AI deployments best practices
SMRTR summary
AI deployment challenges DevOps teams with additional considerations beyond standard software practices. Key aspects include:
1. Implementing DevEx to manage cognitive load and productivity.
2. Utilizing Platform Engineering for architectural decisions and scalability.
3. Adopting responsibility models for clear team roles and artifact ownership.
4. Following pragmatic deployment pillars, including repeatable, verifiable, and auditable processes.
These practices help teams create valuable AI solutions while maintaining governance, testing, and accountability. Automation, standardization, and clear responsibilities are crucial for success.
SMRTR provides this summary for quick context. The original article belongs to Daily.dev.
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