data governance
- AI Strategy (429)
- Generative AI (113)
- IT Leadership (38)
- Leadership (81)
- Product Management (394)
- Product Management Leadership (373)
- Uncategorized (32)
-
How to Build an AI Operating System for Business Growth
A practical method for turning one costly growth workflow into a governed AI loop, proving value quickly, and consolidating tools around it.
-
How to Secure AI Assistant Access to Your Email Inbox
A practical permission model and rollout checklist for letting AI assistants search, draft, and send email without losing account, approval, or policy control.
-
AI Memory Freshness: How to Handle Contradictory Facts
Design AI memory as a governed decision ledger so your product retrieves the latest approved truth, exposes conflicts, and preserves history.
-
China AI Governance: An Operating Plan for Product Leaders
A practical plan for adapting AI products to China’s focus on deployment risk, agent safety, human override, incident response, and auditability.
-
Should You Train AI on Your Company’s Work-Email Archive?
A practical framework for deciding whether an email archive should power retrieval, evaluation, or training without mistaking activity for truth.
-
Why AI Assistant Memory Matters More as Models Open Up
A product strategy for owning assistant memory, preserving user trust, and using open-weight models without locking your product to one vendor.
-
AI Governance for Agents, Privacy, and Open-Model Choice
A practical operating model for shipping AI agents with bounded data access, auditable decisions, and enough leverage to change models.
-
Before You Renew Software, Audit the Agent Workflow
A practical workflow audit for deciding which software capabilities to renew, unbundle, build, or make portable before the next enterprise contract.
-
Five Transferable AI Habits to Build with an Approved Copilot
Use an approved Copilot to master task framing, grounding, workflow design, evaluation, and learning habits that survive the next model switch.
-
AI Citation Integrity Checks: A Workflow Editors Can Trust
A practical design and rollout guide for citation checks that catch integrity risks before peer review without overwhelming editors with weak alerts.
-
Product Context: The Missing Layer in Enterprise AI Agents
A practical framework for giving enterprise AI agents the user, workflow, policy, and outcome context needed to act safely and prove measurable value.
-
Fei-Fei Li and the Product Foundations of Computer Vision
Use ImageNet’s history to decide where a vision product really needs investment: data, taxonomy, evaluation, compute, or model design.
-
How Private Equity Firms Can Measure AI-Driven Advantage
A practical scorecard for separating AI activity from verified economic value, repeatable execution, defensibility, and managed risk in private equity.
-
How to Build Context-Grounded AI for Customer Experience
Learn how to define, govern, evaluate, and safely expand the customer and product context that makes CX agents useful instead of merely fluent.
-
AI Music Search Starts With Metadata, Not a Chatbot
A product playbook for building AI music search on structured metadata, rights-aware retrieval, rigorous evaluation, and durable strategy.
-
AI Engineering in 2026: An Architecture for Reliability
A practical architecture for dependable AI agents, covering bounded workflows, governed memory, production-path evals, and observability in 2026.
-
How to Build a Trustworthy AI-Assisted Research Workflow
A practical workflow for using AI to collect, compare, draft, and edit academic work while keeping evidence, citations, and judgment under your control.
-
A Practical Playbook for AI in Back-Office Operations
A practical framework for choosing back-office AI workflows, setting safe autonomy, and proving improvements in cost, quality, and resilience.
-
Amplitude SDK vs. Warehouse Ingestion: A Decision Guide
Use this framework to choose Amplitude’s SDK, warehouse ingestion, or a hybrid based on behavioral depth, data authority, and governance.
-
How Product Leaders Should Govern Emerging AI Capabilities
A practical framework for governing retrieval poisoning, synthetic user forecasts, agent permissions, and the evidence needed before launch.
Weekly digest
One email a week on AI products, enablement and hiring. No fluff.
Browse topics
- AI Strategy (429)
- Generative AI (113)
- IT Leadership (38)
- Leadership (81)
- Product Management (394)
- Product Management Leadership (373)
- Uncategorized (32)
Work with me
45-minute consultation on AI product strategy, GTM and PM hiring — no charge.