Systems | Development | Analytics | API | Testing

databox

Why Databox MCP Wins for AI Analytics Over Individual Connector MCPs

Mar 12, 2026 By Alexander B. Pavlinek In Databox
The Model Context Protocol (MCP) has given AI assistants something they’ve never had before: a standardized way to pull live data from external systems. Instead of just generating text, an AI agent can now query your CRM, check ad performance, or pull revenue numbers in real time. The industry’s response has been predictable. Every major platform is racing to build their own MCP server.
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ably

Resume tokens and last-event IDs for LLM streaming: How they work & what they cost to build

Mar 12, 2026 By Amber Dawson In Ably
When an AI response reaches token 150 and the connection drops, most implementations have one answer: start over. The user re-prompts, you pay for the same tokens twice, and the experience breaks. Resume tokens and last-event IDs are the mechanism that prevents this. They make streams addressable – every message gets an identifier, clients track their position, and reconnections pick up from exactly where they left off. The concept is straightforward.
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Meet Bitrise AI: 1-minute feature tour

Mar 12, 2026 By Bitrise In Bitrise
In this fast demo, Naveen Nazimudeen walks you through the Bitrise AI features. Unlike typical agents that only suggest changes, Build Fixer applies the fix for you, then runs a build to validate and opens a PR. Code Reviewer automatically reviews new PRs with zero noise. Bitrise provides a full-stack, vertically integrated mobile DevOps solution that unites the tools, processes and testing frameworks engineering teams need to build best-in-class mobile experiences. Over 400,000 developers use Bitrise’s products: Bitrise CI, Build Cache, Release Management, and Insights.
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speedscale

AI Coding Agents Have a UX Problem Nobody Wants to Talk About

Mar 11, 2026 By Kush Mansingh In Speedscale
The pitch was simple: let AI write your code so you can focus on the hard problems. Three years into the AI coding revolution, and developers are focused on hard problems alright, just not the ones anyone expected. Instead of designing systems and solving business logic, engineers in 2026 spend a startling amount of their day managing the AI itself. Should you use Fast Mode or Deep Thinking? Haiku or Opus? Cursor or Claude Code or Windsurf? Should you write a SKILL.md file or a custom system prompt?
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rainforest

The top 11 AI-assisted automated testing tools for QA in 2026

Mar 11, 2026 By Lauren Harold In Rainforest
When it comes to QA, AI-powered automated testing tools promise more speed, better coverage, and lower maintenance. But they don’t all solve the same problems, and their approach to solving problems can be fundamentally different. Some platforms lean heavily into autonomy. Others focus primarily on speed or aggressive self-healing. A smaller group applies AI in specific parts of the workflow while preserving test execution reliability and human control.
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InsightSoftware

Why Your AI Pilot Won't Make It to Production (And What to Do About It)

Mar 11, 2026 By InsightSoftware In InsightSoftware
Most AI pilots fail to reach production not because the models don’t work, but because enterprises struggle with data governance. While pilot-phase AI projects demonstrate impressive results in controlled environments, they hit governance walls when moving to enterprise-scale deployments. This post examines why AI initiatives stall before production and provides a governance-focused approach for breaking the cycle.
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