AI Engineering Circle
Community Guidelines & Code of Conduct
Respect. Learn. Share. Grow Together.
AI Engineering Circle is a community of practitioners who come together to explore AI engineering, software development, cloud, DevOps, security and related technologies through discussions, experiments and shared experiences.
We welcome students, beginners, experienced engineers, architects, researchers, founders and technology enthusiasts.
To maintain a healthy and supportive learning environment, we ask every member to follow these principles.
1. Respect Everyone
Treat fellow members with respect, regardless of their experience, background, role or technical knowledge.
Listen to different perspectives and disagree respectfully. Personal attacks, discrimination, harassment, bullying and offensive behaviour are not acceptable.
2. Be Supportive and Encourage Learning
Everyone is at a different stage of their learning journey.
Help others understand concepts, share useful resources and offer constructive guidance.
Encourage members who are experimenting, asking questions or trying something for the first time.
3. Ask Questions Freely
Every genuine question deserves respect.
Members should feel comfortable asking basic or advanced technical questions without fear of being judged or ridiculed.
If you know the answer, help. If you don't, explore and learn together.
4. Share Knowledge and Practical Experiences
We encourage members to share what they have learned, built, tested or experienced.
Discuss successes, failures, challenges and lessons learned.
When possible, share practical examples, demonstrations, code, articles or references that help others learn.
5. Keep Discussions Constructive
Challenge ideas, assumptions and technical decisions respectfully.
Support your opinions with reasoning, evidence or practical experience whenever possible.
Avoid unnecessary arguments, personal criticism and conversations that discourage participation.
6. Learn Without FOMO
There is no expectation that everyone must learn every new AI model, framework or tool.
Focus on understanding problems, engineering fundamentals and practical applications.
Respect different learning paths, technology choices and approaches.
7. Encourage Participation and Collaboration
Give everyone an opportunity to contribute during discussions and activities.
Avoid dominating conversations. Listen actively and make room for others.
Support collaborative experiments, peer learning and community initiatives.
8. Respect Privacy and Confidentiality
Do not share another member's personal information, private conversations, screenshots, recordings, code or project details without permission.
When discussing workplace or client projects, avoid exposing confidential information, credentials or sensitive data.
Ask permission before recording or publicly sharing community discussions.
9. Avoid Unsolicited Promotion and Spam
Members are welcome to share relevant projects, open-source contributions, events, articles and learning resources.
However, excessive self-promotion, unsolicited sales messages, referral spam and unrelated advertising are discouraged.
Commercial opportunities should be shared transparently and through appropriate community channels.
10. Practice Responsible AI Engineering
Encourage responsible and ethical use of AI technologies.
Consider security, privacy, reliability, transparency and potential misuse when discussing or demonstrating AI systems.
Avoid sharing harmful instructions, unauthorized access techniques or sensitive information that could put others at risk.
11. Give Credit Where It Is Due
Acknowledge the work, ideas and contributions of others.
When sharing code, research, articles or projects, credit the original authors and respect applicable licenses.
Be transparent about your own work and contributions.
12. Help Keep the Community Healthy
If you notice inappropriate behaviour, raise it privately with the community organisers.
Organisers may provide guidance, moderate discussions, remove inappropriate content or restrict participation when necessary.
Repeated or serious violations may result in removal from the community.
Our Community Culture
We encourage every practitioner to follow a simple approach:
Discuss → Question → Share Experience → Learn Together
You don't need to be an expert to contribute.
A thoughtful question, a practical experiment, a useful answer or a lesson from a failed attempt can help someone else.
Let's build a respectful, supportive and collaborative AI Engineering community where everyone has an opportunity to learn and grow.
AI Engineering Circle — A practitioner-led learning community.