Systems | Development | Analytics | API | Testing

Learn how AI handles different types of testing, from simple unit tests to complex end-to-end setups. Discover where AI succeeds in writing test code and where human strategy is still needed. Learn more: speedscale.com.

How do you create a monthly executive report with AI? Run the Executive Decision Brief skill in Databox. Genie, the Databox AI Analyst, reads your connected metrics and writes a one-page leadership brief: the executive takeaway, wins, risks, contradictions between metrics, and three "Should we..." decisions to discuss. It reads in about 90 seconds, and the same skill runs in Claude through Databox MCP.

You can talk an AI model into breaking its own rules. Sometimes, all it takes is knowing what to say. Dr. Peter Garraghan has spent years studying how attackers exploit AI systems, and some of his findings are surprisingly human. AI models can be manipulated through language, using techniques that resemble the social engineering tactics cybersecurity professionals have dealt with for decades.

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.

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.

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.

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.