cluster
Vendor Independence
How to stay independent while going AI-native: architecting so no single provider can trap you, at the model layer rather than the datacentre layer. Open weights as exit insurance, portable prompt and tool-calling design, fine-tune portability, model-deprecation continuity, multi-provider failover, procurement and exit terms, and the difference between EU hosting and genuine sovereignty. Prevention, not migration.
3 articles
Subclusters
Articles
August 25, 2026
Porting Fine-Tunes and LoRA Adapters Between Providers
The true value of your fine-tune is the knowledge embedded in its weights. By extracting your LoRA adapters as portable artefacts and avoiding proprietary serving layers, you can freely migrate your custom models across any infrastructure without vendor lock-in.
August 21, 2026
OpenAI Compatible APIs: What Breaks When Switching Models
Switching inference endpoints is a one-line code change, but prompt behavior rarely transfers perfectly
August 20, 2026
Model Deprecation Risk: Version Pinning & Notice Periods
When an API provider retires or silently updates a model, the resulting breaking changes force a rapid, unplanned migration. Discover how version pinning, rigorous regression testing, and transparent Service Level Agreements protect your infrastructure from deprecation risk.