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Coordinating AI Agents With AWS SQS: A Practical Queue-Based Architecture

30 Jul 2026, 15:00 by Lucas Yoon

Building a single AI agent is not usually the hard part.

You send a prompt to a model, get a response back, and wire it into your app. Done.

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Building a Config-Driven SOAP/REST Integration Layer: One Service, Many Protocols

30 Jul 2026, 14:00 by Balaji Venkatasubramaniyar

If you've spent time in enterprise integration, you know the pattern: your platform needs to talk to dozens (sometimes hundreds) of external partner systems, and none of them agree on how they want to be talked to. Some expect SOAP envelopes. Others have moved to REST/JSON. Some want Basic Auth, others OAuth, others a bespoke token scheme. Multiply that by data formats that differ subtly — different XML schemas, different field names, different nesting — and you have a classic integration headache.

Back in 2019, I inherited a service in exactly this position. It was a .NET-based SOAP web service acting as a middleware layer: a caller would hit our service, our service would reach out to a customer's web service, retrieve the data, and hand a response back to the original caller. Request and response payloads were transformed using XSLT, with a distinct transformation mapped to each customer's expected schema.

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What Is Agentic Test Creation and How Is It Different from AI Test Generation?

30 Jul 2026, 13:00 by John Vester

Throughout my career, I’ve held many roles in the QA conversation:

As a developer, waiting on test teams to validate features before a release could ship
As a tech lead, watching sprint capacity dwindle while we converted Jira stories into test cases by hand
As an architect, auditing a test repository with 4,000 cases where no one knew which ones mattered

So when “AI test generation” started appearing as part of every testing product, I was both interested…and skeptical. After spending time with several of these tools, I’ve decided that the phrase “AI test generation” covers two fundamentally different architectures.

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Build Your Own Local AI QA Engineer With Docker, Ollama, LibreChat, and Playwright MCP

30 Jul 2026, 12:00 by Faisal Khatri

Artificial intelligence is rapidly transforming software testing by enabling QA engineers to generate test cases and test plans, automate browser interactions, analyze and debug failures, and execute complex testing workflows using simple natural-language prompts.

While cloud-based AI assistants offer impressive capabilities, they often require subscriptions and sharing potentially sensitive application data with third-party services.

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