The landscape of software development is experiencing a seismic shift. 🌋

AI isn't just changing how we write code – it's revolutionizing every aspect of how technology teams operate and deliver value. CEOs and founders need their teams to adapt and lead their organizations in this new era.

We've witnessed many tech trends come and go, but this one feels like the birth of the Internet, the true Web 2.0.

As a CTO and consultant, I've been thinking a lot about what I want to see my teams do in this era, as well as where I see the industry going as a whole.

While not an exhaustive list, here are some thoughts.

Empowering Teams with Tools

I'm seeing a troubling pattern in organizations. Some developers are paying for AI tools out of their own pocket. Others aren't using them at all because of the cost. Perhaps most concerning, I'm hearing management ask "How much does that one cost?" as if these tools are a luxury rather than a necessity.

This needs to stop.

First things first: every developer needs a budget for AI tools. While not prescriptive, what about $50-100 USD monthly for Claude, ChatGPT, Cursor Pro subscriptions, V0.dev for UI components, and other AI-powered development tools?

This isn't an expense – it's an investment in 10x productivity. At $50-100 per developer per month, we're talking about 0.5-1% of a developer's salary. Compare that to the cost of additional headcount! The ROI here is astronomical.

Why the budget matters

• Engineers need access to premium features of AI coding assistants
• Multiple AI tools serve different purposes (architecture, coding, user interface)
• Experimentation with new AI tools is crucial for staying competitive
• The cost is minimal compared to the productivity gains

Standardization is More Critical Than Ever

Want AI to be effective? Give it structure.

Your repositories need crystal-clear documentation. CONVENTIONS.md files should outline every tech choice, library preference, and coding standard.

This isn't just for humans anymore. It's for our AI pair programmers too.

Key standardization elements

• Small, focused files with clear boundaries (and no, this doesn't mean microservices - let's not go down that rabbit hole 😅)
• Single responsibility principle at the file level
• Clear contexts that AI can understand and work within
• Detailed architecture documentation
• Clear coding conventions and style guides
• File size limits and organization principles (keeping files small and focused helps both humans and AI understand the codebase)
• Technology stack decisions and rationales
• Comprehensive testing standards that leverage AI's ability to generate test suites
• Deployment and infrastructure conventions

The Return of Visual Communication

Remember UML? I think it really needs to make a comeback, but with a twist - and it's becoming one of our most powerful tools for verifying AI-generated code.

Text-based diagram languages like PlantUML and Mermaid are perfect for AI generation. But more importantly, they're becoming crucial for verification. When AI generates both code and corresponding architecture diagrams, you can instantly spot fundamental issues or areas for improvement. A picture paints a thousand words.

Benefits of AI-powered diagramming

• Instant visualization of system architecture
• Quick verification of AI-generated code structure
• Immediate identification of architectural red flags
• Spot missing connections or unnecessary coupling at a glance
• Validate that AI has maintained your intended system boundaries
• Better communication between teams
• Faster onboarding of new team members
• Easy maintenance of technical documentation

Here's the game-changer: When AI suggests a major refactor or generates a new feature, you can verify its understanding by having it generate the architecture diagram first. If the diagram looks wrong, you've saved hours of code review. If it looks right, you have much more confidence in the code you will review.

Can we see these autogenerated all the time from our codebases? Yes!

Who knew AI would make us better at communicating design? 🎨

Creating a Culture of Experimentation

AI moves fast. Really fast.

Your team requires the freedom to experiment, make mistakes, and learn from both achievements and setbacks.

Cultural elements to foster

• Top-down directives to use and integrate AI
• Celebrate AI-driven innovations
• Share learnings from failed experiments
• Create spaces for AI tool exploration
• Reward efficiency improvements
• Encourage cross-team AI knowledge sharing

Let's be honest: team sizes might change, and some roles might disappear. But for those willing to adapt, lead, and orchestrate these new AI tools - your career isn't just safe, it's about to become more exciting and impactful than ever. The future belongs to those who embrace AI as their ultimate force multiplier.

Rethinking Team Composition

We need to completely reimagine what "junior," "mid," and "senior" mean in an AI-powered world.

The New Engineering Hierarchy

• Junior developers focus on architectural build-out with AI, design patterns, and best practices rather than syntax
• Mid-level developers become AI orchestrators and quality guardians
• Senior developers evolve into strategic architects and AI capability leaders

Education Makes a Comeback

• Formal computer science education becomes more crucial
• The focus shifts from syntax to fundamental principles
• System design and architecture take centre stage
• Understanding trade-offs becomes more important than implementation details
• Theory and patterns matter more than ever

The AI Tool Stack That Matters

Warning: This section has the shelf life of a banana. 🍌

But right now I'm using and recommending

• Claude Sonnet 3.5 - It still leads at getting code right and understanding complex architectures as well as outputting diagrammatic text syntax like PlantUML.
• OpenAI and DeepSeek are great for rapid iterations, smaller changes, and conversations about what you need to do. Design documentation etc..
• Cursor is becoming indispensable as the IDE with the best AI integration and real-time assistance
• V0.dev is revolutionizing UI development
• Fork.app or other git GUI to rapidly review as a whole, what AI is building out
• Aider is showing us the future of AI-first development
• Tools like AI-KB and Repomix are making LLMs more effective with context

The Near Future

Every developer becomes a team leader, orchestrating their own AI workforce. Here's how:

Automated Development Pipeline

• AI creates feature branches directly from ticket descriptions and requirements
• Generates initial code implementation
• Creates comprehensive test coverage
• Raises pull requests for human review
• Documents changes and impacts

The Human Element

• Engineers review AI-generated code for business logic accuracy
• Focus on architectural decisions and edge cases
• Guide AI toward better solutions
• Maintain system integrity and scalability
• Build rapid MVPs of entire apps or initiatives to validate quickly and cheaply.
• Lead rather than just code

Making the Transition

This isn't just about tools. It's about mindset.

Your team needs to embrace AI as a collaborator, not a threat. They need to understand that their value lies in their ability to'

• Direct AI toward business objectives
• Verify and improve AI-generated solutions
• Maintain system architecture integrity
• Think strategically about technical decisions
• Lead and innovate rather than just implement

The Education Imperative

The future of software engineering education needs a radical shift as well.

• Less focus on language-specific syntax
• More emphasis on system design and architecture
• Greater attention to algorithmic thinking
• Enhanced focus on design patterns and best practices
• Strong foundation in computer science fundamentals

Universities and boot camps need to adapt their curricula accordingly.

Need Help?

Let's chat if you want to transform your engineering team for the AI era. This revolution is just beginning, and the opportunities are endless. 🚀

Remember: The goal isn't to replace engineers with AI. It's to elevate engineers into strategic leaders who orchestrate AI to build better software faster.

Are you ready to power up? 💪