Simplifying AI Agents and Automation for Everyone.
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AI assistants are reading the web on your users' behalf. Adobe just put a number on how badly most pages handle that and it turns out "AI visibility" is a retrieval problem, not a marketing one.
How a simple outreach workflow slowly turned into a system that checks replies, handles follow-ups, personalizes messages, and keeps track of what happened.
Follow this guide and learn how to do a machine learning project step by step
A chapter-by-chapter reading guide to Hands-On Machine Learning with Scikit-Learn and PyTorch by Aurélien Géron (O'Reilly, 2025)
7 failure modes that only show up after real users arrive and the architecture patterns that contain them.
What a neural network attack reveals about building more resilient AI systems.
A chapter-by-chapter reading guide to AI Engineering: Building Applications with Foundation Models by Chip Huyen (O'Reilly, 2025)
The future of AI will not be defined by systems that make fewer mistakes, but by systems that understand which mistakes matter.
Welcome to the 60th issue of AI Agents Simplified 🍻
Why You Should Stop Prompting Your AI Agent and Start Designing Its Job
Most teams lock down their code. Almost nobody locks down their agent's tools.
Inside the massive shift to Agentic Engineering, the cure for Context Rot, and the open protocols taking AI mainstream.
Harness Engineering, Loop Engineering, Hermes AI: What They Are and Why Everyone's Talking About Them
Here's a repo that gets the order right.
A deep dive into the 2026 framework extracting exact churn triggers straight from natural language feedback.
The architecture mistake everyone makes on their first build and the exact blueprint to solve it.
AI Agents Are Easy to Demo, Hard to Ship; The Backend Architecture of Reliable Agents
Every Claude Code session begins amnesiac. The fix isn't a better prompt; it's a system that compounds.
A deep dive for engineers, researchers, and practitioners who want their writing to actually say something.
Use this guide to learn AI engineering
Lessons on context discipline, state validation, and closing the feedback loop from building a purely social LLM game.
