Systems | Development | Analytics | API | Testing

How ThoughtSpot's Marketing Team Built an Agent to Segment Their Entire Database

Marketing teams spend more time waiting on ops tickets to segment their database than they do actually running campaigns. By the time the segmentation comes back, the brief has changed, the moment has moved on, and someone is already asking for a revision. In this clip from the Thought Tank: Marketing in the Age of Agents, ThoughtSpot SVP Marketing EMEA Katie Marcham introduces the agent her team built to change that. They call it Slicy McSliceface, and it does exactly what the name suggests.

Spot flaky tests and failure trends with agentic QA | SmartBear BearQ

Wondering which of your AI-driven tests need attention right now? Watch this video to learn how SmartBear BearQ spots flaky tests and failure trends the moment they happen, so you always know exactly where to focus. Each report summarizes what happened and surfaces the issues BearQ detected, whether while exploring your app or running a scheduled test. Drill into failed tests to see exactly which runs broke and why, track trending results over time, and review open issues found across both passing and failing runs.

How to Manage and Secure AI Coding Agents

AI coding tool spend is projected to top $13 billion in 2026, compounding at more than 60% a year. These agents don't just autocomplete a line of code anymore. They plan. They act. They call tools, run commands, and touch other systems on your behalf. This is pretty different from the assistant that used to live in your IDE sidebar. And that's exactly where the risk lives. An AI coding agent is software that writes, tests, and ships code independently. This level of autonomy earlier tools never had.

API + AI Summit 2026 Recap: Helping the World Move AI

That's a wrap on API + AI Summit 2026, Kong's biggest in-person event yet. The event brought together more than 1,000 engineers, architects, and leaders in Los Angeles to discuss running AI systems in production, tackle shared architecture challenges, and swap real-world insights. Recordings from this year’s event will be available in the coming weeks..

Top ESG Software Companies for US Sustainability Reporting in 2026

Ask a sustainability team what slowed their last disclosure and the answer is usually mundane: inconsistent units, missing supplier records, emission factors applied three different ways across four business units, and no audit trail explaining why a number changed between drafts.

What five QE orgs got right about AI transformation

Not all AI transformations are equal, but when AI works well in quality engineering, the results are hard to ignore: 65% fewer major incidents, AI-generated test volume growing 6-7× in a year, or a five-step manual process replaced by three automated workflows. These are just a few of the outcomes from companies that moved past scattered AI experimentation to quality engineering that runs on a continuous, organization-wide signal.

A token is not a message: stop storing AI responses like event logs

How you store a streamed AI response decides what a client sees when the client joins partway through. A human agent taking over a support conversation, a refreshed browser, and a second device all need the response generated so far, and depending on how the response was stored, that late joiner gets the full response, fragments, or nothing. This article compares four common ways to store a streamed response, what each one gives a late joiner, and what each one costs your team.

Do AI Agents Better

See how AI agents use Model Context Protocol (MCP) with FME to connect complex enterprise and spatial data to Snowflake. In this episode of Do It Better with Snowflake, Safe Software CEO Don Murray demonstrates how FME extends Snowflake Cortex AI Agents with FME workflows for data integration, transformation, and spatial analysis. See how Snowflake + FME can help you: Connect complex data: including GIS, CAD, 3D, LiDAR, BIM, ERP, and unstructured data.

Stop re-pasting context into AI prompts: Katalon AI Knowledge Base & more | Give It a Test

Katalon True Platform's September updates are here. Anh Chu (True Platform team) walks through what's new, including a Knowledge Base for Katalon AI: upload your project docs and glossary once, and stop pasting the same background notes into every prompt. In this episode: Plus honourable mentions: Jira custom fields in Requirements, cross-project dashboards, MailSlurp OTP support for the AI runner, and console logs in TrueTest Session Replay.