My experiences of effectively using AI for personal workflows, with a focus on Claude Code.

spoiler: most tools will not even survive 90 days. this guy is literally giving away the exact 2026 playbook for AI Agents. he covers what to learn, what to build, and what to skip 👀 ↓ read this today

A unified theoretical framework for structured test-time scaling, showing how topology compression, scope isolation, and decoupled verification—a three-layer structural decoupling—bypass the linear collapse of long-horizon reasoning across multi-agent systems, recursive architectures, and coding agents.

this is a work in progress mental dump on interesting intersections between how we use and design a harness, implications for memory being accumulated over long timescales, and the search bitter lesson we can’t escape this

An overview of four durable agentic patterns, from deterministic workflows to autonomous multi-agent orchestration, and the trade-offs each architecture introduces.

So far I only have one: Inflicting unreviewed code on collaborators, aka dumping a thousand line PR without even making sure it works first https://t.co/rg6LVi9zkk

Master AI engineering with 30 essential AI systems engineering patterns. From RAG and LLM gateways to multi-agent orchestration and flow engineering, discover the definitive guide to robust LLM design patterns that bridge the gap between traditional software architecture and modern AI development.

Hi, welcome to my website! This is where I share my thoughts on things that interest me, mostly tech, philosophy, history, and math.

If you’ve built an agent, you know that the delta between “it works on my machine” and “it works in production” can be huge. Traditional software assumes you mostly know the inputs and can define the outputs. Agents give you neither: users can say literally anything, and the space

Claude can now discover, learn, and execute tools dynamically to enable agents that take action in the real world. Here’s how.

A step-by-step practical guide on building AI agents using Gemini 3 Pro, covering tool integration, context management, and best practices for creating effective and reliable agents.

We envision a new era of AI, termed agentic organization, where agents solve complex problems by working collaboratively and concurrently, enabling outcomes beyond individual intelligence. To...

A practical guide to Agent Engineering: the intersection of software, systems and security engineering.

Design robust multi-agent AI systems in Google Cloud.

Agentic Design Patterns A Hands-On Guide to Building Intelligent Systems, Antonio Gulli Table of Contents - total 424 pages = 1+2+1+1+4+9+103+61+34+114+74+5+4 11 Dedication, 1 page Acknowledgment, 2 pages [final, last read done] Foreword, 1 page [final, last read done] A Thought Leader's ...

Practical lessons from building production agentic systems

This post shares the local optima Manus arrived at through our own "SGD". If you're building your own AI agent, we hope these principles help you converge faster.

AI Engineer at ANZ Bank working on intelligent systems, LLM optimization, and scalable ML platforms.

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