulate my question to ask instead if the page is still 100% correct or needs an update?
    - simonw 9mo ago
      It's current. I last modified it in October: https://github.com/simonw/simonwillisonblog/commits/main/templates/about.html https://github.com/simonw/simonwillisonblog/commits/main/tem...
benreesman 9mo ago
It is tempting to be stealthy when you start seeing discontinuous capabilities go from totally random to somewhat predictable. But most of the key stuff is on GitHub. The moats here are around mechanism design and values (to the extent they differ): the frontier labs are doomed in this world, the commons locked up behind paywalls gets hyper mirrored, value accrues in very different places, and it's not a nice orderly exponent from a sci-fi novel. It's nothing like what the talking heads at Davos say, Anthropic aren't in the top five groups I know in terms of being good at it, it'll get written off as fringe until one day it happens in like a day. So why be secretive? You get on the ladder by throwing out Python and JSON and learning lean4, you tie property tests to lean theorems via FFI when you have to, you start building out rfl to pretty printers of proven AST properties. And yeah, the droids run out ahead in little firecracker VMs reading from an effect/coeffect attestation graph and writing back to it. The result is saved, useful results are indexed. Human review is about big picture stuff, human coding is about airtight correctness (and fixing it when it breaks despite your "proof" that had a bug in the axioms). Programming jobs are impacted but not as much as people think: droids do what David Graeber called bullshit jobs for the most part and then they're savants (not polymath geniuses) at a few things: reverse engineering and infosec they'll just run you over, they're fucking going in CIC. This is about formal methods just as much as AI.
falloutx 9mo ago
Yet they have produced almost nothing. You can give $10k to couple of college grads and get a better product.
- deleted 9mo ago
  [deleted]
- mrguyorama 9mo ago
  This idea was the explicit business proposition of my college scholarship program. It included "summer internships" which turned out to be selling undergrads for $30 an hour while paying us $9 an hour. Unfortunately, it doesn't matter how many hours you hire someone who doesn't actually know what they are doing, even though they teach themselves new things sometimes, because writing a few hundred lines of TI-BASIC is not a foundation that you can build a "Turbotax for end of life care planning" service out of. Unfortunately, I was charismatic and good at meetings and sounding smart and confident, so they loved my work even though I never delivered a single thing other than the barest of mockups. I can't help but find terrible similarities in AI slop.

by simonw 9mo ago

enderforth 9mo ago

This right here is where I feel most concerned > If you haven’t spent at least $1,000 on tokens today per human engineer, your software factory has room for improvement Seems to me like if this is true I'm screwed no matter if I want to "embrace" the "AI revolution" or not. No way my manager's going to approve me to blow $1000 a day on tokens, they budgeted $40,000 for our team to explore AI for the entire year. Let alone from a personal perspective I'm screwed because I don't have $1000 a month in the budget to blow on tokens because of pesky things that also demand financial resources like a mortgage and food. At this point it seems like damned if I do, damned if I don't. Feels bad man.

navanchauhan 9mo ago
I think corporate incentives vs personal incentives are slightly different here. As a company trying to experiment in this moment, you should be betting on token cost not being the bottleneck. If the tooling proves valuable, $1k/day per engineer is actually pretty cheap. At home on my personal setup, I haven't even had to move past the cheapest codex/claude code subscription because it fulfills my needs ¯\_(ツ)_/¯. You can also get a lot of mileage out of the higher tiers of these subscriptions before you need to start paying the APIs directly.
- rune-dev 9mo ago
  How is 1k/day cheap? Even for a large company? Takes like this are just baffling to me. For one engineer that is ~260k a year.
  - libraryofbabel 9mo ago
    I do not really agree with the below, but the logic is probably: 1) Engineering investment at companies generally pays off in multiples of what is spent on engineering time. Say you pay 10 engineers $200k / year each and the features those 10 engineers build grow yearly revenue by $10M. That’s a 4x ROI and clearly a good deal. (Of course, this only applies up to some ceiling; not every company has enough TAM to grow as big as Amazon). 2) Giving engineers near-unlimited access to token usage means they can create even more features, in a way that still produces positive ROI per token. This is the part I disagree with most. It’s complicated. You cannot just ship infinite slop and make money. It glosses over massive complexity in how software is delivered and used. 3) Therefore (so the argument goes) you should not cap tokens and should encourage engineers to use as many as possible. Like I said, I don’t agree with this argument. But the key thing here is step 1. Engineering time is an investment to grow revenue. If you really could get positive ROI per token in revenue growth, you should buy infinite tokens until you hit the ceiling of your business. Of course, the real world does not work like this.
    - rune-dev 9mo ago
      Right, I understand of course that AI usage and token costs are an investment (probably even a very good one!). But my point is moreso that saying 1k a day is cheap is ridiculous. Even for a company that expects an ROI on that investment. There’s risks involved and as you said, diminishing returns on software output. I find AI bros view of the economics of AI usage strange. It’s reasonable to me to say you think its a good investment, but to say it’s cheap is a whole different thing.
      - libraryofbabel 9mo ago
        Oh sure. We agree on all you said. I wouldn’t call it cheap either. :) The best you can say is “high cost but positive ROI investment.” Although I don’t think that’s true beyond a certain point either, certainly not outside special cases like small startups with a lot of funding trying to build a product quickly. You can’t just spew tokens about and expect revenue to increase. That said, I do reserve some special scorn for companies that penny-pinch on AI tooling. Any CTO or CEO who thinks a $200/month Claude Max subscription (or equivalent) for each developer is too much money to spent really needs to rethink their whole model of software ROI and costs. You’re often paying your devs >$100k yr and you won’t pay $2k / yr to make them more productive? I understand there are budget and planning cycle constraints blah blah, but… really?!
buster 9mo ago
May be the point is, that the one engineer replaces 10 engineers by using the dark factory which by definition doesn't need humans.
- FeteCommuniste 9mo ago
  The great hope of CEOs everywhere.
- falloutx 9mo ago
  And then he get replaced by a new hire when he asks for a raise.
simonw 9mo ago
Yeah, that's one part of this that didn't sit right with me. I don't think you need to spend anything like that amount of money to get the majority of the value they're describing here. Edit: added a new section to my blog post about this: https://simonwillison.net/2026/Feb/7/software-factory/#wait-1-000-day-per-engineer- https://simonwillison.net/2026/Feb/7/software-factory/#wait-...
- deleted 9mo ago
  [deleted]
- noosphr 9mo ago
  This is the part that feels right to me because agents are idiots. I built a tool that writes (non shit) reports from unstructured data to be used internally by analysts at a trading firm. It cost between $500 to $5000 per day per seat to run. It could have cost a lot more but latency matters in market reports in a way it doesn't for software. I imagine they are burning $1000 per day per seat because they can't afford more.
  - threecheese 9mo ago
    They are idiots, but getting better. Ex: wrote an agent skill to do some read only stuff on a container filesystem. Stupid I know, it’s like a maintainer script that can make recommendations, whatever. Another skill called skill-improver, which tries to reduce skill token usage by finding deterministic patterns in another skill that can be scripted, and writes and packages the script. Putting them together, the container-maintenance thingy improves itself every iteration, validated with automatic testing. It works perfectly about 3/4 of the time, another half of the time it kinda works, and fails spectacularly the rest. It’s only going to get better, and this fit within my Max plan usage while coding other stuff.
    - noosphr 9mo ago
      LLMs are idiots and they will never get better because they have quadratic attention and a limited context window. If the tokens that need to attend to each other are on opposite ends of the code base the only way to do that is by reading in the whole code base and hoping for the best. If you're very lucky you can chunk the code base in such a way that the chunks pairwise fit in your context window and you can extract the relevant tokens hierarchically. If you're not. Well get reading monkey. Agents, md files, etc. are bandaids to hide this fact. They work great until they don't.
reilly3000 9mo ago
My friend works at Shopify and they are 100% all in on AI coding. They let devs spend as much as they want on whatever tool they want. If someone ends up spending a lot of money, they ask them what is going well and please share with others. If you’re not spending they have a different talk with you. As for me, we get Cursor seats at work, and at home I have a GPU, a cheap Chinese coding plan, and a dream.
- r0b05 9mo ago
  > I have a GPU, a cheap Chinese coding plan, and a dream Right in the feels
- dude250711 9mo ago
  > If someone ends up spending a lot of money, they ask them what is going well and please share with others. If you’re not spending they have a different talk with you. Make a "systemctl start tokenspender.service" and share it with the team?
- sergiotapia 9mo ago
  I get $200 a month, I do wish I could get $1000 and stop worrying about trying the latest AI tools.
- zingar 9mo ago
  What results are you getting at home?
mgkimsal 9mo ago
I read that as combined, up to this point in time. You have 20 engineers? If you haven't spent at least $20k up to this point, you've not explored or experienced enough of the ins and outs to know how best to optimize the use of these tools. I didn't read that as you need to be spending $1k/day per engineer. That is an insane number. EDIT: re-reading... it's ambiguous to me. But perhaps they mean per day, every day. This will only hasten the elimination of human developers, which I presume is the point.
christoph 9mo ago
Same. Feels like it goes against the entire “hacker” ethos that brought me here in the first place. That sentence made me actually feel physically sick on initial read as well. Everyday now feels like a day where I have exponentially less & less interest in tech. If all of this AI that’s burning the planet is so incredible, where are the real world tangible improvements? I look around right now and everything in tech, software, internet, etc. has never looked so similar to a dumpster fire of trash.
- zingar 9mo ago
  The biggest rewards for human developers came from building addictive eyeball-getters for adverts so I don’t see how we can expect a very high bar for the results of their replacement AI factories. Real-world and tangible just seem completely out of the picture.
- Garlef 9mo ago
  Maybe think about it like this: A dev is ~1k per day. If the tool gives you 3x then 2x in cost is fine. (The current cost of 1k is "real" and ultimately, even if you tinker on your own, you're paying this in opportunity cost) ((caveats, etc))
- lubujackson 9mo ago
  Yes, exactly this. My biggest issue is how uncurious the approach seems. Setting a "no-look" policy seems cutting edge for two seconds, but prevents any actual learning about how and why things fail when you have all the details. They are just hamstringing their learning. We still need to specify precisely what we want to have built. All we know from this post is what they aren't doing and that they are pissing money on LLMs. I want to know how they maintain control and specificity, share control and state between employees, handle conflicts and errors, manage design and architectural choices, etc. All of this seems fun when hacking out a demo but how in the world does this make sense when there are any outside influences or requirements or context that needs to be considered or workflows that need to be integrated or scaling that needs to occur in a certain way or any of the number of actual concerns that software has when it isn't built in a bubble?
DrewADesign 9mo ago
> No way my manager's going to approve me to blow $1000 a day on tokens, they budgeted $40,000 for our team to explore AI for the entire year. To be fair, I’ll bet many embracing concerning advice like that have never worked for the same company for a full year.

riazrizvi 9mo ago

Until there's something verifiable it's just talk. Talk was cheap. Now talk has become an order of magnitude cheaper since ChatGPT.

belter 9mo ago

Can you make an ethical declaration here, stating whether or not you are being compensated by them? Their page looks to me like a lot of invented jargon and pure narrative. Every technique is just a renamed existing concept. Digital Twin Universe is mocks, Gene Transfusion is reading reference code, Semport is transpilation. The site has zero benchmarks, zero defect rates, zero cost comparisons, zero production outcomes. The only metric offered is "spend more money". Anyone working honestly in this space knows 90% of agent projects are failing. The main page of HN now has three to four posts daily with no substance, just Agentic AI marketing dressed as engineering insight. With Google, Microsoft, and others spending $600 billion over the next year on AI, and panicking to get a return on that Capex....and with them now paying influencers over $600K [1] to manufacture AI enthusiasm to justify this infrastructure spend, I won't engage with any AI thought leadership that lacks a clear disclosure of financial interests and reproducible claims backed by actual data. Show me a real production feature built entirely by agents with full traces, defect rates, and honest failure accounting. Or stop inventing vocabulary and posting vibes charts. [1] - https://news.ycombinator.com/item?id=46925821 https://news.ycombinator.com/item?id=46925821

AstroBen 9mo ago
Simon does have a disclosure on his site about not being compensated for anything: https://simonwillison.net/about/#disclosures https://simonwillison.net/about/#disclosures
- belter 9mo ago
  Thank you. That link discloses there was at least one instance where OpenAI paid for his time. I will reformulate my question to ask instead if the page is still 100% correct or needs an update?
  - simonw 9mo ago
    It's current. I last modified it in October: https://github.com/simonw/simonwillisonblog/commits/main/templates/about.html https://github.com/simonw/simonwillisonblog/commits/main/tem...

benreesman 9mo ago

It is tempting to be stealthy when you start seeing discontinuous capabilities go from totally random to somewhat predictable. But most of the key stuff is on GitHub. The moats here are around mechanism design and values (to the extent they differ): the frontier labs are doomed in this world, the commons locked up behind paywalls gets hyper mirrored, value accrues in very different places, and it's not a nice orderly exponent from a sci-fi novel. It's nothing like what the talking heads at Davos say, Anthropic aren't in the top five groups I know in terms of being good at it, it'll get written off as fringe until one day it happens in like a day. So why be secretive? You get on the ladder by throwing out Python and JSON and learning lean4, you tie property tests to lean theorems via FFI when you have to, you start building out rfl to pretty printers of proven AST properties. And yeah, the droids run out ahead in little firecracker VMs reading from an effect/coeffect attestation graph and writing back to it. The result is saved, useful results are indexed. Human review is about big picture stuff, human coding is about airtight correctness (and fixing it when it breaks despite your "proof" that had a bug in the axioms). Programming jobs are impacted but not as much as people think: droids do what David Graeber called bullshit jobs for the most part and then they're savants (not polymath geniuses) at a few things: reverse engineering and infosec they'll just run you over, they're fucking going in CIC. This is about formal methods just as much as AI.

falloutx 9mo ago

Yet they have produced almost nothing. You can give $10k to couple of college grads and get a better product.

deleted 9mo ago
[deleted]
mrguyorama 9mo ago
This idea was the explicit business proposition of my college scholarship program. It included "summer internships" which turned out to be selling undergrads for $30 an hour while paying us $9 an hour. Unfortunately, it doesn't matter how many hours you hire someone who doesn't actually know what they are doing, even though they teach themselves new things sometimes, because writing a few hundred lines of TI-BASIC is not a foundation that you can build a "Turbotax for end of life care planning" service out of. Unfortunately, I was charismatic and good at meetings and sounding smart and confident, so they loved my work even though I never delivered a single thing other than the barest of mockups. I can't help but find terrible similarities in AI slop.