Which AI model should you use? A November 2026 field guide
The current models from Anthropic, OpenAI, Google, DeepSeek and the open-weight labs, what they cost, how they score on independent benchmarks, and how to pick one.
Ravindra KumarA FIELD GUIDE TO BUILDING IN THE CLOUD
Less noise.
More know-how.
Practical guides, lessons learned, and useful resources for your cloud-native journey.
Notes from Ravindra KumarTHE LATEST FIELD NOTE
AI EngineeringWhich AI model should you use? A November 2026 field guide
The current models from Anthropic, OpenAI, Google, DeepSeek and the open-weight labs, what they cost, how they score on independent benchmarks, and how to pick one.
Ravindra Kumar7 Nov 2026 · 8 min read
FROM THE NOTEBOOK
Worth your next read.
Ravindra Kumar
Claude Code works best when you give it a way to check its own work
A practical workflow for Claude Code: a short CLAUDE.md, planning before editing, a clean context per task, hooks for the rules that must hold, and checks it can run itself.
Ravindra Kumar
Serving an LLM on Kubernetes: slow starts, heavy weights and the right scaling signal.
Why a model server breaks the defaults you use for web apps, and how to set probes, model storage, autoscaling and routing for AI inference.
Ravindra Kumar
A GPU is not a bigger CPU. Schedule it like one and your pod waits.
How Kubernetes actually allocates GPUs to AI workloads: whole devices, taints, sharing with isolation in mind, and Dynamic Resource Allocation.
Ravindra KumarSMALL STEPS. REAL PROGRESS.