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
- 🛡️Safety
Inside Amazon’s AI Rollout: Surveillance, Burnout, and Broken Guardrails
Amazon is racing to embed generative AI into everything from its retail storefront to AWS infrastructure. The promise: faster code, fewer mundane tasks, more innovation. Behind that pitch, internal...
7 min1495 words - 🌀Hallucinations
7 AI Fails That Damaged Brands (and How Human Support Could Have Saved Them)
Non-technical executives are pushing for “AI everywhere” in customer experience. When an automated agent takes the site down, leaks data, or gives illegal advice, the blame lands on the team that depl...
11 min2272 words - 📄performance
Inside Amazon’s AI Outage Crisis: What the Emergency Meeting Signals for Enterprise Engineering
Amazon’s latest reliability scare was not a single bad deploy but a pattern. After four Sev1 incidents in one week, Amazon’s retail tech leadership turned its routine “This Week in Stores Tech” (TWiS...
7 min1466 words - 🛡️Safety
How the EU AI Act Rewires Corporate Governance and Business Processes
Introduction: From Future Law to Present Operating Constraint The EU AI Act now has firm dates: bans on some systems apply in 2025 and full high‑risk obligations from August 2026.[10][11] For larg...
8 min1658 words - 🌀Hallucinations
Inside the AI Training Data Contamination Lawsuits Targeting OpenAI and Anthropic
Lawsuits against OpenAI and Anthropic are turning training data contamination from a niche benchmarking issue into a central legal and regulatory flashpoint for generative AI.[1][3] What began as a...
10 min1969 words - 📄performance
Inside Amazon’s GenAI Outages: Why Engineers Are Rewriting the Rulebook
Amazon’s aggressive push into generative AI has collided with its legendary focus on uptime. In one week, the company suffered four high‑severity incidents that degraded or took down critical retail a...
6 min1255 words - 🛡️Safety
Ethical AI as a Strategic Engine for Innovation and Corporate Responsibility
Ethical AI has moved from a niche concern to a core driver of competitive advantage. AI now underpins products, operations, and workplaces, yet governance often lags behind. That gap is costly, risky,...
7 min1379 words - 🌀Hallucinations
AI Deepfake Scams: How Criminals Target Taxpayer Money and What Governments Must Do Next
Introduction: When Public Money Meets Synthetic Identities Deepfakes have turned fraud against tax and welfare systems into a scalable, semi‑automated business. - Hyper‑realistic fake voices, faces...
10 min2077 words - 🛡️Safety
When GenAI Coders Break the Store: Inside Amazon’s AI-Driven E‑Commerce Outages
Amazon’s generative AI coding tools helped ship code so quickly that they repeatedly took down core e‑commerce and AWS services. The result: emergency guardrails, mandatory senior sign‑offs, and a res...
5 min903 words - 🌀Hallucinations
AI Hallucination in Military Targeting: Risks, Ethics, and a Safe-by-Design Blueprint
Introduction When an AI model hallucinates in a customer chatbot, the damage is usually limited to reputation, trust, and compliance. In a military targeting system, the same behavior can misidentify...
10 min1921 words - 📄performance
Inside Amazon’s GenAI Coding Outages: What Broke, Why It Matters, and How to Build Safer AI-Driven Engineering
Introduction: When Experimental AI Jumps the Guardrail In early 2026, Amazon’s internal generative AI coding tools moved from experiment to public failure. A cluster of high-severity outages hit AWS...
10 min2014 words - 📄ethics
Anthropic vs. U.S. Agencies: Inside the AI Blacklist Fight
Anthropic’s lawsuit over its alleged federal procurement blacklist sits at the intersection of contract law, AI safety, and a White House push to normalize “any lawful purpose” access to frontier mode...
3 min528 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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