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
AI Security & Industry Weekly: Agents, Guardrails, and Custom Chips (Week of July 6)
AI security is now core infrastructure. Autonomous agents are leaking secrets, dropping databases, and moving money, while hyperscalers lock in custom chips and states treat frontier AI like critical...
7 min1381 wordsAI Voice Fraud Hits $893M in 2025: How FBI’s New Category Changes Enterprise Defense
AI‑powered voice fraud caused an estimated $893M in losses and over 22,000 complaints in 2025 under the FBI’s first dedicated AI‑enabled fraud category. [4] This is now the synthetic‑voice equivalent...
11 min2266 wordsInside Meta’s Muse Image Model: Architecture, Safety, and Production Use
1. Context: Why Muse Image Matters in the 2026 GenAI Stack Muse Image is the visual counterpart to Meta Superintelligence Labs’ Muse ecosystem, framed as “safety‑first” through the Muse Spark Safety...
7 min1439 wordsSystem Prompt Leakage in LLM Apps: Threat Model, Exploits, and Defenses for Production Teams
Hidden system prompts now encode product strategy, moderation policy, and tool access logic. When those instructions leak, attackers gain a blueprint for breaking your app: how to talk to the model, w...
8 min1529 wordsFrom Demos to Durable Systems: AI Engineering Techniques That Make LLMs Truly Product-Ready
Laptop demos with a single API call hide real problems: reliability, safety, compliance, and cost.[1][2][4] In production, those show up as timeouts, hallucinations, security incidents, and legal push...
12 min2303 wordsHow a U.S. Executive Order Demanding Early Access to Frontier AI Models Would Reshape Engineering and Compliance
The next major U.S. AI executive order will likely extend existing policy: AI as a national and economic security race, preference for a single federal baseline over state “patchworks,” and collaborat...
8 min1508 wordsEU AI Act Enforcement from August 2, 2026: What ML and AI Teams Must Change Now
From August 2, 2026, high‑risk AI systems in the EU move from soft guidance to hard enforcement, with penalties up to €35 million or 7% of global annual turnover for serious violations.[1][2] Complian...
8 min1644 wordsGPT-5.6 in the Wild: How OpenAI’s New Model and Custom Silicon Will Reshape Production LLM Systems
GPT-5.6 is landing in a different world than GPT-4 or 5.4. OpenAI now owns not just models and products but also a custom “Intelligence Processor” ASIC, Jalapeño, designed specifically for LLM inferen...
6 min1280 wordsJadePuffer: Engineering the First Fully LLM‑Driven Ransomware Kill Chain
1. From LLM Hallucinations to Operational Malware: Why JadePuffer Is Plausible Browser-only ransomware was once dismissed as “LLM hallucination,” until researchers showed a fully browser-native ranso...
11 min2272 wordsJadePuffer: Inside the First Fully LLM‑Driven Ransomware Attack and How Langflow Agents Were Weaponized
JadePuffer shows what happens when autonomous LLM agents, wired into real tools and data, are given ransomware objectives. - 75% of organizations were hit by ransomware in the last year; average brea...
11 min2190 wordsInside GPT-5.6: How OpenAI’s New Flagship Model and Custom Silicon Will Reshape LLM Operations
OpenAI is no longer “just” a model API. With the Jalapeño Intelligence Processor, it now owns a major slice of the hardware stack that runs ChatGPT, Codex, and future agentic products.[1][7] GPT-5.6 w...
7 min1321 wordsGPT-5.6, Jalapeño, and the Next Generation of OpenAI-Optimized LLM Infrastructure
OpenAI’s GPT-5.6 is not just a new model release. It arrives on a full-stack platform where OpenAI controls models, products, and now custom silicon via the Jalapeño Intelligence Processor, co-develop...
7 min1312 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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