AI Software Factory: Measure and Forecast Software Delivery While Increasing Automation

Challenges

  • AI adoption without measurable business results.
  • Defects and instability reducing team capacity.
  • Limited visibility into delivery bottlenecks and workflow.
  • Overreliance on AI without proper governance.
  • Difficulty proving return on AI investments.

Solutions

  • Implement an AI Software Factory orchestration model.
  • Prioritize quality and stability before increasing speed.
  • Automate repetitive, low-complexity tasks with AI.
  • Use delivery scorecards to track performance and ROI.
  • Introduce AI incrementally, starting with low-risk workflows.

Benefits

  • Improve software delivery throughput with AI-driven workflows.
  • Reduce defects and production incidents before they impact delivery.
  • Gain end-to-end visibility into the software delivery process.
  • Measure AI ROI with meaningful delivery metrics.
  • Free engineers to focus on high-value engineering work.

Many organizations are investing in AI tools, but few are seeing measurable improvements in software delivery. In this webinar, Jeffrey Palermo introduces the AI Software Factory—an orchestration pattern that helps software leaders improve throughput by combining AI automation with quality, stability, and end-to-end visibility.

Through live demonstrations, you’ll learn how AI can automate repetitive work, enrich planning and testing, streamline production incident response, and provide the metrics needed to measure delivery performance and AI ROI. The session also explores why quality and stability are essential before scaling AI and shares practical guidance for implementing AI in a way that supports long-term software delivery success.