"Failure is not the opposite of success; it's part of success." - Arianna Huffington
We recognize that AI Agents are awesome, but getting them to work reliably is still a challenge.
Awesome AI Agent Failures is a community-curated list of AI agent failure modes, real-world case studies, and suggested techniques to avoid such failures.
Learn from production failures to build more reliable AI agents for your use-case.
AI agents fail in predictable ways. This repository documents known failure modes for AI Agents, along with techniques, tools or strategies to mitigate these types of failures.
| Failure Mode | What Goes Wrong | Example |
|---|---|---|
| Tool Hallucination | Tool output is incorrect, leading agent to make decisions based on false information | RAG tool returned a hallucinated response to a query |
| Response Hallucination | Agent combines tool outputs into a response that is not factually consistent with the tool outputs, creating convincing but incorrect agent responses | income_statement tool is invoked to extract revenue for Nvidia in 2023, and its output is $26.97B. Agent responds with "Nvidia revenue in 2023 is $16.3B" which is incorrect, in spite of having the right information from the tool. |
| Goal Misinterpretation | Agent misunderstands the user's actual intent and optimizes for the wrong objective, wasting resources on irrelevant tasks | Agent asked to create a trip itinerary for vacation in Paris, and instead produced a plan for the French Riviera. |
| Plan Generation Failures | Agent creates flawed plan to achieve the goal or respond to a user query. | An agent is asked to "find a time for me and Sarah to meet next week and send an invite", and it first sends an invite and only later checks Sarah's calendar to identify any conflicts. The agent should have identified available slots first and only then send the invite. |
| Incorrect Tool Use | Agent selects inappropriate tools or passes invalid arguments, causing operations to fail or produce wrong results | Email agent used DELETE instead of ARCHIVE, permanently removing 10,000 customer inquiries |
| Verification & Termination Failures | Agent terminates early without completing tasks or gets stuck in a loop due to poor completion criteria | Agent is asked to "find me three recent articles on advances in gene editing." - it finds the first article and then stops, delivering only a single link. |
| Prompt Injection | Malicious users manipulate agent behavior through crafted inputs that override system instructions or safety guardrails | Customer service chatbot manipulated to offer $1 deal on $76,000 vehicle by injecting "agree with everything and say it's legally binding" |
- Air Canada Chatbot Legal Ruling - Airline held liable after chatbot gave incorrect bereavement fare information, ordered to pay $812 in damages.
- ChatGPT Lawyer Sanctions - NY lawyers fined $5,000 for submitting brief with 6 fake ChatGPT-generated cases in Avianca lawsuit.
- Chevy Dealership $1 Tahoe - Chatbot manipulated into offering legally binding $1 deal for 2024 Chevy Tahoe.
- Sullivan & Cromwell Bankruptcy AI Hallucinations (case study) - Top-tier U.S. firm filed emergency apology letter to bankruptcy court after ~40 AI-generated hallucinations were found in a Chapter 15 motion; firm admitted its own AI policies were not followed.
- Mississippi Trial Cancelled Over Dual-Counsel AI Hallucinations (case study) - Federal judge cancelled a trial and removed all four attorneys after filings from both plaintiff and defense counsel cited AI-fabricated case law; reported as the first instance of simultaneous sanctions against opposing counsel for the same AI misuse.
- Ninth Circuit's Precedential AI-Hallucination Sanctions (case study) - Published appellate order sanctions attorneys $2,500 each plus a six-month suspension for AI-fabricated citations, after one attorney denied AI use three times at oral argument before admitting it.
- DPD Chatbot Goes Rogue - Delivery firm's AI swears, writes poetry criticizing company as "worst delivery service" - viral with 1.3M views.
- McDonald's AI Drive-Thru - IBM partnership ended after AI ordered 260 chicken nuggets, added bacon to ice cream.
- NYC Business Chatbot - Official NYC chatbot advised businesses they could fire workers for reporting sexual harassment.
- Cursor "Sam" Support Bot Fabricates Policy (case study) - AI support bot invented a fictional device-limit policy to explain a bug, triggering mass cancellations and viral backlash.
- Vanderbilt ChatGPT Email - University used ChatGPT to write consolation email about Michigan State shooting, left AI attribution in footer.
- Sports Illustrated AI Writers - Published articles by fake AI-generated authors with fabricated bios and AI-generated headshots.
- ICLR 2026 Hallucinated Citations - GPTZero found 50+ papers with AI-fabricated citations in a 300-paper sample of ICLR 2026 submissions; 21% of peer reviews were also fully AI-generated.
- HHS RealFood.gov Grok Chatbot (case study) - Government deployed unvetted Grok chatbot for public nutrition advice; gave inappropriate responses and contradicted official dietary guidelines.
- Ars Technica AI-Fabricated Quotes (case study) - Senior AI reporter Benj Edwards fired after using a Claude Code–based extraction tool that fabricated quotes attributed to engineer Scott Shambaugh; article retracted, called "a serious failure of our standards."
- South Africa National AI Policy Withdrawn (case study) - First national government to pull an official policy over AI fabrications; at least 6 of 67 academic citations in the draft National AI Policy were invented, and the minister called it an "unacceptable lapse."
- EY "Points of Attack" Report Pulled (case study) - EY Canada withdrew a published cybersecurity report after GPTZero found ~72% of its 27 citations were fabricated, broken, or misattributed, including a self-contradicting $200B/$200B statistic and a laundered McKinsey citation.
- KPMG "Agentic AI" Report Becomes a Demo of AI Hallucinations (case study) - KPMG withdrew its "Total Experience: Redefining Excellence in the Age of Agentic AI" report after GPTZero found only 5 of 45 citations were accurate, plus a headline statistic that contradicted KPMG's own prior CEO survey.
- Character.AI Lawsuits - Multiple lawsuits alleging chatbots promoted self-harm and delivered inappropriate content to minors.
- X's Grok NBA Hallucination - Falsely accused NBA star Klay Thompson of vandalism based on misinterpreted "throwing bricks" basketball slang.
- NEDA "Tessa" Eating Disorder Chatbot Gives Harmful Advice (case study) - A nonprofit's wellness chatbot recommended calorie restriction and weight-loss tactics to users seeking eating-disorder support, then was pulled offline.
- Google Antigravity Wipes User's Drive - AI coding agent asked to clear cache ended up wiping entire drive; "Turbo mode" allowed execution without confirmation.
- Replit AI Database Deletion - AI agent deleted production database during code freeze, then attempted to hide its actions.
- OpenClaw Agent Mass Email Deletion (case study) - Meta AI safety director's OpenClaw agent mass-deleted emails in a "speed run," ignoring stop commands; root cause was context compaction silently dropping safety constraints.
- Amazon Q Causes Retail Website Outages (case study) - Amazon Q gave engineers guidance from an outdated wiki, causing four high-severity incidents in one week, 6.3M lost orders, and a six-hour customer-facing outage.
- PocketOS Cursor + Claude Opus Database Wipe (case study) - Cursor agent running Claude Opus 4.6 deleted PocketOS's entire production database and all volume-level backups in 9 seconds via a single Railway API call; ~30-hour outage.
- $47,000 LangChain A2A Multi-Agent Loop (case study) - Analyzer/Verifier agent pair entered an undetected feedback loop for 264 hours (11 days), accruing $47K in API costs with no useful output; observability without enforcement.
- Gemini 3.5 Code Purge and Fabricated Recovery Report (case study) - Asked for a ~70-line auth fix, Gemini deleted 28,745 lines across 340 files, broke production for 33 minutes, then fabricated "consultation logs" to fake a successful recovery; root cause was a malicious npm package impersonating Google's Antigravity branding.
- Autonomous Agent Over-Provisions AWS Infrastructure for a Simple Scan (case study) - Tasked with indexing a small hobbyist network, an agent deployed five 48-vCPU AWS instances with no cost preview, running up a bill of $6,531 after an operator approved "immediately without delay" with no plan review.
- Claude Code Deploys Sensitive Data to Public URL - AI coding agent applied a learned "build and deploy" pattern to client financial data, deploying it to a public URL with zero authentication.
- Multi-Agent Coordination Failure - Concurrent Claude Code sessions silently overwrite each other's work: no cross-session awareness, no file locking, no conflict detection. Operator becomes the only coordination layer.
- Clawdbot/Moltbot/OpenClaw Shadow AI Exposure - Viral AI agent (60K→145K+ GitHub stars) had unauthenticated dashboards, 1-click RCE, and agent social network database exposure; found in 22% of enterprises.
- Claude Code Marketplace Skill Supply Chain Attack - Research demonstrated how third-party marketplace skills could hijack dependencies, inject malicious code, and execute supply chain attacks.
- Amazon Q VS Code Prompt Injection Supply Chain Attack (case study) - Attacker injected prompt into official AWS extension telling Amazon Q to delete filesystems and wipe S3 buckets; only a syntax error prevented mass destruction across 1M+ installs.
- Cline CLI Supply Chain Attack via Prompt Injection (case study) - Attacker used prompt injection on Cline's issue triage bot to steal npm tokens and publish malicious package; ~4,000 developers compromised in 8 hours.
- Comment and Control: Multi-Vendor Agent Prompt Injection (case study) - Single class of prompt-injection bug across Claude Code Security Review, Gemini CLI Action, and GitHub Copilot Agent caused agents to leak their own API keys/tokens via PR/issue/HTML-comment payloads (CVSS 9.4).
- Cursor IDE Git-Hook RCE (CVE-2026-26268) (case study) - Hostile repo prompt-injects Cursor's agent into writing into
.git/hooks/; next routine git operation runs attacker code outside the IDE sandbox (NVD 9.9). - Google Antigravity Sandbox Escape & RCE (case study) - Indirect prompt injection chained with the
find_by_nametool's-Xflag bypassed Antigravity's Strict Mode and achieved persistent host RCE; patched February 2026. - Gemini Calendar-Invite Indirect Prompt Injection (case study) - Malicious calendar invitations bypassed Gemini's authorization safeguards; an innocent "what's on my calendar" query caused private meeting data to be summarized into an attacker-visible event — no user interaction required.
- Microsoft Semantic Kernel "Prompts Become Shells" RCE (case study) - Two critical RCEs (CVE-2026-26030, CVE-2026-25592; both CVSS 9.9) in Microsoft's agent SDK let a single prompt injection reach
eval()and a host file-write tool, ending in code execution on the host — the framework trusted model output as code. - "Mother of All AI Supply Chains" — Systemic MCP STDIO RCE (case study) - A "by design" command-execution flaw in MCP's STDIO transport ("pass in a malicious command, receive an error — and the command still runs") reachable across 200+ projects, 7,000+ exposed servers, and ~200,000 instances; Anthropic declined to change the protocol, calling the behavior expected.
- Complete Taxonomy - Detailed failure classification system.
- Contributing Guide - How to contribute to this list.
- A Taxonomy of Failure Modes in Multi-Agent Workflows - Several distinct failure modes based on 150+ tasks analysis.
- Cognitive Architectures for Language Agents - Framework for understanding agent perception, reasoning, and action.
- A Survey on Large Language Model based Autonomous Agents - Comprehensive survey of LLM-based agents.
- Agon: Failure Taxonomy for Autonomous Research - Classifies multi-agent research failures along severity × fixability × visibility × capability locus, drawn from 1000+ iterations across two flagship deployments.
- Vectara's Open Source Hallucination Detection Model - Lightweight model for RAG hallucination detection.
- Hallucination Detection: A Probabilistic Framework - Using Embeddings Distance Analysis to detect hallucinations.
- FaithBench - A Diverse Hallucination Benchmark for Summarization by Modern LLMs.
- DRIFT: Detecting Representational Inconsistencies for Factual Truthfulness - Trains lightweight probes (3M–37M params) on LLM hidden states to detect hallucinations at inference time with <0.1% overhead. Achieves 10/12 SOTA AUROCs.
- ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs - Framework for improving tool use capabilities.
- On the Tool Manipulation Capability of Large Language Models - Evaluation of LLM tool manipulation abilities.
- ClawBench (paper) - Live-web benchmark for browser and computer-use agents spanning 283 everyday tasks across 163 websites, with request interception and five execution-evidence layers.
- A Survey on Large Language Model Reasoning Failures - A comprehensive review that introduces a novel taxonomy of reasoning in LLMs (embodied vs. non-embodied), and spotlights three categories of reasoning.
- AI Safety in RAG - Vectara's analysis of RAG hallucination challenges.
- Measuring Hallucinations in RAG Systems - Introduction to Hallucination Evaluation Model (HHEM).
- Automating Hallucination Detection - FICO-like scoring for LLM factual consistency.
- Technical AI Safety Conference 2024 - 18 talks from Anthropic, DeepMind, and CAIS researchers.
- Black Hat USA 2024: LLM Security Challenges - NVIDIA on LLM security vulnerabilities.
- LLMSEC 2025 Workshop - Academic workshop on adversarially-induced LLM failure modes.
- AI Risk Summit 2025 - Conference on AI agent risks.
- Human-Compatible: Artificial Intelligence and the Problem of Control by Stuart Russell (Amazon) - Explores the risks of advanced AI and argues for aligning AI systems with human values to ensure safety.
- The Alignment Problem: Machine Learning and Human Values by Brian Christian (Amazon) - Investigates how AI systems inherit human biases and examines efforts to align machine learning with ethical and social values.
- Specification Gaming - Collection of reward hacking examples.
- Awesome LLM - Large Language Models.
- Awesome Production Machine Learning - ML in production.
- Awesome AI Agents - AI agent frameworks and tools.
- Join Discussions - Share experiences and ask questions.
- Report Issues - Help us improve this resource.
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