Agentic AI is changing how software gets built, but most development processes haven’t caught up.
The old relay race, PRD to mockup to user story to code was built around a constraint that is now dissolving. Forge is a rethinking of how software gets built when that constraint no longer applies: governance as infrastructure, knowledge as a maintained asset, and every role contributing directly to the artifact.
Is this whitepaper for you?
If you’re an engineering or technology leader facing questions like these:
- AI coding assistants are increasing output, but are they also creating more review overhead?
- Scrum ceremonies feel optimized for handoffs that AI is making obsolete.
- Senior engineers spend more time reviewing code than designing systems.
- You’re trying to balance AI adoption with governance instead of simply restricting access.
What you’ll learn
- Why governance, not restricting AI tools, is the key to scaling AI-assisted development.
- How Forge enables every role to contribute directly to working software.
- The four knowledge layers AI agents need to produce reliable, high-quality code.
- A streamlined delivery cycle that reduces unnecessary ceremonies.
- Lessons from a 12-week project simulation showing where AI-enabled teams succeed, and where they fail.
- How Forge compares with Scrum and SAFe, and when it isn’t the right fit.
- Five common adoption pitfalls and how to avoid them.
AI is changing software delivery faster than most organizations can adapt.
Your developers already have AI coding tools. The competitive advantage now comes from how you govern them, capture knowledge, and redesign software delivery for an AI-assisted workforce.
Download the Forge whitepaper to learn how engineering organizations can move beyond traditional SDLC models while maintaining quality, control, and velocity.