Why Lazy Technical Writers, Product Managers, and Greedy CEOs Love AI (And Why Customers Eventually Pay the Price)
There is a new universal solvent in tech. Not one that dissolves technical debt, organizational dysfunction, or bad incentives—but one that dissolves accountability. It’s called “AI,” and everyone loves it for wildly different reasons.
Some love it because it saves time. Others because it saves money. And a few because it provides the illusion of progress without the inconvenience of actually improving anything.
Let’s start with the most enthusiastic adopters.
Why Lazy Technical Writers Love AI
Good technical writing is hard. It requires understanding the product, understanding the user, anticipating confusion, and making brutal editorial decisions about what not to say. It requires interviews, testing, rewrites, and—worst of all—thinking.
AI changes that.
Now documentation can be:
- Generated from API comments no human ever read
- Auto-expanded into 40-page guides nobody asked for
- Perfectly grammatical and completely unhelpful
A lazy technical writer can now “ship” documentation without ever running the software. Need a troubleshooting section? Prompt it. Need a migration guide? Prompt it. Need six variations of the same paragraph explaining nothing? You’re in luck.
Real example:
Plenty of modern SaaS products now ship AI-generated docs that confidently explain features that don’t exist, settings that don’t work, or workflows that were removed three releases ago. The text is fluent, consistent, and wrong. But it looks professional, which is often all that’s required to check the box.
The irony? AI doesn’t replace good technical writers. It replaces curious ones.
Why Lazy Product Managers Love AI
Product management is supposed to be about tradeoffs, user pain, and saying “no.” Unfortunately, those things don’t show up well in slide decks.
AI fixes that by producing:
- Roadmaps with infinite features
- PRDs that sound decisive but commit to nothing
- “User insights” synthesized from no real users at all
Instead of talking to customers, PMs can now prompt an AI to simulate them. Instead of prioritizing, they can generate ten “options” and call it strategy.
Real example:
Teams now ship features justified by “AI-generated user personas” that no one has validated. These personas love every feature equally, never churn, and always want more complexity. Shockingly convenient.
AI lets weak PMs avoid the most important part of their job: choosing.
Why Greedy CEOs Love AI
Now we get to the real romance.
CEOs don’t love AI because it’s smart. They love it because it’s:
- Headcount-neutral (or negative)
- Vaguely magical to investors
- A perfect excuse to freeze hiring
AI turns cost-cutting into innovation theater.
Layoffs become “AI-driven efficiency.” Support degradation becomes “self-service empowerment.” Missing features become “coming soon with AI.”
Real example:
Multiple companies have replaced human customer support with AI chatbots that cannot solve real problems—but do dramatically reduce support staff costs. When customers complain, leadership points to “early-stage optimization” and investor decks nod approvingly.
AI allows executives to extract short-term value while postponing long-term consequences. By the time customers leave, the quarterly numbers have already been reported.
The Shared Fantasy: AI as Responsibility Laundering
Across roles, AI serves the same psychological function: it moves responsibility somewhere else.
- Docs are bad? The model generated them.
- The feature doesn’t make sense? That’s what the AI recommended.
- Customers are confused? They should ask the chatbot.
AI becomes a buffer between decision-makers and outcomes. Nobody owns the result because nobody “wrote” it.
This is not automation. It’s abdication.
Why Customers Lose in the End
Customers don’t care who generated the documentation. They care whether it helps.
They don’t care whether the roadmap was AI-assisted. They care whether the product solves their problem.
And AI-heavy organizations increasingly optimize for output volume instead of outcome quality.
Here’s what customers actually experience:
- More words, less clarity
- More features, less usability
- More “support,” fewer solutions
When everything is generated, nothing is curated. When everything is possible, nothing is intentional.
The result is software that talks a lot and listens very little.
The Quiet Truth Nobody Puts in the Pitch Deck
AI is not making products better by default. It’s making it easier to ship mediocrity faster.
Used well, AI can:
- Accelerate drafts
- Surface patterns
- Reduce grunt work
Used lazily, it amplifies every existing dysfunction:
- Bad strategy becomes faster bad strategy
- Poor documentation becomes louder poor documentation
- Greed becomes scalable
Customers eventually notice. They always do. They just notice after the bonuses are paid.
The Punchline
AI didn’t create lazy writers, weak PMs, or greedy CEOs. It just finally gave them a tool that works at their level of ambition.
The tragedy isn’t that AI replaces humans.
It’s that it enables people who stopped caring to keep shipping anyway.
And the customer? They get a chatbot apology, a broken workflow, and a survey asking how likely they are to recommend it.
