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Company Blog
From Backlog to Code: How SDLC Guardrails Ensure Production-Ready AI Development
October 5, 2026
As generative AI and autonomous coding tools sweep through the software industry, engineering teams are experiencing an unprecedented surge in development speed. Developers can now generate thousands of lines of code in minutes. However, this rapid acceleration has exposed a critical challenge for engineering leadership: How do we ensure that AI-generated code is production-ready, secure, and fully compliant?
In a recent joint webinar, Inflectra, Axiom Studio, and Rhythmic Technologies tackled this issue head-on. Featuring Adam Sandman (Founder & CEO, Inflectra), Ranjan Parthasarathy (Founder & CEO, Axiom Studio), Chris Daniluk (Founder & CEO, Rhythmic Technologies), and hosted by Bill Brown (Axiom Studio), the expert panel delivered a live, step-by-step demonstration on taking software from an initial backlog requirement all the way to production-ready code without sacrificing quality, security, or auditability.
Building a Winning Business Case for Inflectra
October 5, 2026
The Ultimate Shortcut to Executive Approval
If you are currently contemplating the modernisation, standardisation, transformation, or consolidation of your Software Development/System Deployment Lifecycle (SDLC), Test Orchestration, or Program Portfolio Management (PPM), you know that getting budget approval requires airtight justification.
To help you secure executive sign-off, we have compiled the core data points, competitive advantages, and real-world proof of value into a pre-populated business case framework. Use this guide to satisfy procurement, security, your CTO, and prove immediate Return on Investment (ROI).
How Should AI Agents Be Evaluated Before Production?
October 1, 2026
A recent Associated Press report published by PBS NewsHour highlights growing calls for stronger, independent evaluation of advanced AI systems. As AI agents take on more complex tasks and interact with real systems, successful outputs alone may not tell the whole story. What should teams evaluate before an AI agent reaches production?
For enterprise teams, the growing discussion around AI safety and evaluation has practical implications today. AI agents can use tools, interact with external systems, maintain information across multiple steps, and take actions within larger workflows. Software quality and engineering teams therefore need ways to determine whether those agents are ready for production.
