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
Designing with Nvidia’s Open Ising Quantum AI Models: A Calibration Playbook for ML Engineers
🌀HallucinationsClassical LLMs are strong at language and loose reasoning, but weak at hard calibration: dense constraints, discrete knobs, and unforgiving objectives. Ising‑style quantum‑inspired models flip this...
10 min2009 wordsNvidia Ising Quantum AI: Calibration Models Guide 2026
🌀HallucinationsQuantum‑inspired Ising solvers are moving into production for chip layout, routing, and large‑scale scheduling. By 2026, they resemble high‑stakes LLM services: powerful, opaque, tied to sensitive dat...
10 min2034 wordsAI-Enabled Zero-Day 2FA Bypass: How to Protect Open-Source Admin Tools from the Next Wave of Attacks
AI models can now autonomously discover and chain zero-days across large, mature codebases, including OSes, browsers, and core libraries.[2][7] The lag between disclosure and in‑the‑wild exploitatio...
11 min2126 wordsDesigning Nvidia-Grade Ising Quantum AI Models for Robust Qubit Calibration
1. Problem Framing: Why Quantum Calibration Needs Ising-Aware AI on NVIDIA Stacks Modern quantum devices depend on continuous calibration: qubit frequencies, amplitudes, and pulses drift on minute–ho...
7 min1372 wordsNvidia Ising Quantum AI: A Practical Guide to Automating Qubit Calibration and Error Correction
1. Why quantum computing suddenly needs AI-grade calibration Quantum processors remain blocked by noise: even top devices see errors roughly every 10³ operations, while fault-tolerant systems need ra...
10 min2017 wordsCommunity Bank’s SEC 8-K AI Data Breach: How an Unauthorized Employee App Exposed PII and Rewrote AI Risk for Banks
An employee at Community Bank, a 125‑year‑old regional lender, uploaded customer records—including names, dates of birth, and Social Security numbers (SSNs)—to an unauthorized AI application.[1][2] Da...
7 min1364 wordsAnthropic Claude Code npm Source Map Leak: When Packaging Turns into a Security Incident
When an AI coding tool’s minified JavaScript quietly ships its full TypeScript via npm source maps, it is not just leaking “how the product works.” It can expose: - Model orchestration logic - A...
9 min1705 wordsLovable Vibe Coding Platform Exposes 48 Days of AI Prompts: Multi‑Tenant KV-Cache Failure and How to Fix It
From Product Darling to Incident Report: What Happened Lovable Vibe was a “lovable” AI coding assistant inside IDE-like workflows. It powered: - Autocomplete, refactors, code reviews - Chat over...
11 min2126 wordsAnthropic Mythos AI: Inside the ‘Too Dangerous’ Cybersecurity Model and What Engineers Must Do Next
Anthropic’s Mythos is the first mainstream large language model whose creators publicly argued it was “too dangerous” to release, after internal tests showed it could autonomously surface thousands of...
11 min2203 wordsVercel Breached via Context AI OAuth Supply Chain Attack: A Post‑Mortem for AI Engineering Teams
An over‑privileged Context AI OAuth app quietly siphons Vercel environment variables, exposing customer credentials through a compromised AI integration. This is a realistic convergence of AI supply c...
7 min1408 wordsAI in Art Galleries: How Machine Intelligence Is Rewriting Curation, Audiences, and the Art Market
Artificial intelligence has shifted from spectacle to infrastructure in galleries—powering recommendations, captions, forecasting, and experimental pricing.[1][4] For technical teams and leadership...
7 min1451 wordsComment and Control: How Prompt Injection in Code Comments Can Steal API Keys from Claude Code, Gemini CLI, and GitHub Copilot
Code comments used to be harmless notes. With LLM tooling, they’re an execution surface. When Claude Code, Gemini CLI, or GitHub Copilot Agents read your repo, they usually see: > system prompt + de...
7 min1473 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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