5 public policy principles for data and AI
As AI's power grows, so do the public policy implications of data stewardship. These 5 principles form our public policy framework.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
The eMudhra certificate compromise: how it affects Bitrise users
On October 17, 2026, the developer world learned that the private keys of eight intermediate certificate authority (CA) certificates from eMudhra had been compromised. In this article, I’ll explain how that affects the Bitrise environment powering your Bitrise CI jobs, Build Hub runners, and Remote Developer Environments.
6 Vibe Coding Security Tools for Enterprise Engineering Teams
AI coding assistants are changing how enterprise software gets built. Developers can generate applications, refactor code, install dependencies, and connect external services through natural-language instructions. But the same tools that accelerate development can also access sensitive files, execute commands, and introduce unverified components into corporate environments.
How AI Is Changing the Role of the Modern QA Engineer
If you started in quality engineering decades ago, your whole mental model was forged in deterministic logic: assert(actual === expected). You took a business requirement specification, mapped out boundary values, wrote explicit test steps in TestRail or Jira, and automated them in Selenium, Cypress, or Playwright. In traditional QA testing, if an input of 2 + 2 yielded anything other than 4, you opened a severity-1 blocker, attached the stack trace, and kicked the build back to the developers.
Tricentis Labs: Agentic app exploration and exploratory testing
Modern applications move faster than traditional testing can keep up with. Teams inherit apps they did not build, ship on tight timelines, and release AI-generated code that no one has fully tested, so the gap between what gets built and what gets verified keeps growing.
AI Workspace + Cursor: Generating a consistent test base from your code
Prompting your agentic IDE to write tests gives you different steps and different results every time. The result is inconsistent and low-quality test cases. Combine AI Workspace's agentic workflows with your Cursor IDE to generate a consistent, reusable test base straight from your code repository. In this walkthrough, Product Marketing SVP Ryan Yackel will show how Tricentis generates test cases from a GitHub repo, stores them in qTest, and runs tests against a desktop application.
AI Needs to Know What Your Data Means, and Whether to Trust It
Over the past year, nearly every data and analytics vendor has made the same argument: AI agents need business context. Give a model enterprise data without telling it how the business defines revenue, margin, or an active customer, and it will give confident answers to the wrong questions. I agree. But definitions alone are not enough.
AI Assisted Development Explainer
AI is transforming software development, but it can be costly and hard to maintain without clear direction. Appian addresses this with spec-driven development: use AI to extract business logic and create visual, collaborative specifications. Then, let agents build and update apps with alignment and control, optionally integrating external agentic tools, so critical applications are built to last.
Your AI Analyst Is Now in Microsoft Teams: Here's How It Works
Your governed data is only useful if people can access it where decisions actually happen. For most teams, that's not a BI tool… it's Microsoft Teams. In this demo, watch how Spotter, ThoughtSpot's AI analyst, works directly inside Teams: in direct messages, group chats, and collaborative channels. Ask a question in natural language, and Spotter pulls from your governed data models to return an answer, right in the thread. Every answer names the model it came from, so anyone can verify the number instead of taking it on faith.
Your AI Analyst Is Now in Slack: Here's How It Works
Most data questions come up in Slack. Most data answers require leaving it. In this demo, watch how Spotter, ThoughtSpot's AI analyst, works directly inside your Slack workspace, in direct messages, threads, and public channels. Ask a question in natural language, and Spotter pulls from your governed data models to return an answer with high-level insights and relevant artifacts (images, PDFs, and CSVs), right where the conversation is already happening.