The IBM watsonx generative AI stack, end to end, for engineers and architects working in governed environments: watsonx.ai to build and serve models, watsonx.data as the lakehouse and vector store, watsonx.governance for risk, monitoring and audit, Granite as the model family, and the tuning, agent, and deployment layers that turn a model into a compliant product. A 24 part series that reads from first principles to production. Where it meets vendor neutral ground it links to the Generative AI guide and the NVIDIA AI guide rather than repeating them.
Complete · 24 of 24 published
Phase 1 · Platform foundations
- 01What the watsonx Stack Is, End to End
- 02watsonx.ai Studio and Prompt Lab
- 03The Granite Model Family, Third-Party Models and Licensing
- 04Deployment Options, SaaS to OpenShift
- 05Pricing, Resource Units and Tiers
- 06GPUs and watsonx on OpenShift
- 07Regions, Private Connectivity and Security
Phase 2 · Build, tune, and retrieve
- 08Inferencing and Prompt Engineering
- 09RAG on watsonx.data and Vector Search
- 10Granite Guardian and Hallucination Detection
- 11Prompt Tuning and Fine-Tuning Granite
- 12InstructLab, Taxonomy to Aligned Model
- 13Data Prep and Synthetic Data
Phase 3 · Agents, apps, and scale
- 14Training Infrastructure on OpenShift
- 15watsonx Orchestrate, Building Agents
- 16watsonx Assistant, Conversational Apps
- 17Model Evaluation and Benchmarking
- 18Docling Document Understanding and Multimodal
Phase 4 · Govern, operate, and decide
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