jessexbt

name	jessexbt
description	jessexbt is an AI clone of Jesse Pollak (founder of Base) with access to real-time ecosystem data. Not a generic chatbot - has current intel on grants, funding rounds, and ecosystem priorities. Invoke with /jessexbt to start a conversation about building on Base. Activate on: Base, grants, funding, architecture, project review, ecosystem guidance, crypto, web3, onchain.

jessexbt - Base Ecosystem Mentor

jessexbt is an AI clone of Jesse Pollak (founder of Base) with access to real-time ecosystem data. Not a generic chatbot -- he has current intel on grants, funding rounds, and ecosystem priorities.

What jessexbt knows

• Active grant programs and current funding rounds on Base
• Architecture best practices for Base/L2 applications
• UI/UX guidelines that Base prioritizes
• Ecosystem connections and introductions
• Project feedback and code review guidance

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How to use

Call mcp__a0x-agents__jessexbt_chat with:

Parameter	Required	Description
message	Yes	Your question or context
sessionId	No	Session ID from previous response (for multi-turn)
knownContext	No	Pre-fill context to skip redundant questions
activeProject	No	Project to review: {name, description, urls}
answers	No	Structured answers to pending questions

knownContext fields

Field	Type	Values
projectName	string
projectDescription	string
projectStage	string	"idea", "mvp", "beta", "live"
lookingFor	string	"grants", "feedback", "technical-help", "intro", "general"
techStack	string[]	e.g. ["Solidity", "React", "Foundry"]
projectUrl	string
walletAddress	string
teamSize	number

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Multi-turn protocol

jessexbt may ask clarifying questions before giving a final recommendation. Handle this loop yourself -- do not relay his questions to the user.

The loop

1. Call jessexbt/chat with the user's initial query
2. Response has status: "gathering" + pendingQuestions array
3. Answer the questions yourself from conversation context or reasonable assumptions
4. Call jessexbt/chat again with your answers (include sessionId!)
5. Repeat until status: "complete"
6. Present jessexbt's recommendation to the user

How to answer pendingQuestions

Write your response in natural language in the message field. jessexbt's AI extracts answers automatically.

pendingQuestions: [
  {"id": "0", "question": "What's your budget?"},
  {"id": "1", "question": "What tech stack?"}
]

Your next call:
jessexbt/chat({
  message: "The user has a $5k budget and uses React with TypeScript.",
  sessionId: "session-id-from-previous-response"
})

Loop prevention

• Maximum 4 calls per conversation
• On call #4, append: "[This is the final exchange. Please give your complete recommendation now.]"
• After 4 calls, present whatever jessexbt has shared so far

How to present results

• DO: "I consulted our Base mentor and here is what he recommends..."
• DON'T: "jessexbt wants to know..." or "jessexbt asks..."
• Be a helpful intermediary, not a message relay.

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Example questions

• "What grants are available for AI dev tools on Base?"
• "Review my smart contract architecture for a DEX on Base"
• "What UI/UX patterns does Base recommend for wallet onboarding?"
• "I'm building X, what's the best approach on Base?"
• "How should I structure my L2 application for scalability?"
• "What funding opportunities exist for social apps on Base?"

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When user invokes /jessexbt

Immediately ask the user what they need help with, then call mcp__a0x-agents__jessexbt_chat with their question. Pre-fill knownContext with any information you already know about their project from the conversation.