Claude also believes it knows how AWS' KMS works, quite confidently, while getting things wrong. I have a separate "this is how KMS replication actually works" file just to deal with its misconceptions.
For gemini, I typically use it to query information from large corpuses, but it often web searches and hallucinates instead of reading the actual corpus. On a book series, it will hallucinate chapters and events which, while reasonable and plausible, do not exist. "Go look at the files and see if your reference is correct" shows that it's not correct, and it's a mandatory step. But that doesn't prevent hallucination, but makes sure you catch it after the fact, just like a method in a class that doesn't exist gets found out by the compiler. The LLM still hallucinated it.
I was trying to understand a game I've been playing, The Last Spell. I asked it for a tier list of omens -- which ones the community considers most important. At least a few of the names it posts are hallucinated ("omen of the sun" does not exist, and the omens that give extra gold are "savings," "fortune," and "great wealth").
Obviously not a critical use case but issues like this do keep me on my toes regarding whether the thing is working at all. I should ask 3.5 flash to do the same job. (I did try and it once again hallucinated the omen names and some of the effects.)
The fix is easy enough though, a line in my global AGENTS.md instructing agents to search/ask for documentation before working on API integrations.
```
Build a Nango sync that stores Figma projects.
Integration ID: figma
Connection ID for dry run: my-figma-connection
Frequency: every hour
Metadata: team_id
Records: Project with id, name, last_modified
API reference: https://www.figma.com/developers/api#projects-endpoints
```
Note: You do need a Nango account and the Nango Skill installed before it could work.
Two of the three strip titles are hallucinated and two of the three strips are bad examples. Haley is mute in strip 403 and does nothing. Strip 578 is the start of the arc that shows the behavior Gemini is talking about, but has things going wrong so it's not a good example either.
Claude picks a good strip but also hallucinates the strip title: https://claude.ai/share/56be379d-c3da-443e-b60f-2d33c374eba8
...my chats are all pretty long and involve personal conversations, or I've deleted them. It's a lot to ask for someone to post receipts. The number of complaints is enough data.
No matter how big the model is there will be edge cases where it has no data or is out of date. In these cases it just makes stuff up. You can detect it yourself by looking for words like usually or often when it states facts, e.g. "the mall often has a Starbucks." I asked it about a Genshin Impact character released in June 2025 and it consistently interpreted the name (Aino) as my player character because Aino wasn't in its data.
Honestly I'm surprised your haven't encountered it if you're using it more than casually. Pro is much better but not perfect.
Also, prompts that reliably produce hallucinations is kind of a hard ask. It's inconsistent. One day the LLM I work with quotes verbatim from the PCIe spec and it's super helpful. The next day it gives me wrong information and when I ask it what section of the spec that information comes from it just makes up a section number
And when I say all the time, I mean it, and this is for Opus 4.7 Adaptive.
I often have to say, please do searches and cite sources, as if it doesn't it will confidently give me wrong or outdated information.
If you're often asking questions about a topic that's not in your specialist knowledge you won't notice them.
If you aren't paying attention it can spend a long time (and a lot of tokens) spinning in that loop. Sometimes there might be more than two approaches in the loop, which makes it even harder to see that it's repeating itself in a loop. It's pretty frustrating to see it working away productively (so you think) for 20 minutes or so only to finally notice what's going on