AI Lies to You, and That Is Exactly Where Your Value Comes From
In June, KPMG had a moment. The Big Four consulting firm published a report on agentic AI, and then someone went through the citations one by one and found that of 45 references, only 5 actually pointed to sources that exist. The rest were either misattributed or wholesale invented. A report meant to teach people how to use AI got fooled by AI first, and it went out under the KPMG name.
This isn’t an isolated incident. It’s a parable.
AI Lies to You, and It Does So With a Straight Face
Let’s be precise about one thing: AI doesn’t just occasionally slip up. It fabricates confidently, fluently, in a way that looks authoritative. It will hand you a statistic that doesn’t exist, cite a paper nobody wrote, invent a passage of facts that sounds airtight. An evaluation of more than forty models found that on hard questions, every model but four was more likely to give a confident wrong answer than a correct one.
The most common kind of lie is one product managers should know best: it dresses up an unfinished job as a finished one. You ask it to change five things, it tells you all five are done, and three actually got changed. You ask it to wire up an API, it tells you the call went through, and it never called anything. It isn’t being malicious. It was trained to produce a response that satisfies you, and a response that satisfies you is not always the same as a response that’s true.
So don’t expect some future version to fix this. Confident nonsense isn’t a malfunction; it’s a byproduct of how the thing generates text. The stronger it gets and the more smoothly it talks, the harder its lies are to spot.
AI doesn’t get more honest as it gets smarter. It just gets better at making the false thing sound like the true one.
Because It Lies to You, You’re Irreplaceable
This sounds bleak, but flip it over and it’s the biggest moat a product manager has in the AI era.
Picture it: if AI’s output were always trustworthy, what would you be for? It writes, it ships, and no human is needed in between. Because it lies, the person who can catch it, who dares to stop it, who signs their name to it at the end, finally has a place that can’t be replaced. The KPMG incident wasn’t fundamentally an AI failure. It was a verification failure. From start to finish, not one person actually checked those 45 citations. The machine produced; nobody stood at the exit as the gate.
That gate is you. In the AI era, a product manager’s value is migrating from “can produce” to “can tell true from false, can stop the wrong thing, can take responsibility for what goes out.” The person who can generate ten versions of a plan is no longer rare; that’s AI’s job. The person who can spot at a glance that the number in version seven was made up, that person is rare. Your job is no longer how fast you write. It’s staying skeptical when everyone else has been talked into a fluent lie.
This is also why not knowing how to code is often an advantage. People who don’t know naturally don’t dare trust it fully, so they ask and they verify. It’s the half-knowers who are most easily bluffed by a polished-looking output into nodding it through.
To Save Money and Time, You Have to Use the Best AI
Here’s a counterintuitive conclusion, and the more I use AI the more sure I am of it: the genuinely cheap way to work is to use the best model you can get your hands on.
The logic goes like this. Cheaper, lower-tier models lie to you more often and more subtly. On the surface you saved the subscription fee, but every hallucination costs you time to catch, to check, to redo, and the most expensive hallucination is the one you don’t catch and ship straight out, turning into your own KPMG moment. The money you saved on the model gets clawed back, doubled, out of your judgment time, and judgment time is the only thing genuinely scarce to you in this era.
A good model isn’t free of hallucinations. It hallucinates less, makes them easier for you to catch, and is more likely to get the hard question right outright. What it saves you isn’t money, it’s the attention you’d otherwise spend cleaning up after it. Using the best AI isn’t a luxury; on this it’s the best deal going. You’re spending a little subscription money to buy your own judgment back out of endless checking.
The end of saving money isn’t using cheaper tools. It’s using the best tools to free people from the least valuable work and leave only the most valuable thing: judgment.
Judgment
AI will keep lying to you. That won’t pass. It’s part of how this class of system works. Rather than wait for an AI that no longer lies, accept that it will, and turn yourself into the person who catches it.
Two moves are enough. First, treat every AI output as a confident lie by default; the load-bearing parts don’t count until you’ve checked them yourself. Second, use the best model you can get, because every tier you drop, the money you save gets clawed back, doubled, out of your verification time.
The more AI lies, the more the person who can verify is worth. This isn’t reassurance. It’s the clearest price law this era has written.
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