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Engineering Insights
Practical writing on software architecture, SaaS products, AI automation, legacy modernisation, and the business of building reliable systems.
Curated links from external sources — not 360Softy original articles.
Money launderer accused of stealing seized crypto while in prison
A Bulgarian national has been charged with stealing $290,000 in government-seized cryptocurrency while serving 121 months in prison for helping launder millions stolen from American fraud victims. [...]
Scaling agentic workflows with native case management in Amazon Quick Automate
In this post, we show you how to combine case management with agentic automation capabilities in Quick Automate. We introduce case management and explore the lifecycle of cases in an agentic workflow from case creation through processing to resolution. We cover how to create and manage single or multiple cases, automatically track and update status, handle exceptions, and incorporate Human-in-the-loop (HITL) steps within workflows. We also show the case creator-processor pattern that enables dyn
Deploying quantized models on Amazon SageMaker AI with Unsloth
In this post, you will learn four deployment patterns for taking models that have already been quantized with Unsloth and deploying them on AWS infrastructure. The patterns use Amazon Elastic Compute Cloud (Amazon EC2) for direct instance access, Amazon SageMaker AI inference endpoints for managed serving, and Amazon Elastic Kubernetes Service (Amazon EKS) or Amazon Elastic Container Service (Amazon ECS) when inference needs to fit into an existing container framework. You also learn operational
Computation as a universal and fundamental concept
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How KTern.AI built agentic AI for SAP on Amazon Bedrock AgentCore
Evolving from a traditional software as a service (SaaS) platform into a next-generation agentic AI platform meant orchestrating multiple specialized agents across long-running enterprise programs. Each agent operates with persistent context, secure tool access, and production-grade reliability. We built that system on Amazon Bedrock AgentCore using the Strands Agents SDK. This post walks through how we architected it, which agents we built, and the outcomes for our customers.
Disaggregated prefill and decode for LLM inference on SageMaker HyperPod
In this post, we show how to implement DPD with vLLM on Amazon SageMaker HyperPod using the HyperPod Inference Operator.
NASA sure seems to be asking an awful lot of private space stations
"Industry finally knows what NASA is asking of them."
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