Coding got faster. Delivery didn't. What happens next in Agentic engineering
AI agents can already execute engineering work. The bottleneck moved. It is no longer writing code, it is running the engineering process.
Three things break at once when you try to scale AI-assisted delivery on a real system.
📈 Scale. There is more work than anyone can plan. Boards, standups, and sprint mechanics turn the engineering leader into the coordination engine, and the bottleneck.
🔒 Trust. There is more code than anyone can verify. Output exists, but no record of what was built, why, and whether it is safe. Trust erodes as AI volume grows.
🧭 Context. No system holds the canonical truth of how the whole system works. On a brownfield codebase the architecture and past decisions are not in the agent's context, so the agent assumes what does not exist, drifts, and quietly regresses what works.
This webinar does not stop at the problem. We introduce a new model for how software delivery organizations operate, and show the platform underneath it.
The Agentic Engineering OS is the operating layer that lets agents run the engineering process continuously, with people making the decisions that matter. It sits above the coding harnesses your developers already use, Claude Code, Cursor, Codex, and Copilot, and drives them with your context, rules, and acceptance criteria.
🎥 What you will see
Why the bottleneck moved from writing code to running the process, and why more agents alone do not close it
What an Agentic Engineering OS is, and how it differs from a coding harness and from another coordination tool
The three layers, live on a real brownfield codebase: the Knowledge Core reading a legacy system (Context), requirements traced to tests and code both ways in the Ledger (Trust), and the "Your move" decision queue in Mission Control (Scale)
Human on the loop in practice: the 5 moments where a person decides, and the system doing the rest
One shared context across harnesses: how the platform drives Claude Code, Cursor, Codex, and Copilot, so you keep the harness your developers prefer
The honest limits: what the platform does not do yet, where a human decision is still required, and what commercial beta means today
🗓 Agenda
45 minutes of session and live demo, then 15 minutes of open Q&A.
🎤 Who is presenting
Pasi Vuorio, Founder of ModernPath. 30 years shipping software, now working with CTOs on scaling AI-powered development across their teams. Keynote speaker and trainer.
We built ModernPath after 1.5 years of AI-native delivery and 20+ production apps, and we ran it on ourselves first. It took our own release timeline from 3 months to 1, same team, same quality bar, and cut human effort 10x, with the platform running coordination and routine work while people make the decisions.
🎯 Who should attend
Built for people accountable for scaling AI development at the organization level, not for individual developer speed.
CTOs, VPs and Heads of Engineering, Directors of Engineering, CPOs, and Chief AI Officers deciding how their organization operates AI-assisted delivery
Architects who want to see the shape of the system before they trust it
Lead and principal engineers who already know that hand-feeding context to an agent does not scale on a legacy codebase
✅ Know before you go
The session is live. The platform walkthrough runs on a real brownfield codebase, not a scripted greenfield demo.
Everyone who registers gets the recording, whether or not you attend.
Register above to save your seat.