Library
Technical articles: agents, architecture, tools and design decisions.
If your business uses third-party AI, the AI Act barely applies to you, but the GDPR does. A hype-free guide for decision-makers: what you can do, what you can't, and what gets you fined.
Generative AI doesn't look up truths: it predicts the most plausible word. That mental model explains why it hallucinates, why it changes, and where it fails.
A framework for knowing which of your tasks are a good fit for AI and which ones are money down the drain: AI use cases in business, no hype.
Set up autoMode.environment so the classifier understands your infrastructure and stops interrupting you with false positives.
An LLM predicts the next most probable token. It doesn't understand. So how does it produce outputs that seem to require real comprehension?
An honest guide to AI risk in the workplace: where it can go wrong, how to contain it, and what to check before committing budget. No hype.
AI for business without the hype: when it actually makes sense, when it doesn't, and a clear framework for deciding where to start without gambling your business.
What is prompt injection, OWASP's #1 vulnerability for LLMs, how the attack works, and how to protect your app from day one.
How to build AI automations using Zapier, Make, or n8n. Five real workflows, comparison table, and a framework for choosing your first automation.
Implement guardrails in your AI agent step by step: input/output validation, action limits, and loop control. Real, copy-ready code examples.
Learn how to use an AI model to automatically evaluate another agent's responses. Rubrics, evaluation types, and the most common pitfalls.
Set up a Claude Project from scratch: custom instructions, knowledge files, and ready-to-copy examples. A practical visual guide for any workflow.
