The AI Engineering Stack: What Actually Belongs Around the Model
Saleem Chauhan
The model is only one component of a production AI system. A practical architecture for orchestration, context, tools, policy, evaluation, observability, security and cost.
2026
From AI Demo to Production: What Changes When the System Has Consequences
Moving AI from an impressive demo into production changes the engineering problem. A practical framework for evaluation, boundaries, observability, recovery and controlled autonomy.
AI Agents at Work: How Much Autonomy Should You Give an AI?
AI agents do more than generate answers. They take actions. A practical framework for deciding how much autonomy to give an agent—and how to earn more through evidence.
Constrained AI in Regulated Industries: A 4–6 Week Experiment
A focused 4–6 week experiment for comparing a standard LLM approach with a constrained or verified approach in a rules-heavy regulated workflow.
How Do You Know Your AI Actually Works? Build an Evaluation Harness
One of the easiest mistakes to make with an AI application is to confuse a convincing demonstration with a reliable system. A prompt works on ten examples. The output looks…