Documented AI Incidents
Hallucinations, ghost sources, RAG failures: understand and prevent common AI agent issues.
AI Hallucinations - RAG best practices - Ghost sources - KB Drift - Chunking strategies
Articles
- 🌀Hallucinations
AI in Military Operations: Navigating Ethical Red Lines Before the Next Conflict
Artificial intelligence is now core military infrastructure, not a futuristic add‑on. General‑purpose AI can parse satellite imagery, generate battle plans, write malware, and script propaganda—often...
10 min1993 words - 🌀Hallucinations
AI Agents, Financial APIs, and the Invisible Threat of Unauthorized Stock Trades
As enterprises wire AI agents into trading stacks, treasury platforms, and finance workflows, they are quietly giving probabilistic systems the ability to move real money. Debate still centers on bia...
11 min2227 words - 🌀Hallucinations
How Retrieval Augmented Generation Actually Prevents AI Hallucinations
Introduction Retrieval Augmented Generation (RAG) is often sold as a cure for hallucinations: add search and a vector database, and the model stops lying. Reality is subtler. LLMs are excellent at s...
9 min1851 words - 🌀Hallucinations
Why LLMs Invent Academic Citations—and How to Stop Ghost References
Introduction Large language models now assist with theses, grant proposals, and journal articles, often drafting sections and reference lists. Across 13 state-of-the-art models, hallucinated cit...
9 min1879 words - 📄bias
Source-Verified AI Systems: Governance Architecture for Auditable LLM Deployment (2026 Guide)
LLMs are moving from experimental tools to decision infrastructure in government, finance, and healthcare. Regulators, CISOs, and auditors now demand proof of what the model did, what it saw, and wh...
8 min1420 words - 🌀Hallucinations
Ars Technica’s AI Retraction: What Fabricated Quotes Reveal About Newsrooms and AI Governance
Introduction Ars Technica, a highly technical outlet, retracted a story after an AI tool invented quotes and attributed them to a real person, open source maintainer Scott Shambaugh.[1][2][3] The edi...
8 min1651 words - 🛡️Safety
Claude, Militaries, and Maduro’s Venezuela: A Safety-First Ethics Blueprint
Deploying Claude-like systems in militaries or security organs is never neutral. In fragile, polarized Venezuela under Nicolás Maduro, the same tools that aid planning or translation can also power su...
5 min1015 words - 🌀Hallucinations
Google AI Overviews in Health: Misinformation Risks and Guardrails That Actually Work
As Google shifts health search from curated links to AI‑generated Overviews, errors can scale from isolated mistakes to synchronized, system‑level failures delivered with search‑page authority. In bio...
5 min1032 words - 🌀Hallucinations
Designing High-Impact `--help` Experiences for AI, CLI, and DevOps Tools
In AI, MLOps, and security-heavy environments, --help is a primary interface for discovery, safe automation, and compliant usage—not a cosmetic add-on. When teams script everything, onboard continuou...
5 min986 words - 🌀Hallucinations
AI Surgery Incidents: Preventing Algorithm-Driven Operating Room Errors
As hospitals embed AI into pre-op planning, intra-op navigation, and post-op documentation, the incident surface expands far beyond model accuracy. Enterprises already show the pattern: 87% use AI in...
5 min1034 words - 🌀Hallucinations
Clinco v. Commissioner: Tax Court, AI Hallucinations, and Fictitious Legal Citations
When a tax brief cites cases that do not exist, the issue is structural, not stylistic. LLMs optimized for sounding persuasive can generate “Clinco v. Commissioner”–type authorities that look valid bu...
4 min867 words - 🌀Hallucinations
Kenosha DA’s AI Sanction: A Blueprint for Safe LLMs in High‑Risk Legal Work
When a Kenosha County prosecutor was sanctioned for filing AI‑generated briefs with fabricated case law, it marked a turning point. This was a production failure in a courtroom, with real consequences...
5 min1002 words
Topics Covered
AI Hallucinations
Understanding why LLMs invent information and how to prevent it.
RAG Best Practices
Retrieval Augmented Generation: architectures, chunking, optimal retrieval.
Ghost Sources
When AI cites sources that don't exist. Detection and prevention.
KB Drift
How to detect and correct knowledge base drift.
Chunking Strategies
Optimal document splitting for better retrieval.
LLM Evaluation
Metrics and methods to evaluate AI response quality.
AI Regulation
Laws, regulations and compliance frameworks governing AI systems.
AI Safety
Risks, safeguards and best practices for safe AI deployment.
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