Don't classify. Hallucinate! | SpinGraph: Innovation framing
description: SpinGraph analysis of Simon Willison's Weblog's Don't classify. Hallucinate! story: innovation framing, The Hype, Spin Score 40%, moderate AI repetition risk.
canonical: https://stuffthatspins.com/spin/dont-classify-hallucinate
markdown: https://stuffthatspins.com/spin/dont-classify-hallucinate.md
keywords: hallucination
keywords: vector embeddings
keywords: tagging
keywords: The Hype
keywords: narrative intelligence
published: 2026-08-14T21:54:35+00:00
modified: 2026-08-16T04:03:32.531889+00:00

Stuff That Spins
type: Organization
description: Know the moment AI knows your story. Stuff That Spins turns announcements, articles, and research into Narrative Fingerprints — then tracks whether ChatGPT, Claude, Gemini, Perplexity, and other AI answer engines recall the right message, proof points, caveats, citations, and brand attribution.

Don't classify. Hallucinate!
type: NewsArticle
alternative headline: Don't classify. Hallucinate! | SpinGraph: Innovation framing
description: SpinGraph analysis of Simon Willison's Weblog's Don't classify. Hallucinate! story: innovation framing, The Hype, Spin Score 40%, moderate AI repetition risk.
date published: 2026-08-14T21:54:35+00:00
date modified: 2026-08-16T04:03:32.531889+00:00
main entity of page: https://stuffthatspins.com/spin/dont-classify-hallucinate
is accessible for free: true
language: en-US
article section: developer
keywords: hallucination, vector embeddings, tagging, LLM prompting, developer workflow
author: Simon Willison's Weblog
publisher: Stuff That Spins
citation: https://simonwillison.net/2026/Aug/14/dont-classify-hallucinate/
about: hallucination
about: vector embeddings
about: tagging
about: LLM prompting
about: developer workflow
mentions: Simon Willison's Weblog
abstract: Uses LLMs not for classification but for generative tag suggestion ('hallucination') Matches generated tags to existing vocabulary via vector embeddings, not exact string match Solves real developer pain point: scaling metadata curation across 1,856 existing tags without API cost or prompt engineering overload

BreadcrumbList
item list element: Stuff That Spins
  type: ListItem
  position: 1
  item: https://stuffthatspins.com/
item list element: Don't classify. Hallucinate!
  type: ListItem
  position: 2
  item: https://stuffthatspins.com/spin/dont-classify-hallucinate

Spin Analysis: innovation framing
type: AnalysisNewsArticle
description: Emphasizes cleverness and novelty of the approach while minimizing discussion of failure modes (e.g., hallucinated tags too semantically distant for embedding retrieval to recover, or domain drift between generated and corpus tags).
about: innovation framing
  type: DefinedTerm
  description: Developer-first, pragmatic innovation — leveraging model behavior rather than fighting it.
  term code: The Hype
additional property: Spin Score
  type: PropertyValue
  value: 40
  unit text: percent
additional property: Narrative Risk
  type: PropertyValue
  value: low
additional property: AI Repetition Risk
  type: PropertyValue
  value: moderate
additional property: Likely AI Summary
  type: PropertyValue
  value: A developer uses LLM hallucination plus vector search to auto-tag blog posts — turning a flaw into a feature.
additional property: Narrative Frame
  type: PropertyValue
  value: Developer-first, pragmatic innovation — leveraging model behavior rather than fighting it.
additional property: Missing Context
  type: PropertyValue
  value: No benchmarking against baseline methods (e.g., zero-shot classification, few-shot classification, or traditional NLP taggers); No discussion of latency, token cost, or embedding index maintenance overhead
additional property: How the Spin Works
  type: PropertyValue
  value: The story uses titles, institutions, awards, rankings, partners, experts, or official language to make the subject feel more credible. Watch for loaded terms such as hallucinate, neat solution, novel. The distribution reads as editorial reporting. A pressure point: No benchmarking against baseline methods (e.g., zero-shot classification, few-shot classification, or traditional NLP taggers).
author: Stuff That Spins
is part of: Don't classify. Hallucinate!

Extracted Claims
type: ItemList
item list element: ListItem
  position: 1
  item: Claim
    text: Tell the model to output tags without any details of the existing vocabulary, then use vector embeddings against the existing corpus to find the concrete tags that are closest to the ones the model imagined might fit.
    appearance: Doug Turnbull has a neat solution. Tell the model to output tags without any details of the existing vocabulary, then use vector embeddings against the existing corpus to find the concrete tags that are closest to the ones the model imagined might fit!
    author: Simon Willison's Weblog

Key Statistics
type: Dataset
description: Extracted statistics from the source narrative
variable measured: existing tags
  type: PropertyValue
  value: 1,856
  description: Author's personal blog tag count, cited as reason conventional classification fails