NEW LIVE WEBINAR – PRACTICAL, ENGINEERING-FOCUSED
In this practical session, you will learn five proven development practices, adapted for working with AI. Together, they help individuals and teams gain the benefits of AI’s speed while preserving human judgment, shared understanding, and responsibility for the code.
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60-min live session · Interactive · Time for Questions.
AI Changes the Speed, Not the Responsibility
AI is extraordinarily capable at generating implementations, suggesting alternatives, applying mechanical changes, and helping us explore unfamiliar code. It can accelerate a strong development system.
It can also accelerate confusion, duplication, fragile design, and code that nobody fully understands.
The difference is not the AI tool. The difference is how we work.
In this practical and thought-provoking webinar, I will show you how five proven development practices help teams collaborate with AI while keeping humans in control of intent, evaluation, and design.
You will leave with a practical operating model for building software with AI without surrendering the engineering discipline that makes speed sustainable.
Meet Your guide
David Scott Bernstein has trained more than 10,000 professional developers from organizations including Microsoft, IBM, and Yahoo. He is the author of *Beyond Legacy Code* and co-author of *Prompt Engineering for Everyone with ChatGPT*.
Today his work focuses on helping developers and teams collaborate effectively with AI while strengthening human understanding, sound engineering judgment, and the practices that make software changeable.
AI is making it possible to generate code faster than teams can understand it.
That changes the central challenge of software development. Producing code is no longer the bottleneck. The challenge is preserving the shared understanding, tests, design quality, and human judgment needed to change that code safely.
This webinar explores a simple but important idea: **AI does not eliminate engineering discipline. It increases its value.**
what you'll learn
- How to keep AI-assisted development steps small, understandable, and verifiable
- Why larger AI-generated changes create a larger verification burden
- How to use CLEAN as a shared vocabulary for evaluating generated code
- How pairing and mobbing with AI can spread skills and judgment across a team
- Why test-first development remains essential when AI can generate many tests or implementations at once
- How outside-in tests shape stable interfaces and executable specifications
- How to use AI for refactoring while retaining human responsibility for meaning and design
Most organizations are measuring AI by how much faster people produce code. The deeper question is whether teams can continue to understand, trust, and change what they produce. Weak development practices allow AI to amplify risk. Strong practices allow AI to amplify learning, collaboration, and capability. Teams that understand this distinction can move faster without trading away the qualities that make software sustainable.
If you are a software developer learning how to work effectively with AI. If you are a technical lead or architect responsible for code quality and system design. If you are an engineering manager helping a team adopt AI without fragmenting knowledge or lowering standards. If you practice test-first development, refactoring, Extreme Programming, or evolutionary design and want to understand how these practices change with AI. If you want more than faster code generation: you want software your team can understand, trust, and continue to change.
When you attend this webinar, you’ll:
- Gain a practical operating model for developing software with AI
- Learn techniques for keeping AI-assisted changes observable and reversible
- Understand how collaboration spreads AI capability instead of concentrating it
- Gain a vocabulary for evaluating whether generated code will remain easy to change
- See how test-first development and emergent design evolve in AI-assisted work
- Leave with practices you can apply immediately to both new and legacy code
Details
– Length: 45- to 50-minute presentation plus Q&A
– Format: Live, practical, and discussion-oriented
– Experience level: Useful for developers, technical leaders, and engineering managers
– Technical background: Software development experience is recommended; prior AI expertise is not required
– Extended formats: The session can be offered privately for teams and expanded to 90 or 120 minutes for deeper discussion and examples
Testimonials
“Thank you David! You gave me a different way to think about AI and I will be modifying how I interact with it to improve its responses.” — Kortni Kelly
“Really top notch content. I will look for more from David!” — Andrew Sisson
“Great presentation, thanks for the information and for all the passion to share it,” — Gloria Suasnavar
FAQ
- Do I need experience developing with AI? No. The session will give you a practical foundation for working with AI while preserving sound development practices.
- Is this only for software developers? The examples focus on software development. Technical leads, architects, and engineering managers will also gain a useful framework for guiding AI adoption and evaluating its effects on teams and codebases.
- Is this a presentation about prompting? No. Prompting is only one small part of AI-assisted development. This session focuses on the practices that help teams create understandable, tested, and changeable software with AI.
- Will this webinar be recorded? Yes. A link to the recording will be sent to registered participants after the webinar.