Bringing that back to tech debt: a simple kind of high-interest short-term debt would be committing code without tests or documentation. Yay, it works, ship it! And truthfully, maybe you should, because the revenue (and customer feedback) you get from shipping fast can outweigh how much more bug-prone you made the code in the short term.
But like all high-interest debt, you should plan to pay it back fast. Tech debt generally manifests as a slowdown in your development velocity (ie. overhead on everything else you do), which means fewer features launched in the medium-long term, which means less revenue and customer feedback.
[...]
Bankruptcy
The tech bankruptcy metaphor is an easy one: if refinancing doesn't work and your tech debt continues to spiral downward, sooner or later your finances will follow. When you run out of money you declare bankruptcy; what's interesting is your tech debt disappears at the same time your financial debt does.
This is a really important point. You can incur all the tech debt in the world, and while your company is still operating, you at least have some chance of someday paying it back. When your company finally dies, you will find yourself off the hook; the tech debt never needs to be repaid.
Okay, for those of us grinding away at code all day, perhaps that sounds perversely refreshing. But it explains lots of corporate behaviour. The more desperate a company gets, the less they care about tech debt.
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this post was submitted on 17 Jul 2026
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Brilliant and nuanced description.
It also makes me pause when thinking about AI. AI-generated code, as it is commercially used, undoubtly increases technical debt. Companies want to use it because they see it as an advantage. But it can also lead quickly to technical debt bankruptcy. Which will likely be the outcome given the bone-headed way how many companies actually use AI.
But what drives them?
A lot of AI adoption seems to be driven by two things: Fear and greed. Fear, of becoming obsolete among the competition. Greed to not miss out on a perceived bonanza. This is not necessarily rational. It might be the cause why all these purported gains in speed are rarely actually measured.
But as Apenwarr (Avery Pennarun) points out, companies often behave more rational than it seems. Specifically, as he writes, they accept an unsustainable level of technical debt when it seems that they cannot compete any more. That makes actually sense: Why polishing a shiny, immacculate, well-designed code base, when you never have the chance to re-earn the money that you did spent for that? (People do the same: An aging person living in a run-down house with broken roof and heating might not want to invest in repairs or installing a heat pump, because that person will not see the gains from this investment - possibly their children, but will they keep the house?).
But how does all this match up with technical debt and AI? Are tech companies simply giving up business? Are they completely unaware on the level of technical debt it creates? Why does this happen?
This is a great description, I have not heard of the technical bankruptcy metaphor.
I don't think companies outside of Anthropic and OpenAI are acting rationally though. The whiplash policy decisions of CEOs and CFOs about workplace AI use, first being ecstatically for it, then reversing themselves after weeks/months, and only now asking where their IP went. I think it's more likely they were unaware of the risks, not just technical debt but also the financial cost, privacy concerns and data protection, and the addiction aspect, making your workforce dependent on an external knowledge model that can be changed, upgraded, turned off entirely without your control, and never considered whether openai was reliable or sustainable. That's not even getting into whether the model itself is reliable or not: the power structure inherent in serving chatbots of any kind is going to have these lock-in and privacy concerns.
Business leaders are slowly learning about the cost and data concerns, but I don't think they are quite done being irrational yet. It's obvious technical debt is not a concern to them, and hasn't been even from the before time. Ed Zitron goes into this more, but the entire tech sector is inflated with debt, and 'zombie unicorns' are becoming more common, companies with impossible expectations placed on them to grow revenue. That might explain the wreckless decisions to incorporate ai, but I still don't think it was rational, other than in the sense that a lot of them must feel hopeless and are just grasping at straws.
The entire software industry will have a reckoning soon. AI maybe sped up its arrival but I don't think sustainable business practices have been in vogue in silicon valley for decades.
He also describes the analogon to financial restructuring of debt (giving up some products or features because you can't support them any more) and the massive costs in terms of trust that bankruptcy has as a consequence.
That could be the case.
There is also the situation with tons of AI filtered CVEs. In theory, the EU cyber resilency directive should address that .... but it is not possible to address literally decades of technical debt with processes that only optimized for short-term revenue. Might turn out that some smart home technology was not so smart, and smart factory tech neither.
iiot is an overlooked timebomb of incompetence.
true.