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Practical writing on software architecture, SaaS products, AI automation, legacy modernisation, and the business of building reliable systems.

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Curated links from external sources — not 360Softy original articles.

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From OpenClaw to Norax: Evolving an AI Agent Architecture

From OpenClaw to Norax OpenClaw was my first AI agent. It worked, but it was built on borrowed infrastructure. Norax is the rebuild — ground-up, every line mine. Own your stack — Don't depend on others' runtimes Memory is everything — OpenClaw forgot everything after 50 messages. Norax has 11,000+ canonical memories with entity graph retrieval Tools need guardrails — Loop detection, write verification, parallel execution Cost optimization is not optional — OpenClaw: $8-12/day. Norax duo: $1.80

agentsaiarchitecture
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ExternalSoftware Engineering
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Kustom vs SaaS: Cara Memilih Arsitektur AI Knowledge Base Internal yang Tepat

Memilih antara platform AI knowledge base siap pakai (off-the-shelf) dan sistem yang dibangun dari awal bukan soal mana yang lebih canggih—ini soal kontrol, kepemilikan data, dan apakah sistem itu masih bekerja dengan baik dua tahun dari sekarang. Dua pendekatan ini memiliki logika masing-masing, dan kesalahan paling umum adalah memilih salah satunya karena tekanan waktu, bukan karena analisis kebutuhan. Off-the-shelf)? Solusi SaaS untuk AI knowledge base—seperti Notion AI, Guru, atau Glean—ma

aiarchitecturerag
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ExternalSoftware Engineering
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Videollamadas 1:1 en ~180 líneas de backend a $0.20 por sesión, no necesitas más

No necesitas un SaaS de video para poner a dos personas en una llamada. Con un plano de medios administrado (aquí AWS Chime SDK, pero la forma se generaliza), el lado del servidor de una videollamada 1:1 es una reunión, dos tokens de ingreso, y un interruptor de apagado. Este post construye exactamente eso, una llamada host↔guest con grabación, sobre FastAPI + SQLAlchemy + un cliente de React, y mantiene la cuenta predecible. / blog-video-conferencing-code Code companion —

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ExternalSoftware Engineering
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Kubernetes Explained: The Airport Control Tower Mental Model

The Problem with Learning Kubernetes Kubernetes documentation is thorough. It's also overwhelming. Terms like "control plane," "kubelet," "etcd," and "pod" get thrown around without a unifying mental model. Here's the analogy that made it click for me: Kubernetes is an airport control tower. The control plane doesn't run your containers (fly the planes). It orchestrates where they run and ensures the system stays healthy. API Server: The communication hub. Every request goes through here. Sche

kubernetesdevopsdocker
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