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

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How a "safe" shipping change silently disapproved 621 products in Google Merchant Center

I run a small Shopify store. One afternoon I split my shipping policy in two — separate rules for domestic vs. international, nothing exotic — and by the next morning 621 of 739 active products had been disapproved in Google Merchant Center. A 21% drop became an 84% drop overnight, and the actual error Google returned was missing_shipping, which made no sense: the products had shipping info, I'd just moved it. This is the write-up of what actually went wrong and how I built a small diagnostic to

ecommerceshopifyseo
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ExternalSoftware Engineering
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Service Level Objectives for Complex Microservices

Why SLOs Break in Microservices A SLO that works for a monolith often collapses when you distribute the same logic across 30 services. The math of availability is unforgiving. If your service depends on 5 others, each at 99.9%, your realistic ceiling is 0.999^5 = 99.5%. That 0.4% gap eats your entire error budget before your own code even runs. 1. Copying the same SLO to every service A 99.9% target on a payment service and a batch analytics service are not the same thing. One ruins revenue. O

sreslomicroservices
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ExternalSoftware Engineering
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Modernising a legacy AS/400 (IBM i) system without rewriting it

Many companies still run production, warehousing, orders and invoicing on a business system that has been going for twenty years or more on an AS/400. Today that platform is called IBM i (it went from AS/400 to iSeries, System i and finally IBM i), but the name almost everyone still uses is the first one. Faced with a system this old, the instinctive reaction is to think it should be scrapped and rebuilt. Almost always that is the wrong conclusion. The problem is rarely the machine, which remain

legacyibmijava
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ExternalSoftware Engineering
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I Built a $0 Local AI Automation Stack: Agentic Coding + Market Data Over MCP

Serious AI-assisted development has a habit of turning into a stack of subscriptions: a coding-assistant plan, a market-data API, a backtesting service, model credits. Each one is reasonable on its own, and together they quietly become a monthly bill that also locks you into someone else's rate limits. I wanted to know how far you can get without any of that. The answer turned out to be: surprisingly far. Here's the stack I ended up with, running at $0 recurring cost and scripted so it rebuilds

aimcppython
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ExternalSoftware Engineering
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La capa sobre el asistente: por qué tu contexto muere entre IDEs y cómo construir el puente

El problema de los workflows multi-IDE no es la calidad del modelo, es que cada sesión empieza desde cero. Tienes tres asistentes de IA en tu flujo de trabajo. Kiro para triage y razonamiento sobre el codebase, Cursor para implementación rápida, y Claude Code para sesiones largas de refactor donde necesitas un modelo con ventana de contexto grande. Cada uno hace bien su parte. El problema está en el medio. Kiro encuentra el bug, analiza el stack trace, entiende el contexto. Cambias a Cursor o a

kiroclaudecursor
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ExternalSoftware Engineering
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Common Problems in AI-Generated Frontend Code and How to Avoid Them

Over the last year, I’ve reviewed about a dozen projects where AI was used heavily in development. These were real products with real users, built fast and shipped to production. Most worked fine. Some had interesting patterns that kept showing up across different codebases. These aren’t unique to any one team or project, they’re just common things that happen when AI writes code and humans skip the review step. Here’s what I noticed: AI is exceptional at writing code quickly. It’s less aware of

webdevfrontendai
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