AgentLock VS Diffyn

AgentLock's answer

AgentLock sits between the agent and the outside world instead of trusting the agent to behave. Every HTTP call, MCP tool call, browser action or SSH command becomes a request that a policy decides on, and anything sensitive waits for a human approval that arrives on the phone. Credentials live in the vault and are injected only at execution time, so an agent can use a key without ever seeing it - and if nobody approves in time, the action simply does not happen.

Diffyn's answer:

Addresses workflow and change management on LLM prompts, provide teams with traceability and visualization of tests across multiple models, provide deeper understading into efficiency of these prompts.

AgentLock's answer

A secrets manager stores keys, but once an agent holds one, nothing stops it from making the wrong call. AgentLock covers both halves: the encrypted vault plus a gateway with policies, human approval, automatic redaction, a full timeline and undo for supported actions. It is available as an MCP server and an SDK, so an existing agent can be routed through it without a rewrite, and the free plan already covers 100 actions a month with one agent.

Diffyn's answer:

Diffyn is the platform that specializes on both change management and multi-model analysis.

AgentLock's answer

TypeScript across the stack: a React dashboard on Vercel, Supabase with Postgres, Auth and Edge Functions for data, policies and the encrypted vault, a self-hosted runner for actions that need a private network, React Native for the iOS and Android approval app, and Stripe for billing.

Diffyn's answer:

React, Next.js, POSTGRESQL

AgentLock's answer

Developers who run autonomous agents against real systems - deployments, payments, mail, customer data - and want an audit trail and a stop button instead of hoping the prompt holds. Small teams also use it to let an agent work with shared credentials without handing the keys to every team member or to the model itself.

Diffyn's answer:

Professionals incorporating LLMs or AI tools in their workflow and wants to keep track of changes and test their prompts.

Diffyn's answer:

I started working on Diffyn when I notice that prompting has become an essential part of work across many industries. While there are version control platofrms like github, they are not designed for just prompt management are can be overkill such applications, it is also not integrated natively with various LLMs and relevant tools for users to validate ideas and visualise results properly.