# Vision And Mission The future for AGI is programmability, which will come from smart contracts(As mentioned by OpenAI CPO). However, both AI Agents and smart contracts are facing a huge threat from malicious hackers. No one is able to provide a bulletproof solution to these threats, as hackers find newer attack vulnerabilities that existing security solutions fail to detect. With frontier models’ guardrails failing regularly to safeguard against newer prompt injection sequences, and with daily evolving attack vectors for smart contracts, two of the biggest emerging technologies(AI Agents and Smart Contracts) are facing huge potential threats. Our adversarial swarm is the solution that can safeguard both AI Agents and smart contracts by simulating millions of attack patterns with adversarial agents to train self-evolving guardrails for agents and a red-team co-pilot for smart contracts. **Vision:** To secure the decentralised, agentic economy of the future with autonomous adversarial intelligence, empowering developers and users to build, trade, and interact safely and confidently. **Mission:** * To develop the most advanced adversarial AI agents that can proactively identify, simulate, and mitigate any emerging vulnerabilities in the on-chain economy. * To create a self-evolving, AI-powered security layer that scales with the growth of autonomous agents and decentralised applications. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://quillainetwork.gitbook.io/quillai-network/introduction/vision-and-mission.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.