Essays, explainers, and practical guides on AI work, spend, workflows, and model economics.
13 resources shown
We're coming out of stealth and joining Y Combinator's Winter 2026 batch. Here's why we're building the visibility layer the enterprise has been waiting for.
Blog · 2026-01-27
Enterprise AI adoption accelerated because it was useful. What didn't evolve at the same pace was visibility. Here's why that's the biggest risk to scaling AI safely.
Blog · 2026-01-23
Why observability must survive developer reality. Security that assumes perfection does not scale - observability that survives imperfect behavior will endure.
Guide · 2026-01-18
As AI systems influence decisions, automate workflows, and shape outcomes, responsibility is quietly diffusing. When something goes wrong, the organization often discovers that no single team fully owns the system involved.
Blog · 2026-01-15
Why AI risk emerges upstream of prompts, providers, and policies. The most effective security controls are those that shape decisions before they become irreversible.
Guide · 2026-01-08
Employee AI observability does not fail at the prototype stage. It fails when AI becomes a daily habit. Here's why tracking workforce AI usage requires a fundamentally different approach.
Blog · 2026-01-06
Why most enterprise AI risk starts with people, not agents. Organizations that start with workforce visibility gain understanding, trust, and control.
Guide · 2025-12-28
Nearly every enterprise that reaches meaningful AI adoption encounters the same moment of clarity: how do we see what's happening without slowing everything down? That's when the build-versus-buy discussion begins.
Blog · 2025-12-20
A practical, thirty-day path from uncertain AI usage to defensible, governed adoption - designed for organizations that need to move now, not eventually.
Blog · 2025-12-12
AI agents do not merely respond. They act. They browse, call APIs, write files, trigger workflows, and make decisions that have real operational consequences. This fundamentally changes the security model.
Blog · 2025-12-05
Why durable AI visibility cannot depend on applications, SDKs, or developer behavior. A comprehensive guide to network-layer observability for AI systems.
Guide · 2025-12-05
Most enterprises already have an AI policy. It sits alongside information-security guidelines and acceptable-use standards. On paper, it looks like progress. In practice, it rarely governs anything.
Blog · 2025-11-28
Shadow AI is not simply the next iteration of shadow IT. It is categorically more dangerous because AI systems move data, interpret intent, and generate outcomes in ways traditional tools never did.
Blog · 2025-11-22