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Code and Connect: MCP + MuleSoft

Jun 25th 2026, 15:00 by Ajay Singh

I often find myself in conversations where the same words keep popping up again and again: Agents, MCP, and A2A. Everyone seems excited about them. But the funny part is that when the topic shifts to MCP (Model Context Protocol), the explanations start to vary.

One day, someone confidently said, “An MCP server is basically a tool.” Another person immediately disagreed and replied, “No, no — MCP is more like a client.” Before that debate could settle, someone else joined the conversation and said, “Actually, MCP is just a protocol.”

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Reducing Alert Fatigue in the SOC Using Correlation Rules and Detection-as-Code

Jun 25th 2026, 14:15 by Krishnaveni Musku

Alert fatigue in a security operations center tends to appear when alerts outpace the ability to validate them with confidence, creating desensitization and burnout while increasing the chance that the rare high-signal alert is handled too slowly. Practitioner research on SOC alarm validation describes this work as tedious and emphasizes that “false positive” is often an imprecise label, because many alarms are better understood as benign triggers that match a detection condition but are tolerated in the local environment. Correlation rules and detection-as-code reduce fatigue by shifting escalation away from isolated event matches and toward repeatable, reviewable patterns and thresholds.

When alerts become noise rather than signal

Fatigue is frequently framed as too many alerts, but the tractable engineering problem is too many alerts that require human validation. The same qualitative study reports that analysts are often required to decide the accuracy of alerts produced by automated systems, that alarm validation involves repetitive manual work, and that excessive alarms can contribute to desensitization, mistrust, and reduced responsiveness.

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REST-Assured Configuration and Specifications: Writing Maintainable API Tests

Jun 25th 2026, 13:00 by Faisal Khatri

When working on API automation projects, one of the first things that becomes repetitive is configuring the same settings for every test. The base URL, content type, request logging, and common response validations often appear in multiple test classes. As the number of tests increases, maintaining these repeated configurations becomes difficult.

REST Assured provides specifications to solve this problem. Instead of defining the same settings in every test, common configurations and specifications can be created once and reused throughout the test suite.

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The AI Definition of Done

Jun 25th 2026, 12:00 by Stefan Wolpers

TL;DR: The AI Definition of Done

Your team has a Definition of Done for a product increment. It has none for the 20-plus AI-supported outputs that leave the team each week: status reports, stakeholder emails, release notes, and updates for the C-level. Each one carries your team’s name. “I know quality when I see it” is the standard most teams actually run by, and you cannot audit it, teach it to a new colleague, or defend it when a claim turns out to be wrong. The AI Definition of Done fixes that with one page per task class, agreed by the team, before the output ships.

Your Increment Has a Standard; Does Your AI Output?

A model turns the Jira board into a Friday status update, and the update tells an enterprise prospect that the security feature is in production. Unfortunately, it is not. The feature was descoped three months ago, but the old ticket title persisted because no one felt responsible. So the model reported the title instead of the reality. Nobody checked the claim against the release notes because nobody had agreed that someone should. The email was sent with the team’s name on the cover.

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