Resources#
Thank you for following along. Every link referenced across this site is collected here, along with a few extra starting points if you want to keep exploring agentic engineering, agentic workflows, and platform engineering for the AI-native era.
Start here#
Awesome GitHub Copilot → Agentic workflows on GitHub → Git-Ape: agentic platform engineering →
- Awesome GitHub Copilot - a community-maintained collection of custom agents, reusable instructions, prompts, and agentic workflow examples for GitHub Copilot.
- Agentic workflows on GitHub - GitHub's own hub for Copilot's agent capabilities, including the coding agent and code review agent referenced throughout this site.
- Git-Ape - an open, multi-agent platform engineering framework for Azure that shows agentic patterns (requirements gathering, architecture review, security gating, drift reconciliation) applied to infrastructure delivery, not just application code.
GitHub Docs#
- About Copilot coding agent
- Using GitHub Copilot code review
- About rulesets
- About code owners
- Managing a branch protection rule
GitHub Blog#
- GitHub Copilot coding agent 101: getting started with agentic workflows on GitHub
- Enterprise AI controls & the agent control plane are in public preview
Microsoft Learn & Microsoft blogs#
- Foundations of Agentic AI in GitHub - Microsoft Learn training module
- Optimize DevOps with AI agents on Azure - Microsoft Learn training path
- Agentic DevOps: evolving software development with GitHub Copilot and Microsoft Azure - Microsoft Azure Blog
- Agentic DevOps in action: reimagining every phase of the developer lifecycle - Microsoft Developer Blog
About the talk#
This site accompanies "Engineering the AI-Native Cloud," a DevOps Asia Conference talk on cloud native AI in the SDLC. Get in touch or follow along:
GitHub - codess-aus → LinkedIn - Michelle Sandford → scaling-guacamole.com →
A note on sources
Nothing on this site invents a case study, statistic, or benchmark. Every factual claim about GitHub or Microsoft product capability links to its primary documentation above. Where the talk uses an anecdote (see Chapter 2), it's presented as a story illustrating a risk, not as data.