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Model Deployment Strategy: API vs Self-Hosted AI Systems

7 chapters · 31 lessons

1. 1. Access Models and Control Surfaces

   4 lessons

   Map the spectrum from managed APIs to self-hosted systems and identify what each access level enables or constrains.

2. 2. Cost Modeling Across Deployment Patterns

   5 lessons

   Build total cost of ownership models that account for API pricing, infrastructure, engineering effort, and operational overhead.

3. 3. Data Governance and Security Requirements

   4 lessons

   Evaluate how data locality, privacy regulations, and security posture influence deployment architecture decisions.

4. 4. Performance and Latency Architecture

   5 lessons

   Design deployment patterns that meet latency, throughput, and availability requirements for different product scenarios.

5. 5. Customization and Integration Depth

   4 lessons

   Assess when and how to customize model behavior, from prompt engineering to fine-tuning and architecture modifications.

6. 6. Licensing, Compliance, and Vendor Risk

   4 lessons

   Navigate license terms, usage restrictions, and vendor dependencies that constrain deployment and product strategy.

7. 7. Decision Frameworks and Business Cases

   5 lessons

   Build structured evaluation processes and communicate deployment trade-offs to stakeholders and leadership.