Systems | Development | Analytics | API | Testing

antino

AI Agents Deployed, but what about cost optimization?

Jun 26, 2026 By Radhakanth Kodukula In Antino
AI agents are no longer a pilot-stage bet. As of 2026, 80% of enterprises have at least one production AI agent deployed. The global AI agents market has crossed $10.91 billion and is sprinting toward $52.62 billion by 2030. The cost-per-task economics are staggering: a human-handled customer support ticket costs $4.18 on average. An AI agent resolves the same ticket for $0.46. That is a 9x cost reduction, right there.
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ably

Is AI making your teams better, or just busier?

Jun 26, 2026 By Amber Dawson In Ably
AI adoption programs tend to end in the same place. Tools are accessible, usage is up, and there's a dedicated Slack channel for wins. Six months later, nothing about how the team works has fundamentally changed. People are doing the same things – just slightly faster. And it’s easy for programs to stall when you’re measuring the wrong thing. Adoption (whether people have access and whether they're using the tools) is visible and easy to report.
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smartbear

AI Coding Tools and API Governance: Here's Why You Need Both.

Jun 26, 2026 By Daisy Priya In SmartBear
GitHub Copilot, Claude, and Cursor have become genuine superpowers for API development. They draft OpenAPI definitions, generate endpoints, propose schema changes, and write test cases — all from inside the IDE, in real time. Teams using these tools are generating API definitions faster than most thought possible even a few years ago. That velocity is real, and it’s reshaping how engineering teams think about their toolchain.
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bugfender

Rubber Duck Debugging: How to Find and Fix Logic Bugs

Jun 26, 2026 By Aleix Ventayol In Bugfender
Rubber duck debugging allows us to discover our own coding errors by retracing our steps. Instead of relying on complex black-box tools, we simply explain our own logic until the problem reveals itself. This is one of the most straightforward debugging techniques around, and it can be easily enhanced by AI tools.
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smartbear

Mobile testing, reimagined: How Reflect's Mobile Testing Changes QA

Jun 25, 2026 By Pratik Pal Bariha In SmartBear
Mobile application users expect flawless experiences on every device, every OS version, and every screen size, and they have little patience for anything less. Yet for QA teams, achieving that level of coverage traditionally means wrestling with brittle automation scripts, complex Appium setups, and endless device fragmentation. Even after all this manual effort, your mobile app quality could contain unseen gaps.
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Digital Twins for Devs & AI Agents - Record, Replay & Catch Regressions | Keploy

Jun 25, 2026 By Keploy In Keploy
Give your developers — and your AI agents — a digital twin of your live environment. Keploy records real traffic from your live services (no production access, nothing to spin up) and replays it as a faithful twin, so you can continuously verify behavior and catch regressions before they ship. In this demo: record a live service, turn that traffic into integration tests and mocks automatically, replay everything against digital-twin sandboxes, and wire it into CI for continuous verification.
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Build resilient end-to-end tests with AI agents in SmartBear Reflect | Demo Den

Jun 25, 2026 By SmartBear In SmartBear
See how SmartBear Reflect uses agentic AI to build end-to-end tests in minutes and keep them resilient as your application changes. In under 20 minutes, Reflect co-creator, and SmartBear Director of Product Management, Todd McNeil walks through live test creation across web and mobile, with zero fluff.
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