What HumanLayer does
HumanLayer is an oversight layer for AI agents. In the coding context, that means an agent can plan, edit, run tools or prepare a pull request, but selected actions can be routed to a human for approval before they proceed. This is the missing middle between “never let the agent do anything important” and “let an autonomous agent freely change a repo or production system.”
The product is especially relevant because agentic coding tools are becoming more capable, longer-running and more parallel. As soon as a team delegates real work to Claude Code, Codex, Devin-style agents or internal automation, it needs a policy surface: what can the agent do alone, what requires approval, and who gets notified?
Where it works best
HumanLayer is strongest for high-risk or high-ambiguity steps. Examples include sending a PR, applying a database migration, calling an external API, changing billing logic, deploying infrastructure, or escalating to a product owner for domain context. These are not just technical events; they are accountability events. A human-in-the-loop gate gives the team a record of who approved what and why.
This also makes HumanLayer useful for organizations that are not ready for full autonomy. Agents can still do useful work, but approval gates keep the blast radius smaller.
Tradeoffs
Approval systems can become bottlenecks. If every small tool call asks for permission, developers will ignore the system or revert to manual work. HumanLayer’s value depends on designing useful boundaries: low-risk actions should continue automatically, while irreversible or business-sensitive actions stop for a person.
It also should not be confused with testing or security scanning. Human approval is one safety layer; teams still need CI, code review, sandboxing, secret controls and observability.
Bottom line
HumanLayer is a strong fit for teams graduating from local AI coding experiments into delegated agent workflows. It gives agentic coding a governance layer without forcing every action back into manual review. The best buyers are teams already running or planning long-running coding agents and looking for a clear way to keep humans in control of the risky steps.
