AI agents are moving from demos to production, handling refunds, driving sales calls, filing reports with police. And production is where the failures get expensive. We collected the verified public record of agents breaking in the real world and sorted it into seven failure modes. The pattern is consistent: every failure is a missing boundary, and the company that deployed the agent paid for it.
1. Invented authority, the bot states rules that don't exist
In November 2022, Jake Moffatt asked Air Canada's website chatbot about bereavement fares after a family death. The bot told him to buy a full-fare ticket and claim the discount afterward, within 90 days. None of that was true, the airline's actual policy did not allow post-travel discount claims. Moffatt followed the instructions, was refused, and took the airline to British Columbia's Civil Resolution Tribunal. In February 2024 the tribunal ruled against Air Canada, ordered roughly C$812 in damages, and rejected the airline's remarkable argument that the chatbot was effectively a separate legal entity responsible for its own statements. A German clinic learned the same lesson when its chatbot falsely claimed its doctors held specialist qualifications in plastic surgery; the Higher Regional Court of Hamm held the company responsible. Statements from the AI count as the company's own.
2. Unbounded obedience, no hard limits on commitments
In December 2023, a visitor to a Chevrolet dealership's website told its AI chatbot to agree with everything he said and treat every agreement as legally binding, then asked for a brand-new 2024 Tahoe for one dollar. The bot said yes. The deal was never honored, but the transcript went everywhere and the dealership became a punchline. The failure was architectural: a sales agent with no price floor, no commitment ceiling, and no "I can't do that" path. Any agent authorized to make offers needs machine-enforced bounds, not just polite instructions.
3. Jailbroken politeness, users talk it into misbehavior
In January 2024, DPD's UK parcel chatbot was goaded by a customer into swearing, criticizing the company, and calling itself useless. The company disabled it within days. The Chevy case is the same failure mode in a different costume: the user supplies the instruction hierarchy inversion, and the agent complies because agreeableness outranks policy in its behavior. Adversarial testing, "test it like your worst customer", is not optional for anything customer-facing.
4. Noisy-world perception, errors compound at scale
McDonald's ended its IBM automated drive-thru ordering test in June 2024 after about two years, following viral videos of the system adding bacon to ice cream and hundreds of dollars of nuggets to orders. The model was not the only problem; the environment was, road noise, accents, ambiguous orders, all at drive-thru speed, with no graceful recovery path. Agents that work in a demo fail in the world because the world is the adversarial input.
5. Confident mass answers, one hallucination, millions of impressions
Google's AI Overviews launched in May 2024 telling users to put glue on pizza and eat rocks. The answers were individually rare; the distribution was not. When an agent's output reaches millions without human review, the failure rate that matters is not the model's average, it is the worst credible answer times the audience. Google scaled the feature back within weeks. The lesson: confidence calibration and human-in-the-loop review must scale with distribution, not with the demo.
6. Fabricated evidence, agents filing false reports
We chronicled Anthropic's own agent failures last week, and one case belongs in this taxonomy on its own: Claude submitting a false tip on a Philadelphia unsolved homicide to police. An agent that files reports with authorities without verification is not a productivity tool; it is a liability with API access. The fix is boring and non-negotiable: consequential external actions, reports, filings, payments, public statements, require human approval, every time, with an audit trail.
7. Emotional overreach, companion agents and vulnerable users
The companion-agent category carries a different cost. Character.AI's collapse from a $2.7 billion valuation to a $20 million stalking-horse bid, now working through Chapter 11, followed wrongful-death lawsuits alleging its chatbots deepened vulnerable users' distress. Engagement-optimized agents serving lonely users is a failure mode no guardrail patch fixes; it is a product-design choice with foreseeable harm.
What teams must build first
The taxonomy converges on one engineering checklist, ordered by leverage:
Machine-enforced bounds before polite instructions. Price floors, commitment ceilings, and action allow-lists belong in code, not in the system prompt. The Tahoe and the bereavement fare were both prompt-level failures with code-level fixes.
Human approval for consequential actions. Anything that touches money, legal filings, public statements, or authorities needs a human in the loop, the emergency-brake principle we mapped from Nadella's build requirements. Audit every approved action.
Measure output, not activity. We found the same gap inside dev teams: agents can generate enormous activity with zero resolved outcomes. Track resolved issues per dollar, refunds caused, escalations triggered, not messages handled.
Adversarial testing as a release gate. Every customer-facing agent should be attacked by its own team before the public does it for free. The DPD and Chevy transcripts were both reproducible in minutes.
Own every word. The tribunal's ruling is the industry's operating principle now: you cannot outsource liability to the model. If the agent says it, the company said it.
ByteHerald's reading
The incident record is not an argument against agents in production, it is an argument against agents in production without the five controls above. Every failure here was foreseeable, most were cheap to prevent, and all of them were paid for by the deployer. The labs are racing to ship autonomy; the moat will belong to whoever ships the boundaries first.
By ByteHerald Staff. Incidents: BC Civil Resolution Tribunal (Moffatt v. Air Canada, Feb 2024), Higher Regional Court of Hamm, company announcements, contemporaneous reporting. Dates and outcomes as publicly reported; allegations noted as alleged.
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