Amira Shah
Latest from Amira Shah
TechnologyAI evaluation is becoming infrastructure
The companies that can test quality, safety and product fit continuously will move faster than those that treat evaluation as a last check before launch.
Synthetic data has a trust problem, not just a quality problem
Generated data can expand testing and training, but its value depends on whether teams can explain what it represents, what it leaves out and how it was validated.
AI memory is becoming a product design decision
Remembering user context can make an AI service useful. It can also create surprise, privacy risk and a confusing sense of what the system knows.
The open and closed model debate is really a strategy question
Model access choices shape cost, control, speed and product differentiation. There is no universal answer because the right decision depends on the job the system has to do.
Agent observability is becoming a customer product
As AI systems take multi-step actions, logs and traces are no longer only engineering tools. They are part of the explanation customers need when a system acts on their behalf.
Model distillation is a product economics decision
Smaller specialized models can reduce cost and latency, but the real value comes from knowing which part of the customer experience must retain frontier-level capability.
Data provenance is becoming an AI product feature
Customers will increasingly ask not only what an AI system says, but what evidence it used, whether that evidence is current and how they can verify the answer.
Internal AI platforms are becoming the new shared service
A common platform can reduce duplication and improve controls, but it has to earn adoption by making teams faster rather than forcing every use case into a central queue.
