Agent Launchpad

Inspiration

As AI agents become capable of acting autonomously, simply authenticating a user is not enough. We wanted to build a middleware layer that can answer who is acting, what they are allowed to access, and what they actually did, while supporting collaboration between humans and agents.

What it does

Agent Launchpad provides an identity-first middleware architecture for multi-agent systems. It connects human authentication, Agent ownership, session collaboration, delegated Agent credentials, execution controls, and audit logging to enforce security at the server level.

How we built it

We implemented the security model in the backend Control Plane. Users are authenticated and linked to Agents through ownership, Sessions enforce collaboration boundaries, and Agents receive scoped and revocable credentials. Execution guardrails limit Agent steps and runtime, while structured logging provides attribution and auditability.

Challenges we ran into

The biggest challenge was making the different security layers work together without mixing their responsibilities. We had to distinguish human identity from Agent identity, handle ownership and collaboration correctly, securely manage credential lifecycles, and ensure enforcement happens server-side rather than relying on the UI.

Accomplishments that we're proud of

We turned a shared-token starter system into a much stronger identity-first architecture. We added server-side ownership and collaboration controls, independent Agent credentials with lifecycle management, execution safety controls, and attributable logging with secret redaction.

What we learned

We learned that security for Agent systems is not one middleware check. It is a chain of controls: identity establishes who is acting, authorization determines what can happen, guardrails constrain execution, and auditability records what happened. We also learned the importance of testing security boundaries and negative paths, not just successful requests.

What's next for Agent Launchpad

The architecture can be extended with finer-grained authorization policies and RBAC, policy-aware execution budgets, token/cost limits, trace-correlated audit trails, and human approval gates for high-risk Agent actions.