AI Is Only as Good as Its Context #shorts
AI doesn’t run on prompts alone—it runs on context. Architecture, security, and governance shape how AI makes decisions. Better context leads to safer, smarter outcomes.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Entering the agentic age: Don't wait to get started
Delivering value now with data integration, the right data platform, and generative and agentic AI.
Introducing Agent-Flavored Markdown (AFM): No Code, Portable AI Agents
Advances in large language models (LLMs) and their widespread accessibility have transformed both what software can do and how we build it. The use of LLMs has quickly evolved from simple single-turn interactions to AI agents that reason, use tools, manage state, and operate autonomously.
Top 23 Test Automation Frameworks in 2026
There was a time when software teams shipped code hoping nothing would break, relying on slow manual testing and last-minute sanity checks. Those teams that failed to adapt were quickly left behind as release cycles shortened and user expectations skyrocketed. Today’s high-performing engineering teams use a top automation testing framework to deliver rapid feedback, reliable regression coverage, and continuous validation at scale.
Tracking testing progress with reports | Zephyr
SmartBear Zephyr is the Jira-native test management and automation platform that empowers your team to deliver better software, faster. Its reporting and dashboard capabilities provide real-time visibility into your quality metrics, so you always know the status of your release. This short demo video shows you how to navigate the Zephyr Reports tab and build customized Jira Dashboards. Whether it’s via high-level execution summaries or deep-dive traceability reports, you can track coverage and identify testing bottlenecks instantly.
How to create a test cycle | Zephyr
SmartBear Zephyr is the Jira-native test management and automation platform that empowers your team to deliver better software, faster. Organizing your testing into Test Cycles is the best way to align your QA efforts with specific sprints, releases, and versions, ensuring your team stays focused and on schedule. This short demo video guides you through the process of setting up and populating your Test Cycles. You’ll learn how to define execution windows, link cycles to specific release versions, and pull in test cases from across different Jira projects to create a unified testing effort.
Xcode 26.3 coding intelligence: First impressions
Senior & Staff engineers Ben Boral and Oliver Falvai from Bitrise discuss the initial impressions of the new coding intelligence features in the Xcode 26.3 Release Candidate. They have been experimenting with the new features - see what they think! Bitrise provides a full-stack, vertically integrated mobile DevOps solution that unites the tools, processes and testing frameworks engineering teams need to build best-in-class mobile experiences. Over 400,000 developers use Bitrise’s products: Bitrise CI, Build Cache, Release Management, and Insights.
The next evolution in QA: How AI is changing software testing
Shipping high-quality software quickly is challenging. QA professionals are facing pressure to test more, faster in a world where GenAI is pushing delivery – all while trying to cut costs. For years, manual testing and traditional automation tools like Selenium have been the standard. But both come with challenges. Manual testing alone can be slow and prone to errors, while Selenium and similar tools require coding expertise, need constant script maintenance, and are easily broken by UI changes.
What Your CISO Needs to Know About LLM Database Access
Here’s what you need to know: Bottom Line: Treat LLMs as untrusted clients. Secure database access with strict governance, API controls, and robust monitoring to mitigate risks without sacrificing productivity.
Secure AI at Scale: Prisma AIRS and Kong AI Gateway Now Integrated
In today's digital landscape, APIs are the backbone of modern applications, and AI is the engine of innovation. As organizations increasingly rely on microservices and AI-powered features, the API gateway has become the critical control point for managing traffic. But as LLM/GenAI and MCP requests flow through these gateways, they bring a new wave of security challenges.