Professional architect sharing high‑quality architecture insights. Topics include high‑availability, high‑performance, high‑stability architectures, big data, machine learning, Java, system and distributed architecture, AI, and practical large‑scale architecture case studies. Open to ideas‑driven architects who enjoy sharing and learning.
A Rust rewrite of SQLite generated largely by an LLM runs a simple primary‑key lookup 20,171 times slower than native SQLite, exposing how seemingly correct code can miss critical system constraints, and illustrating the need for explicit acceptance criteria, benchmark baselines, and governance when using AI‑generated software.
This article walks you through the complete process of converting a single‑agent OpenClaw deployment into a multi‑agent architecture, covering agent isolation resources, when to split, creating agents, routing rules, DM safety, sandbox options, multi‑gateway setups, remote access, hot‑reload configuration, and a pre‑deployment checklist.
This article dissects a real Skill from Anthropic’s open‑source repository, explains the design principles behind its 42‑line SKILL.md, compares Anthropic’s Claude Code and OpenAI’s Codex ecosystems, and extracts practical lessons for building robust, version‑controlled AI Skills.
In a 14‑minute interview, Mihail Eric explains how the rise of AI agents is forcing software engineers to transform from code writers into orchestrators who allocate intelligence, manage contexts, and redesign codebases to be agent‑friendly, offering a practical checklist for teams navigating this structural shift.
This article distills the Claude Code team's hard‑won insights on building effective AI agents, highlighting why action‑space design outweighs model size, how structured questioning improves bandwidth, when to replace Todos with Tasks, and a repeatable seven‑step loop for evolving toolsets.
The article explains why writing code alone does not guarantee delivery, outlines three core challenges for long‑running agents—process reuse, execution, and context continuity—and presents a practical framework of Skills, Shell, and Compaction together with ten actionable recommendations, security guidelines, and implementation steps for teams.
This article explains how OpenClaw controls the side‑effects of AI‑driven tool calls by splitting them into three guardrails—sandbox, tool policy, and elevated—plus a dynamic exec‑approval step, detailing configuration keys, practical troubleshooting tips, and a minimal baseline setup for secure deployment.
The article explains how OpenClaw tackles common multi‑agent messaging problems by treating sessionKey as a partition key, redefining DM scope for multi‑source inputs, employing a dual‑layer queue with per‑session serialization and global lane throttling, and exposing configurable knobs for micro‑batching, backpressure, and observability.
Boris Tane, former founder of Baselime and Cloudflare Workers observability lead, shares a disciplined eight‑step workflow that lets architects harness Claude Code while preventing costly system‑breaking AI‑generated code, by making every AI contribution explicit, reviewed, and anchored to documented architectural decisions.
The article explains how OpenClaw’s control plane guarantees reliable, idempotent, and observable agent execution by enforcing a two‑phase protocol, strict handshake, role‑based authorization, layered deduplication, gap‑recovery mechanisms, and schema‑driven validation, turning a simple message flow into a production‑grade job system.
