Blog

Notesfromthestudio

What we learn shipping AI products, written by the engineers and researchers doing the work, not a marketing team.

Governance for Enterprise AI: Access, Audit Trails, and Human Oversight

Practical governance practices for enterprise AI deployments, covering access control, audit trails, provenance, and human oversight.

Julian Voss · Head of Data Platform · 9 min read

A practical framework for deciding whether to build custom AI features in-house or integrate off-the-shelf AI tools.

Priya Natarajan · 7 min read

Patterns for reliable multi-step AI agents: tool use as a contract, guardrails on the plan, human escalation, and real observability.

Marcus Lindqvist · 10 min read

Freshness, lineage, vector stores, and feature stores: the unglamorous data plumbing that determines whether AI features hold up.

Julian Voss · 8 min read

A grounded framework for measuring internal AI copilot ROI: time saved per task, adoption curves, and the baselines to capture first.

Devika Sundaram · 7 min read

How to build golden datasets, human review loops, and regression tests so prompt and model changes stop being a guessing game.

Renata Osei · 8 min read

Chunking, hybrid search, and evaluation harnesses that keep retrieval-augmented generation reliable once it leaves the demo.

Marcus Lindqvist · 9 min read

A six-week structure for scoping, building, and validating an AI SaaS MVP without letting the model become the whole project.

Devika Sundaram · 7 min read