Topic starter
21/08/2026 4:55 pm
TL;DR: AI gateways turn delegation into a governance problem, TruFoundry says, because tools, skills, and sub-agents each shift who acts and what can be traced. Identity, scope, versioning, and tracing need to match the rung in use, or a reasoning delegate can slip past call-level controls.
Editorial analysis by NHI Mgmt Group, based on content published by TruFoundry: “Tool vs. Skill vs. Sub-agent: The Delegation Spectrum and Its Governance”.
Key questions
Q: Why do sub-agents create more accountability risk than tools or skills?
A: Sub-agents create more accountability risk because they are separate reasoning principals, not just packaged instructions or callable actions.
Q: What are the signs that a skill registry is being misused?
A: Look for copied procedures, version drift, and inconsistent behaviour across agents using what appears to be the same skill.
Q: How should teams classify delegated work in AI gateways?
A: Classify delegated work by the governance unit it actually creates.
Practitioner guidance
- Classify delegated work by governance unit Separate one-off actions, packaged procedures, and reasoning delegates in your AI gateway design so each rung maps to the correct control model.
- Require per-principal scoping for sub-agents Assign explicit identity, scoped permissions, and bounded context to any delegate that reasons independently, even when it sits inside a larger parent workflow.
- Version and review skills as governed artefacts Store reusable procedures in a registry with version pinning, review status, and RBAC so behaviour changes are visible before they spread.
Bottom line: AI gateways expose a governance problem, not just a routing problem, because delegation changes the actor being controlled.
Glossary terms: Delegation spectrum, Subagent, Skills Registry, Per-Principal Governance
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This topic was modified 4 days ago by NHI Mgmt Group
21/08/2026 5:12 pm
Delegation is now an identity boundary, not just an engineering pattern: AI gateways do not simply route work, they decide which actor is allowed to act and under what governance model. Once a system can reason, the control question changes from call legitimacy to principal legitimacy. That is why tool, skill, and sub-agent must be treated as separate identity surfaces, not interchangeable implementation styles. The practitioner conclusion is simple: govern the delegation rung, not the label.
A few things that frame the scale:
- AI-related credential leaks surged 81.5% year-over-year in 2025, with the surrounding AI infrastructure leaking 5x faster than core LLM providers, according to the State of Secrets Sprawl 2026.
A question worth separating out:
Q: What should security teams do when a delegate inherits the parent’s permissions?
A: They should treat inherited permissions as a design smell and re-scope the delegate explicitly. If a sub-agent can write, reach sensitive data, or act in production because the parent could, the control model is too coarse. Separate identity, narrow tool access, and an auditable trace are the minimum conditions for safe delegation.
👉 Read our full editorial: Delegation spectrum in AI gateways: tools, skills, sub-agents