Glossary Definition

Hallucination

Term Definition

A phenomenon where an AI model confidently generates factual errors, fabricated references, or unverified data assertions absent from its true context.

Related Blueprints

No active workflows are currently tagged with this glossary term. Run the playbook enrichment tool to auto-link blueprints.

Featured In Blog Posts

Sep 12, 2026

GPT-6 Astra Explained: Features, Capabilities, Benchmarks, Pricing

On September 3, 2026, OpenAI released GPT-6 Astra — the first model it rates "Critical" for cybersecurity capability under its own safety framework, and a model it markets as its most capable, most aligned release to date. Here's what's officially confirmed, what independent evaluators found, and how it actually compares to Claude and Gemini.

Oct 13, 2026

Using AI for Legal Document Review: Benefits and Limitations

A single merger due-diligence project can involve reviewing tens of thousands of contracts for one clause. A single e-discovery matter can involve millions of emails. AI has made both jobs faster and cheaper — but it has also produced fabricated case citations, sanctioned attorneys, and quietly missed the one clause that mattered. This is a practical look at what AI document review actually does well, where it breaks, and how to build a workflow that gets the benefit without the exposure.

Sep 9, 2026

Using AI to Summarize Meetings: Tools, Prompts, and Pitfalls

The average knowledge worker spends nearly a fifth of the workweek in meetings, and most of what's said in them evaporates within days. AI-generated meeting summaries promise to fix that — but only if you pick the right tool, write the right prompt, and know exactly where these systems quietly get things wrong.

Aug 7, 2026

How AI Is Changing Healthcare Diagnostics and Patient Care

More than 1,300 AI medical devices now have regulatory clearance. What's less often reported is exactly where those tools are actually changing care today — and where the evidence still falls short.

Aug 25, 2026

What Multi-Agent Collaboration Means for the Future of Work

We spent three years asking what a single AI could do for us. The more consequential question — the one reshaping how organisations are actually built in 2026 — is what a coordinated team of AI agents can do together.

We use cookies

We use cookies to improve your experience and analyze our traffic. By clicking "Accept", you consent to our use of cookies. Privacy Policy