BREAKING: LLM “reasoning” continues to be deeply flawed
We recorded 4 claims from this post. 2 were checked against evidence. 2 can’t be checked. 2 more are held. Read the post at its source.
Claims from this post (4)
In the order they appear in the post. Each quotation is the speaker’s words in this post. A label such as “Supported” or “Can’t be checked” is the claim’s current assessment; its page has the evidence and the reasons.
Assessment: SupportedSaid
Observation
“LLMs still hallucinate and continue to make boneheaded errors.”
Our reading: As of February 2026, LLMs still hallucinate and still make boneheaded errors.
No horizon Evidence as of
Limitation: Vectara measures faithfulness in summaries only; it does not cover other kinds of hallucination.
Assessment: SupportedSaid
Observation
“And reasoning is still one of the core issues.”
Our reading: As of February 2026, reasoning is still one of the core unsolved problems for LLMs.
No horizon Evidence as of
Limitation: 'Core issue' is qualitative; no metric ranks reasoning failures against other limitations.
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“If you want a full idea of how far we have left to go (and, implicitly, why LLMs aren’t the right answer) read it.”
Our reading: The Caltech/Stanford review of LLM reasoning failures shows how far AI still has to go and, implicitly, why LLMs aren't the right answer.
No horizon
Qualifier: implicitly, as conveyed by the review
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Silicon Valley can do one of two things. It can continue to dismiss critics and criticism, praying for magical solutions, or it can face reality and start focusing on alternatives to LLMs.”
Our reading: The AI industry should face reality and start focusing on alternatives to LLMs instead of dismissing critics.
No horizon
Held from this post (2)
These records did not pass every check, so nothing about them is published. Held is not a finding.
- The two reviews reached different assessments. Our reading, not assessed: As of February 2026, AGI has not arrived, despite AI industry leaders repeating the promise year after year.
- The record does not meet the current rules. Our reading, not assessed: The latest deep learning systems, including those marketed as reasoning models, still have major problems with reasoning, as a Caltech/Stanford review shows.