![How We Built a System for AI Agents to Ship Real Code Across 75+ Repos [Part 2 of 2]](/cdn-cgi/image/width=1200,quality=75,format=auto,fit=cover/https://www.mabl.com/hubfs/Geoffs%20Blog%20Featured%20Image%202.png)
How We Built a System for AI Agents to Ship Real Code Across 75+ Repos [Part 2 of 2]
mabl has operationalized AI agents across more than 100 repositories using a four‑phase pipeline—analysis, planning, implementation, and review—integrated with Jira. Confidence‑based gating reduces implementation failures by roughly 60 % and forces human oversight before code merges. Between October 2025 and March 2026 the system drove a 291 % jump in PR velocity, lifted AI‑assisted commits from 17 % to 70 %, and more than doubled monthly production releases, all without adding headcount. The rollout highlights how structured AI orchestration can scale developer productivity while keeping safety controls.
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Introducing Active Coverage: Quality That Keeps Pace with Agentic Development
mabl announced Active Coverage, a self‑building, self‑running, self‑healing test automation platform designed for AI‑driven development. The solution stitches together test authoring, failure analysis, recovery and execution into a single autonomous loop, eliminating manual handoffs. Key capabilities include Agent Instructions, Cloud...
When AI Writes Code, Who's Accountable for Quality? | Mabl
AI coding assistants such as Claude Code and Copilot now generate features and tests in minutes, dramatically boosting engineering velocity. However, when test outcomes become the sole decision signal for autonomous agents, organizations face hidden risks like logic drift, excessive manual...