Systems | Development | Analytics | API | Testing

keploy

How To Use Copilot In Software Testing: A Practical Guide For Testers

Jan 21, 2026 By Keploy In Keploy
Software testing is critical in assessing the quality of apps, testers oftentimes have to deal with limited resources when it comes to creating tests, as well as repetitively creating tests for all feature coverage. These factors lead to a significant reduction in both the speed of development and efficiency in the testing process.
Read Post
appian

Appian Supercharges SAP with Serious AI

Jan 21, 2026 By Gregg Aldana In Appian
If you’re an SAP customer, you’ve probably heard the same pitch more than once: just wait a little longer. Your migration to S/4HANA will unlock the agility you need. Your SAP Business Technology Platform (BTP) investments will catch up soon. Your workflows will get faster. Your data will become more accessible. Just a little more time. But what if you can’t wait? What if your supply chain teams are buried under manual work?
Read Post
kong

KAi Just Got a Major Upgrade, Powered by the New Kong Konnect MCP Server

Jan 21, 2026 By Alex Drag In Kong
KAi, the AI assistant inside Kong Konnect, just got significantly more capable. Today, we're announcing an enhanced beta version powered by the new Kong Konnect MCP Server — a shared infrastructure layer that also opens up your API platform to IDE copilots and custom agents. The result? KAi can now do things it couldn't before, and those same capabilities are available wherever you work. If you've used KAi before, you'll notice the difference immediately.
Read Post
kong

What is a MCP Gateway? The Missing Piece for Enterprise AI Infrastructure

Jan 21, 2026 By Kong In Kong
AI agents are spreading across organizations rapidly. Each agent needs secure access to different Model Context Protocol (MCP) servers. Authentication becomes complex. Scaling creates bottlenecks. The dreaded "too many endpoints" problem emerges. You face a classic AI infrastructure headache. The numbers tell the story. Organizations using AI in at least one business function jumped from 55% to 78% in just one year. Generative AI usage specifically rose from 33% in 2023 to 71% in 2024.
Read Post
Sponsored Post
speedscale

Peeking Under the Hood with Claude Code

Jan 20, 2026 By Matthew LeRay In Speedscale
Claude is one of the go-to AI-native code editors for developers. Because it's a simple chatbot interface housed inside a familiar CLI, it provides a pretty smooth path between traditional IDEs and agentic AI. But what's actually happening behind the scenes when you ask it to write code, generate a test, or debug an issue? Who and what is it talking to behind the scenes? Can I prevent data leakage or do I need to add another layer to my tin foil hat? To answer these questions, I used proxymock to inspect the network traffic flowing from the Claude IDE.
Read Post
bitrise

From suggestions to fixes: How Bitrise AI lets teams ship faster with control

Jan 20, 2026 By Daniel Balla In Bitrise
For many developers, AI coding assistants are already as fundamental as a terminal window or version control system. Data from DORA shows that 90% of IT professionals are using AI at work. StackOverflow’s 2025 Developer Survey found that over half of professional developers use AI daily.
Read Post
perforce

Talk to Your Test Data: Improve Test Data Management with the Perforce Delphix MCP Server

Jan 20, 2026 By Perforce In Perforce
Many technology leaders face a persistent bottleneck: delivering the right data to the right people at the right time. Despite significant investments in test data management and automation, developers often wait for database refreshes, compliance checks, and answers from infrastructure teams. These delays directly reduce development velocity. A recent shift has occurred in how developers work. AI agents, such as Claude Desktop and Cursor, are now essential coding tools.
Read Post
antino

Pre-Training vs Fine-Tuning vs RAG: Which AI Approach Fits Your Business in 2026?

Jan 16, 2026 By Radhakanth Kodukula In Antino
Every organization today is racing to embed AI into its core, yet the real question isn’t which model to choose, but how to build an AI capability that truly aligns with your business goals. Should you invest months in training a proprietary model to gain full control and differentiation? Or would adapting a pre-trained model strike a better balance between performance and time-to-market?
Read Post

Copyright © 2026 OpsMatters™. All rights reserved.