Insights
Analytical pieces on the decisions enterprise leaders are making about AI, data, and cybersecurity.
ai-generative
The enterprise AI model selection matrix for 2026
Not every workload needs frontier Claude or GPT. A decision framework for picking the right model — open-source or paid — across cost, quality, latency, residency, and governance.
cybersecurity
Agentic AI approval gates: a CISO framework
Autonomous agents take actions. The question is not whether to allow them — it is where to put the approval gates. Here is a tiered framework you can apply to every agent in production.
cybersecurity
The CISO's guide to agentic AI risk in 2026
Autonomous agents take actions, not just generate text. That changes the threat surface. Here is how to govern them without blocking the program.
data
The data platform decision in 2026: Fabric, Databricks, or Snowflake
Three platforms. Three credible answers. The choice depends on existing investment, workload shape, and team skill — not on a leaderboard.
ai-generative
The real cost structure of enterprise AI in 2026
Model tokens are the cheapest line item in most production AI programs. The expensive parts — and the ones that actually break budgets — live somewhere else.
modernization
The sequencing problem in legacy modernization
Most enterprise modernization programs fail at the sequencing, not the execution. A framework for deciding what to modernize, when, and in what order.
ai-generative
The case for self-hosted AI in the regulated enterprise
Cloud LLM APIs are fast, easy, and cheap per token. They are also often the wrong answer for regulated workloads. Here is the framework for deciding when self-hosting is the right call.
staffing
When staff augmentation beats full-time hiring (and when it does not)
The default assumption — full-time is better, staff aug is a stopgap — is often wrong. A decision framework for enterprise technology leaders.