Systems | Development | Analytics | API | Testing

A QA's Complete Guide to LLM Evals: What You Need to Know

Let’s get straight to the point—this post is vital and couldn’t have come at a better time. As QA professionals, we’ve always been the gatekeepers of software quality. But with the rise of AI and LLMs, our role is evolving. Writing evaluations—assessments of AI systems—is quickly becoming a core skill for anyone working with AI products, and soon, this will include nearly everyone in tech.

AI Agents and Enterprise Data: The Missing Link in AI Success

Organizations everywhere are in hot pursuit of competitive advantages, seeking out and implementing artificial intelligence technologies ranging from GenAI to sophisticated machine learning systems. Yet, despite massive global investments that are projected to reach $375 billion in 2025, many enterprises remain disappointed with their AI initiatives’ real-world results. Why is it that so many AI projects are failing to deliver on their promise? The answer isn’t in the algorithms themselves.

What Are AI Agents? Definition, Types, Applications for Enterprises, and More!

Teams are spending as much as 71% of their time on administrative tasks and manually entering data. But what if there was a way to automate all their repetitive work so they could focus on performing higher-order tasks, creating value, and driving actual ROI? That’s what AI agents can do for you.

Agentic AI in Software Testing: The Next Evolution in Automation

With Deloitte predicting that 25% of companies using Generative AI will launch agentic AI pilots or proofs of concept in 2025, is your testing strategy ready for the agentic revolution? This highlights the pace at which the modern software development industry, already demanding continuous operational speed improvements, heightened efficiency, and superior product quality, is turning to advanced AI.

Best Opensource Coding Ai

AI has become the talk of the town nowadays, right? There are tons of AI tools available for different tasks, and new advancements are coming up daily like vibe coding. But how do you actually do vibe coding? Or how do you try out these models? You could use tools like ChatGPT or Claude, but they come with restrictions, and you often need to pay to access full features. What if you don’t want your data to become part of their training models? That’s where open source coding models come in.

Smoke Testing vs Sanity Testing: What's the Difference?

Say you’re a new developer, and you were just hired to test an e-Commerce website before it goes live. You want to make sure that the login function is working. Is it time for a smoke test or a sanity test? Well, it depends. If a login bug was recently fixed, then you’ll want to run a sanity test to check whether users can successfully log in with valid credentials or if the bug broke the login’s functionality.

APIs Over IPAs 18: Platform Engineering and Reducing Operational Overhead with Nuwan Dias, WSO2

In this episode, Nuwan Dias, Vice President and Deputy CTO at WSO2, joins to explore what effective API lifecycle management really looks like. Drawing on his deep experience building API platforms, Nuwan outlines the key pillars of successful API programs—from strategy and governance to security, testing, and deployment. He shares how organizations can operationalize API-first thinking at scale, and the role of dedicated API teams in enabling this shift.

Data compliance in 2025 - what you need to know

Data leaders face a high-stakes challenge as stricter global and state-level privacy laws, like the American Privacy Rights Act (APRA), ramp up financial penalties — potentially up to 4% of a company’s global revenue — for compliance failures. Organizations must prepare for increased accountability and standardization in data privacy, sovereignty, and ethical AI governance, all of which demand stronger data safeguards and transparent practices.

Key Benefits of APIs For Pharmaceutical Companies

Many pharmaceutical companies have been around for decades and must continually adapt to a rapidly evolving, technology-driven world. Even those that keep pace with digital trends often struggle with data silos and disparate systems, making it difficult to share information across platforms. This fragmentation hinders their ability to meet patient expectations, accelerate drug launches, and develop personalized therapies.