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Enterprise AI Reality

#concept

Summary

The indie/practitioner world and the regulated-enterprise world diverge sharply. Sebastian's key business insight: harness cannot survive compliance, so a scalable, company-managed standard harness is an underserved market — "the interesting market."

Current Understanding

  • Locked-down reality: at Sebastian's biggest clients, engineers can't use their own laptops — only a centrally-managed VM with zero ability to install their own tools. Compliance and liability make ad-hoc, per-developer setups impossible. Reference points: a Roche SAP transformation ran ~1,200 engineers for years; banks first banned AI outright and now cautiously adopt it "because it's just so good."
  • The business opportunity: scalable, manageable, company-standard harnesses for larger engineering teams. The gap between what individuals can do (custom harness) and what enterprises can allow is the product.
  • Governance vs leverage tension: individuals get maximum leverage from personal harnesses (eugene); enterprises must standardize and control (sebastian). Unresolved — and monetizable.
  • Adjacent constraints: the seniority-and-the-junior-squeeze security concern is amplified at scale; safety-critical/regulated code is the clear exception to code-as-throwaway.

Evidence

Contradictions / Uncertainty

  • How AI transforms huge (~1,200-engineer, multi-year) programs is explicitly unknown even to Sebastian.
  • Whether virtido itself is building the company-managed harness, or just naming the market, is unstated.

Next Questions

  • What is the minimal compliant feature set for a centrally-managed enterprise harness?