Systems | Development | Analytics | API | Testing

Everyone thinks AI is getting cheaper. But is it really? At first glance, the economics of AI seem to be improving for everyone. Thanks to continued model optimization and advances in hardware, the cost of running LLMs (also known as inference) is steadily decreasing. Developers today can access incredibly powerful models at a fraction of what it cost just a year ago. But there’s a catch.

Another day, another API. Fueled by AI-assisted coding and agile workflows, the speed of innovation has never been higher. But for the compliance team? It’s panic mode. Every new API must follow a minefield of internal rules: security protocols, naming conventions, reuse policies, documentation standards. And while the dev team is flying forward, compliance is stuck doing manual reviews, chasing specs, and untangling inconsistencies often after the code is already written.

AI failures rarely look like crashes. More often, they appear as confident but incorrect answers, subtle bias, or culturally inappropriate responses.

Agentic coding tools like Cursor, GitHub Copilot, and OpenAI’s Codex are reshaping how software is developed. They enable developers to offload routine tasks and accelerate feature delivery. However, these tools also introduce new challenges – particularly in how we test and validate the code they produce.

In modern web development, speed and reliability are combined you can deploy features quickly, but without proper testing, bugs might pass through and strike real users. That is where tools like Selenium IDE fit in – they enable you to automate browser interactions without writing a single line of code. As a person who just tried Selenium IDE on a test login form, I was amazed at how simple it is to create repeatable test flows in a matter of a few clicks.

Software development teams need methodologies that enhance collaboration while ensuring quality. Behavior-Driven Development (BDD) has emerged as a powerful approach that bridges the gap between technical and non-technical team members through a shared language of expected behaviors. When implemented correctly, BDD transforms requirements into actionable test cases that serve as living documentation for your software.

One of the problems development teams experience is that when they build applications, they are unable to scale them or handle maintenance and that leads to technical debt and maintenance nightmares. Eventually, the very thing that is software architecture becomes necessary once an organization needs systems to continue to evolve, scale, and change because of the needs of the business.

Automation testing begins with a test script. Its job is to command the machine to perform each test step on your behalf. A well-written test script executes those steps exactly like how a human would, with the extra consistency, standardization, and precision of a machine. However, writing test scripts means coding, and coding can sometimes be a challenge, especially for testers who are only getting started. Let us show you how to write a test script in a simple fashion.

A test suite is a collection of test cases with similar characteristics. They are created to group test cases for a specific feature. Depending on the nuances of your product, there are so many ways to categorize test suites. In this article, we'll show you: Let's dive in!