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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.
The new Google image search will use your "unique interests" to create an always-updated gallery.
In this post, you will learn how ScienceSoft, an Amazon Web Services (AWS) Services Partner, integrated Amazon Nova 2 Sonic with Amazon Bedrock Guardrails to build a Health Insurance Portability and Accountability Act (HIPAA)-compliant AI voice scheduler. You will see how the solution addresses healthcare scheduling challenges while maintaining privacy, compliance, and responsible AI standards, and how you can apply the same architecture to your own workflows.
Progress Software has confirmed that a high-severity zero-day vulnerability is behind the emergency shutdown of ShareFile Storage Zone Controllers last week and has released security updates to patch the flaw. [...]
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Cutting-edge artificial intelligence models are deploying with more independence and less human oversight. Several state governments are trying to legislate transparency in their use.
In a world where testing is mainly test execution, it is reasonable to expect that when people test, they simply expect to find bugs. "We test to find bugs" is the answer given in job interviews. An answer repeated in onboarding materials, embedded in KPI frameworks, and implicitly assumed in every conversation about when software is ready to ship. It is so thoroughly taken for granted that questioning it sounds absurd, like questioning whether hammers are for hitting things. Testing does find b
Google Images is turning 25. Here’s a look back at some major milestones — and new ways to explore and create visual content.
Coding AI agents are becoming practical operators for long-running machine learning (ML) workflows. They can inspect repositories, set up runtimes, resolve... Coding AI agents are becoming practical operators for long-running machine learning (ML) workflows. They can inspect repositories, set up runtimes, resolve build issues, launch experiments, monitor execution, analyze metrics, and summarize results. For reinforcement learning (RL) research, this matters because meaningful metrics often appe
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