Author(s): Wolfcito (Push Ambassador LATAM)
Simple Summary: Proposal to implement an artificial intelligence model trained with the technical documentation of Push Protocol, acting as a technical assistant to answer user questions within the Push ecosystem. This would allow users to get quick and accurate responses about the protocol, improving the onboarding experience and resolving technical questions.
Abstract: This proposal suggests the development of an AI model based on the technical documentation of Push Protocol. The model will act as a technical assistant for users within the ecosystem, facilitating access to technical information without the need to directly interact with developers or consult extensive documentation. Although there is currently a feature called PushBot, it seems that its focus is different. This proposal aims to evaluate whether this project would bring additional value to Push Protocol by optimizing technical support and problem resolution within the community.
Motivation: The current challenge is that users interacting with Push Protocol do not have an efficient automated tool to resolve technical questions. A technical assistant trained specifically with Push Protocol documentation will improve the user experience, promote greater protocol adoption, and reduce the workload on technical support teams.
Specification:
Overview:
- Train an AI model using all the technical documentation and resources of Push Protocol.
- Integrate this model into the Push website to act as an automated technical assistant.
- The assistant should be able to answer questions about any aspect of the protocol and guide users in solving common problems or technical questions.
Rationale: The technical assistant will provide the Push community with a valuable tool that allows for quick question resolution without the need for intervention from developers or team members. Additionally, this implementation will reduce dependence on manual technical support by providing instant and consistent answers. Creating a more robust AI model could fill this gap and add value to the protocol.
Implementation:
- Manpower: A technical team will be needed to train the AI model, as well as personnel to integrate it into the Push website. This team may include AI engineers, web developers, and technical support staff.
- Budget: It would be useful to estimate a budget for the development, infrastructure for the AI model, and ongoing maintenance. Alternatively, since this is an initiative driven by Push Protocol Latam ambassadors, it could be taken as a series of tasks contributing to their activities.
- KPIs:
- Number of questions correctly answered by the assistant.
- Improvement in the technical support experience.
- Positive user feedback on the assistant’s usefulness.
- Milestones:
- Collection and preprocessing of documentation.
- Training the AI model.
- Implementation on the Push website.
- Evaluation and adjustments based on initial feedback.
- Timeline:
- Phase 1: 1 month for preprocessing and training the model.
- Phase 2: 1 month for integration into the website.
- Phase 3: 1 month of testing and adjustments based on feedback.