About us
Technical Excellence is the foundation of sustainable software engineering. Without technical excellence, there's no quality; the development is slow and cannot be sustainable. Without technical excellence, there's no agility.
Do you want to share knowledge about software quality, to build better products?
This group is for engineering leaders and software developers who are motivated by building high-quality solutions and continuously improving. Technical Excellence is both a mindset and a set of practices to help us build quality software faster and deliver value sooner.
Our focus will be on the following topics:
- Extreme Programming
- Software Craftsmanship
- Continuous Integration
- Continuous Delivery
- Trunk Based Development
- Test Driven Development
- Hexagonal Architecture
- Clean Architecture
- Domain Driven Design
- Use Case Driven Design
- System Design
- Clean Code
- Refactoring
- Technical Leadership
- Learning Culture
Our sessions will be in English, held remotely, and open to participants across the globe.
Our goal is to share knowledge, discuss diverse perspectives and synthesize our collective knowledge.
You can follow us on:
- YouTube: https://www.youtube.com/c/techexcellence
- LinkedIn: https://www.linkedin.com/company/techexcellenceio
- Twitter: https://twitter.com/techexcellence_
- GitHub: https://github.com/valentinacupac/techexcellence/discussions
Founder: Tech Excellence was founded by Valentina Cupać, Technical Coach @ Optivem.
Community Guidelines: We want to build a safe community. Please ensure you have an appropriate profile photo image. When posting comments, please ensure your communication is professional. In the case of violation of these guidelines, your membership will be revoked.
Upcoming events
1
AI Can Write Code. How Do We Keep It Clean?
·OnlineOnlineRegistration
https://codeartify.ch/en/public-video-sessions/ai-assisted-clean-codeWhy AI-assisted development needs clearer engineering standards, not just better prompts or faster code generation.
About the session
Can we simply prompt an agent to “write clean code” and get good results? Or do teams first need to make their standards and quality expectations explicit before AI can work with them?
AI coding tools do not just generate code. They also reflect the patterns already present in the codebase. If these patterns are problematic, AI can reproduce them confidently and make them look consistent.
The result is not automatically better software. It can become software that looks consistent, but becomes harder to change over time.
This session looks at what Clean Code means when AI becomes part of everyday development. It helps teams find clearer language for code quality, language explicit enough that AI can actually work with it.
You probably ask yourself…
- Can we prompt an AI agent to “write clean code” and get consistently good results?
- If AI creates, reviews, and tests most of the code, who still needs Clean Code knowledge: the developer, the agent, or both in different forms?
- How do we help AI learn from the best parts of a codebase, without turning shortcuts, workarounds, and compromises into future templates to follow?
- How do we guide AI to keep simple code simple, while evolving both code and architecture when complexity actually demands it?
What you will take away
- The “magic prompt” nobody told you about for consistently creating Clean Code with AI.
- What changes about Clean Code when AI starts creating, reviewing, and testing most of the code.
- How to define effective guardrails that capture team best practices, help AI avoid repeating shortcuts and compromises, and guide code and architecture as complexity grows.
Who this is for
This session is for software engineers, tech leads, software architects, engineering managers, and teams who are already using AI coding tools or are being asked to introduce them responsibly.
It is especially relevant if your team already uses AI coding tools in a real codebase and wants faster delivery without quietly increasing complexity, inconsistency, or long-term maintenance cost.
Who this is not for
This is not a tool comparison or generic AI productivity demo.
The focus is on code quality, maintainability, evolvability, team standards, AI agent guidance, and responsible adoption in real codebases.
Format
- Thursday, 9 July 2026
- 12:15 to 13:00 CEST
- Online
- 45 minutes practical input incl. Q&A
- Recording available for registered participants
- English
193 attendees
Past events
85
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