REVIEWS / GENERAL / OWNER INSIGHTS
🦉 WE READ 584 OWNER COMMENTS
Hallucinate: what owners actually say
Users are deeply frustrated by AI tools that hallucinate, deceive, and underdeliver — but a subset of developers find real value when they learn to work around the flaws.
What owners complain about
- Deceptive AI customer support COMMON
Cursor deployed an AI support bot named 'Sam' that was not labeled as AI, leading users to believe they were talking to a human. Users describe this as intentionally deceptive, and the company then attempted to 'control the narrative on reddit' when called out.
- Hallucinated outputs can't be trusted COMMON
LLMs generate fictitious information — fake legal cases and citations, wrong code, fabricated facts. The core problem users identify is that 'you don't know which 5% is wrong,' making output unreliable without thorough verification.
- Visual quality degradation SOME
Referring to Nvidia's DLSS/AI upscaling, users call it a 'slop filter' with ridiculous ghosting. The CEO's defense of the technology is met with mockery and accusations of justifying sunk R&D costs.
- AI forced into unwanted products SOME
Users compare AI proliferation to 'the reverse headphone jack' — shoved into everything whether people want it or not. Phone AI features are called 'bullshit' and not worth upgrading for.
- Account and credit abuse systems FEW
Cursor's free-credits-without-credit-card model led to abuse, forcing changes to how their VSCode fork handles user identification, which degraded the experience for legitimate users.
What owners love
- Daily coding utility
Some developers love Cursor and use it daily; entire companies are building workflows and MCP tools on top of it, embedding 'Active Curation' into their development process.
- Unblocks stuck projects
One user described being stuck on a long-term code project for various reasons; after a friend explained how to properly talk to the LLM, they made genuine progress by changing their approach.
- Acceptable imperfection
Users compare AI to IDE tab completion (wrong >5% of the time but still useful) and calculators — tools that are imperfect but valuable when you understand their failure modes.
Surprising patterns
- Lawyers have been disbarred and faced contempt charges for submitting unvetted AI-generated legal filings with fictitious cases — users unanimously support harsh punishment for this.
- Stack traces are now appearing with notes attributing issues to AI-generated code, marking what may be the first documentation of AI's footprint in bug reports.
- Users are actively developing adversarial techniques to mess with AI support bots, including prompt injections that force bots to give proper answers or reveal their nature.
- Even enthusiastic AI users explicitly warn that you must verify everything — the tolerance for errors exists only when users can identify and correct them, not when errors are hidden.
WHO SHOULD SKIP IT
Anyone who needs guaranteed accurate output — especially legal professionals, support staff requiring accountability, and users who can't or won't manually verify every claim, citation, or code block the tool produces.
Synthesised from 584 real owner comments across 5 platforms. Every point is grounded in the comments — no marketing, no AI guessing. How we do it →