AI Coding Tools Are Not a Software Development Process · Live July 28

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Reserve your spot for July 28.

A 45-minute live session with Nick Chase on turning AI coding spend into governed, accountable delivery you can forecast. Can't make it live? Register anyway, the recording comes to you.

Live talk and demo of a governed, accountable AI delivery model
Open Q&A, bring your hardest questions on cost, risk, and accountability
Recording and session materials sent to every registrant

Registration

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Tuesday, July 28 · 10:00 AM PT / 1:00 PM ET

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The Premise

Faster code is not cheaper or more predictable delivery. The real challenge is turning business intent into accountable change you can stand behind, across teams, cost, and risk.

Code generation is the cheap part. Everything around it, the review, the oversight, and the accountability for what ships, is where AI adoption either pays off or quietly raises your cost of delivery.

What AI coding tools give you

More code, generated faster
Individual developer productivity
Isolated experiments and pilots
Output measured in lines and velocity

What enterprise delivery requires

Safe, traceable, reviewable change
Organizational capability across teams and controls
A governed operating model for the full lifecycle
Decisions tied to outcomes, risk, cost, and system impact

What You'll Learn

Eight things you'll walk away with, in one session.

Investment, or just cost?

How to tell whether your AI coding spend is improving delivery or quietly adding to it.

Speed vs predictability

Separate developer speed from delivery you can actually forecast and budget for.

Know what to ask before you invest

The questions that tell you whether a tool, agent, or managed service will actually improve delivery, before you fund it.

Make delivery accountable

What it takes to make AI delivery predictable and accountable, not just faster in spots.

Where accountability pays

Where human oversight and sign-off protect both cost and quality as AI does more of the work.

Demand more from managed services

Where headcount, ticket handling, and reactive maintenance stop being enough, and what to expect instead.

From experiments to operating model

How to move from funded AI pilots to an accountable operating model for real software work.

One shared language

How finance, operations, and engineering tie AI delivery decisions to outcomes, risk, and cost, instead of tool hype.

The Format

A working session, not a lecture.

The case, made live

Nick walks through why AI coding tools aren't a software development process: the argument, the evidence, and where the cost actually hides.

Live demo

See what a governed, AI-managed software lifecycle looks like in practice, with human sign-off and accountability built in.

Open Q&A

Bring your hardest questions about governance, risk, and adoption. The session ends when the useful questions do.

45 minutes plus Q&A, live. Bring your engineering lead, they'll want to pressure-test it. Can't make it? Register anyway, every registrant gets the recording.

Your Host

Led by the person building the answer.

Nick Chase, Head of AI and Data at CloudGeometry

Nick Chase Head of AI & Data, CloudGeometry · Product Lead, AI-MSL

Leads the Data workstream of the LF AI & Data Foundation's Generative AI Commons

Head of AI & Data · Product Lead, AI-MSL

Nick Chase

Nick leads CloudGeometry's AI and data organization, spanning client delivery, pre-sales, internal products, and the company-wide AI strategy. He is the product lead for AI-MSL, and spends his days on exactly the problem this session covers: making AI-powered software delivery governable, accountable, and predictable at enterprise scale.

Architected and launched the CloudGeometry AI Agent Platform, leading CG's entry into the AI agent space with CrewAI, LangChain, LangGraph, and LangFlow.
Shapes technology roadmaps and oversees agile execution of production AI solutions for enterprise clients.
Builds strategic partnerships with industry leaders and the open-source community to co-develop exportable AI modules.
Former AI/ML Practice Director and Senior Director of Product Management, with deep roots in product strategy and technical content.

Tuesday, July 28 · 10:00 AM PT. 45 minutes plus live Q&A. Register and the calendar invite and recording come to you.

Who It's For

Built for the people who have to answer for AI adoption.

Technology Leadership

CTOs, VPs of Engineering, Heads of Platform

You're accountable for delivery outcomes across teams, not just developer satisfaction scores. You need AI to improve the system, not just the individual.

Security · Compliance · Architecture

The teams who have to say yes

You're asked to approve AI-generated change without a clear picture of review, traceability, and control. This session gives you the framework to engage on your terms.

Business & Delivery Leadership

CIOs, product and transformation leaders

You're funding AI adoption and fielding the hype. Leave with a shared language for tying AI delivery decisions to outcomes, risk, and cost.

The Bottom Line

The winners won't be the organizations that generate the most code. They'll be the ones that govern software change the best.

Join us to understand how to move beyond AI coding experiments toward a managed, accountable, enterprise-ready software lifecycle.

Save my seat

Looking for a coding-assistant comparison or a tool tutorial? This isn't that session. It's about the operating model around the tools.

About CloudGeometry. CloudGeometry is a strategic engineering partner helping enterprises adopt AI-powered software delivery with governance built in. AI-MSL, its platform and managed service, maintains, modernizes, and extends production software systems, with human sign-off at every lifecycle gate, full traceability of every change, and all code and assets remaining under client ownership and control.