Supply Chain Attacks, Vibe Coding, and Safer Dependency Habits
The March 2026 axios npm compromise and LiteLLM PyPI attack show how package trust breaks. Practical dependency habits that reduce your exposure.
Read article → AI/ML
10 Posts
Exploring ai/ml and related topics
Filter by Topic
All AI AI Agents AI Architecture AI Engineering AI Evaluation AI Literacy AI/ML Agent Harness Agentic Workflows Agents Anthropic Architecture Automation Benchmarks Best Practices Blockchain Career Claude Claude Code Codex Data Quality Developer Productivity Development Engineering Eval Generation Feedback Loops Gemini Governance LLM LLM API Leadership MLOps Machine Learning OpenAI Production Production AI Prompt Engineering Python RAG SOTA Security Self-Improving AI Structured Prompting Supply Chain Systems Thinking Testing Versioning npm
What Happens When You Call an LLM API
· 12 min read
Your prompt travels through 7 infrastructure layers before a single token comes back. A plain-language walkthrough of API gateways, tokenization, prefill, decode, post-processing, billing, and the network physics underneath.
Read article →OpenClaw for Builders: Architecture, Data Flow, and Security Guardrails
· 9 min read
A practical OpenClaw guide for beginner to advanced builders. Learn the gateway architecture, message-to-action data flow, and the security controls that matter before real deployment.
Read article →Context Window vs Attention Window: What AI Architects Must Understand
· 5 min read
Context size is not the same as attention behavior. A practical guide for LLM architecture, RAG design, and long-context system trade-offs.
Read article →Red Teaming AI Systems: A Practitioner's Guide to Breaking Your Own Agents
· 14 min read
Teaming in AI integrates offensive and defensive expertise through multiple specialized teams. Organizations implementing comprehensive teaming detect 92% more vulnerabilities and reduce fix costs by 78%.
Read article →Recursive Language Models: Why Smarter Navigation Beats Bigger Memory
· 8 min read
RLMs solve the context window problem by letting AI write code to explore information. The result? Tasks going from 0% to 91% success. Here's how it works and when to use it.
Read article →Sloperators: Why AI Outputs Need Owners, Not Better Models
· 4 min read
AI outputs fail when signals lack owners and judgment.
Read article →AI and Data Quality: The $12.9 Million Problem and How Training Data Poisons Your AI
· 9 min read
AI doesn't create garbage; it recycles your mess at warp speed. How bad data poisons AI at the training and prompting stages, and what you can do about it.
Read article →AI and Data Quality: RAG Systems, Context Engineering, and the Governance Layer
· 13 min read
How RAG systems and context engineering can poison your AI, plus the governance layer and action plan to fix data quality across your entire pipeline.
Read article →Why AI Architecture Became Unavoidable
· 7 min read
How software systems evolved faster than job titles, and what that means for building production AI systems in enterprise environments.
Read article →