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Hallucination

Also known as: confabulation

Definition

Output that is fluent, confident and false. Language models generate plausible continuations rather than retrieving verified facts, so a missing fact is filled with something that looks like one.

Hallucination is not a bug that gets patched; it is a property of how the systems work. It is managed rather than eliminated — by grounding output in retrieved sources, by constraining what the model is asked to produce, and by having a person check anything consequential.

The commercially dangerous cases in marketing are invented statistics, invented product specifications, invented prices and invented case-study outcomes. Any of those in published material is a credibility problem at best and a regulatory one at worst. Claims about a product should be looked up from a structured source, never generated.

More in AI

Agentic workflow

A process where an AI system is given a goal rather than a script, and chooses its own sequence of tool calls to reach it. Distinguished from automation by being non-deterministic: the same input can produce a different route each run.

AI agent

An AI agent is a system that pursues a goal across multiple steps using tools — reading data, calling APIs, updating records — rather than producing a single response to a single prompt.

AI automation ROI

The payback calculation for an automation: hours recovered multiplied by fully loaded hourly cost, against build plus running cost. Frequency dominates the result — the same build against a process running twice a month rarely pays back at all.

AI observability

Logging and monitoring for AI systems: what went in, what came out, which tools were called, what it cost, and how often a human overrode it. Without it, a misbehaving automation is undiagnosable.

AI readiness

Whether a business has the process documentation, data quality and decision ownership for AI to add value. Readiness is mostly organisational: the constraint is almost never model capability.

Automation debt

The accumulated cost of automations nobody owns: undocumented flows, forgotten triggers, and scripts that break silently when an upstream field is renamed. The AI-era version of technical debt.

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