Insights
Building with evidence
Studio practice notes on platforms, AI governance, automation, and delivery — no hype metrics.
- ·1 min read·Platform Engineering
Evidence-Driven Go-Live Gates
Replace calendar-driven launches with explicit readiness criteria — soak reports, test evidence, and operator sign-off.
- ·1 min read·AI Systems·Featured
Building Knowledge Layers with Governance
Retrieval, classification, and summarization inside real workflows — with logging, evaluation, and human review paths.
- ·1 min read·Automation
Workflow Automation Without Silent Failures
How to design event-driven automation with retries, dead-letter queues, and operator visibility — so integrations fail loudly, not quietly.
- ·2 min read·Studio Practice·Featured
Structuring a Readiness Audit Before an AI Initiative
What a systems and AI readiness audit should cover — data, workflows, governance, and realistic next steps without shelfware deliverables.
- ·1 min read·Data Intelligence
Mode Labels for Honest Metrics
How to label paper, replay, demo, and live data so dashboards stay trustworthy — for operators, investors, and your future self.
- ·2 min read·AI Governance·Featured
Paper-First Validation for AI Products
Why paper, replay, and soak modes belong in AI product architecture — not as embarrassing disclaimers, but as engineering discipline.
- ·2 min read·Operational Platforms·Featured
Operational Platform vs. Buying More SaaS
When a custom operational platform beats stacking SaaS tools — and when it does not. A practical decision framework without vendor hype.
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