Blogs

Ask a testing team how they know a test has worked, and you'll usually get a technical answer. But strip the question back and something more fundamental sits underneath it: how do you know what the right answer should be in the first place?

Test automation is one of the most overloaded terms in enterprise software. Ask 10 people what it means and you'll get 10 different answers. Recording clicks and replaying them. Writing thousands of lines of code to mimic the front end. Image recognition, screen scraping, bots that "watch" how ...

Every trading organisation we meet has test automation. Most of them have automation that was working six months ago and is slowly, quietly failing now.

When an Energy Trading and Risk Management (ETRM) upgrade slips, the post-mortem rarely blames the upgrade itself. It blames testing.

Artificial Intelligence (AI) has changed how software is built. Code appears faster. Release cycles compress. Backlogs move. Most of our clients can point to specific features that landed in days rather than weeks.

Artificial Intelligence (AI) is fundamentally reshaping how software is built. Code is being generated at remarkable speed. Features are appearing faster than anyone expected. Release cadences that once felt ambitious now look leisurely.

Why Triangle’s self-evolving tests are a ‘game changer’ for trading platforms Most trading organisations don’t plan for test maintenance. It’s not in the budget. It’s not in the resourcing model. In fact, it’s rarely even recognised as a problem. Until it becomes one.

Most trading organisations don't plan for test maintenance. It's not in the budget. It's not in the resourcing model. It's rarely recognised as a problem at all, until it becomes one.

The slow leak: why testing becomes the thing that holds you back.

Most teams don’t set out to build ineffective test automation.