SecuAgent · Insights

Insights

Observations and practical recommendations on enterprise AI adoption, AI agents, and governance frameworks, updated on an ongoing basis.

Not Your Weights, Not Your Product: A Sequoia Partner's Warning and Four-Step Playbook

Sequoia Capital partner Sonya Huang's public talk delivered a blunt warning: if you don't own your model weights, you don't own your product. Here's a breakdown of the four drivers behind enterprises building their own models, the performance reversal of open-weight models, and the four-step playbook for application companies moving toward AI sovereignty.

Are Most Enterprises Getting AI Adoption Wrong From Day One? An NTU Professor Names the Blind Spot

Professor Chia-Yen Lee, Executive Director of NTU's EiMBA program, observes that the biggest obstacle to enterprise AI adoption is rarely technology or talent — it's the lack of a shared language between users and AI experts. Here's a breakdown of what makes AI transformation stall, and the decision-making mindset leaders need.

Who's Reining In Runaway Enterprise AI? Decoding the Four Core Functions of the AI Gateway

Gartner's Market Guide for AI Gateway, published late last year, names the need for an independent control layer between enterprises and AI models. Here's a breakdown of the AI gateway's four core functions — and what IT teams should be preparing for now.

Decoding the Token Economy: How Should Enterprises Train Employees to Use AI?

Uber once burned through a full year's AI budget in just four months. Here's a breakdown of what the token economy really is, the three keys to using tokens well, how reverse division of labor is reshaping organizations, and how individuals can evolve from T-shaped to comb-shaped talent.

Agent vs. Workflow: What Enterprises Actually Need

Clarifying the real differences between Chatbots, AI Workflows, Agentic Workflows, Autonomous Agents, and the Harness that governs them — and why enterprises adopting AI should prioritize a solid governance framework over going all-in on agents.

Big Tech's Compute Arms Race, and the Productivity Tax on Every Enterprise

Microsoft, Google, and Meta pour hundreds of billions of dollars a year into AI infrastructure — a moat-defense war, not a quest for short-term profit. Here's how enterprises can shift from selling hours to selling outcomes, and build their own vertical micro-platform to collect a productivity tax of their own.

The GenAI Divide: MIT's Report Decodes Why 95% of Enterprise AI Projects Deliver Zero Return

MIT NANDA's July 2025 report analyzed more than 300 AI adoption cases and found that 95% of enterprise generative AI projects deliver zero return — only 5% actually create value. Here's where the real divide lies, and the concrete actions enterprises should take when adopting AI.