Free Live Webinar for Software Developers, Technical Leaders, and Teams Working with AI
Live Online Webinar
Cost: Free
Designed for Developers, Technical Leaders, and Teams
45-Minute Presentation + 15-Minute Q&A
Includes AI Systems Thinking Checklist
Reserve My Free Seat → Jump to Registration
Transform How You Think with AI
AI can write code.
Can your team still understand and change what it builds?
AI coding tools are becoming extraordinarily capable. They can generate features, tests, screens, APIs, integrations, and entire applications faster than most of us imagined even a few years ago.
That is exciting.
It is also dangerous if we think working code is the finish line.
The real question is not whether AI can help us build faster. It can. The deeper question is whether we are using AI to create systems we can understand, verify, change, and extend over time.
In this live webinar, I will show developers and technical leaders why the future of software development is not just AI coding. It is systems thinking.
Meet Your guide
Hi, I’m David Scott Bernstein.
I have spent much of my life helping software developers build systems that are easier to understand, verify, and change. I have trained more than 10,000 professional developers in Extreme Programming, test-first development, domain modeling, design patterns, refactoring, and the practices that make software sustainable.
I am the author of Beyond Legacy Code and co-author of Prompt Engineering for Everyone with ChatGPT. My current work explores how developers can collaborate with AI without giving up the fundamentals that make software development meaningful: understanding, craft, judgment, feedback, and human agency. I do not believe AI makes these things obsolete. I believe AI makes them essential.
This webinar explores a simple but important idea: AI access is not AI capability. Organizations that thrive in the coming years will not merely adopt AI tools. They will develop new ways of thinking, learning, and collaborating together.
In this engaging session you’ll see live demonstrations, practical examples, and emerging patterns from organizations that are moving beyond prompting toward collaborative intelligence.
what you'll learn
- A clearer way to explain why code quality matters more now, not less
- A practical language for discussing AI, testability, and cost of change with managers
- A deeper understanding of why domain models matter
- Questions you can ask AI to help discover better models and responsibilities
- A way to evaluate generated code without becoming a permanent quality cop
- A stronger sense of where developers create value in an AI-shaped world
- A starter AI Systems Thinking Checklist you can use with your own codebase or team
Most organizations are asking the obvious question:
How can we use AI to build more software faster?
I think that question is too small. We have already seen what happens when good ideas get reduced to productivity mechanisms. Agile and DevOps both began with humane and powerful principles: sustainable pace, technical excellence, collaboration, fast feedback, shared responsibility, and continuous learning.
But in too many organizations, those ideas were turned into ways to squeeze more work out of developers. The result has cost our industry dearly: brittle systems, exhausted teams, and mountains of legacy code.
AI gives us another chance.
Maybe our last best chance to reclaim craft in software development. Not because AI will eliminate the need for craft, but because it gives us the leverage to practice craft at a higher level. If we use AI only to generate more features, we will accelerate legacy code. If we use AI to deepen understanding, improve feedback, and compose better systems, we can build software that is more expressive, more resilient, and more humane to work with.
The Big Shift
Anyone can ask AI to build a feature. That does not mean the result is a system.
Enterprise software is not just a pile of working code. It is a living model of a business, a domain, a workflow, a product, and a set of hard-won discoveries. It contains customer knowledge, edge cases, policies, exceptions, operational realities, and tradeoffs that may have taken years to learn.
That is why legacy code has value.
It may be hard to change. It may be frustrating. It may need serious refactoring. But it often embodies the organization’s secret sauce. If we treat existing systems as disposable text that AI can simply regenerate, we risk throwing away the learning those systems contain. The developers who thrive in this next era will not be the ones who merely know the latest AI tools. They will be the ones who can turn ambiguity into coherent, testable, changeable systems.
The Question That Changes Everything
For managers: What will the next meaningful change cost?
That question connects software quality to business reality. If every change requires fear, archaeology, and heroics, the system is expensive no matter how quickly the first version was generated.
For developers: How straightforward is it to verify this behavior?
Testability is the developer’s north star.
Once you understand what a good test is, you can evaluate almost any piece of code by asking whether the behavior is straightforward to verify. You do not always have to write the test immediately. Just asking the question reveals hidden coupling, unclear ownership, vague behavior, weak boundaries, and poor design.
If behavior is hard to test, it is usually hard to understand. If it is hard to understand, it is hard to change.
If it is hard to change, AI has not solved your software problem. It may have made it bigger, faster.
If you are a manager, director, or executive exploring how AI will impact your team.
If you are a product owner, analyst, consultant, or knowledge worker who wants to improve decision-making and collaboration.
If you are a software developer, architect, or technical leader interested in moving beyond prompting into deeper forms of AI collaboration.
If you are an Agile coach, Scrum Master, facilitator, or transformation leader helping teams navigate change.
If you are curious about how AI can strengthen human capability rather than replace it.
When you attend this webinar, you’ll learn:
– Why AI coding is only the beginning of the shift happening in software development
– Why “just regenerate it” misunderstands the value of legacy systems
– How to distinguish working code from changeable code
– Why systems thinking becomes more important when code is easy to generate
– How to use testability as a practical way to evaluate design quality
– How to move from procedural narrative toward domain models with clear responsibilities
– Why the question “Who owns this behavior?” changes how we design software
– How to use AI as a collaborator in discovering concepts, boundaries, invariants, responsibilities, and tests
– How developers can preserve agency when working with increasingly capable AI system
Details
• Length: 45-minute presentation + 15-minute Q&A
• • Format: Live and interactive with demonstrations and discussion
• Limited seats to keep it interactive.
• Bonus: Invitation to monthly office hours and follow-up resources
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
Will this be recorded? Yes. Registrants will receive the replay and resources after the webinar.
Is this for developers or managers? Both, but the center of gravity is software development. Developers will get practical ways to think about testability, models, and changeability. Managers will get a clearer way to understand why sustainable software quality matters in the AI era.
Do I need a technical background? No. We focus on practical patterns for leaders and teams; code is shown only to illustrate concepts.
How is this different from other AI talks? Most AI coding webinars focus on tools, prompts, and productivity. This one focuses on understanding, agency, domain models, testability, and the systems thinking skills developers will need as AI becomes more capable.
Can I ask questions? Yes, there’s time set aside at the end for Q&A.
- Can we arrange a private session for my team? If you want to bring this conversation to your development team, leadership group, or technical community, I also offer private sessions tailored to your codebase, practices, and goals. Contact me to schedule a conversation.