Botcamp Cohort 13

Complete these setup tasks before the cohort begins on April 21st.

An introduction to algorithmic trading bots and the cryptocurrency exchange landscape. Explore the differences between various types of algo trading strategies, including arbitrage, trend-following, and market making. Understand the tradeoffs between different exchange types—spot vs perpetual, centralized vs decentralized, and central limit order books vs automated market makers—and learn about the critical role that market makers play in providing liquidity to crypto markets.

A comprehensive overview of the Hummingbot API covering how to fetch market data, execute trades, and create automated trading bots. Understand the distinct roles and interactions between the Hummingbot API, MCP Server, and Condor in the overall architecture. Set up your development environment for the cohort and verify that you have access to all the necessary tools and resources needed for hands-on exercises.

Trace the history of market making from traditional finance through the development of the groundbreaking Avellaneda-Stoikov model and its evolution into modern crypto market making. Learn the business models, trading strategies, and operational protocols employed by professional market makers. Apply these concepts by running your first market making scripts and controllers with Hummingbot, while understanding how to effectively balance risk and return in your trading approach.

Gain a deep understanding of the Hummingbot StrategyV2 Framework architecture and how it enables flexible, modular strategy development. Walk through each core component of the framework, including Executors, Controllers, and Data Providers. Master the different executor types available in Hummingbot—Order, Position, Grid, LP, Swap, and more. Learn when to use each executor type, how to configure them properly, deploy them via the API, and integrate them effectively within your controllers.

An introduction to decentralized finance and on-chain trading across Solana and Ethereum ecosystems. Understand the differences between lending pools, liquidity pools, vaults, routers, and various decentralized exchange types. Learn about different on-chain yield strategies including staking, lending, liquidity provision, and looping—along with their expected returns, risks, and tradeoffs. See a live demonstration of how to connect your wallet securely and the operational security measures you should implement to protect your assets.

A hands-on session exploring a professional market making strategy operating at scale. Watch a live demonstration of the PMM Mister strategy running with multiple controllers, all managed using AI. Compare how it differs from the original PMM V1 strategy and understand the improvements in the new architecture. Learn to implement your own unique trading logic within the V2 Framework architecture.

A deep dive into liquidity provision strategies and how they compare to traditional order book-based market making approaches. Analyze and compare liquidity provision mechanisms across Meteora, Orca, Uniswap, and PancakeSwap to understand each platform's unique characteristics. Learn to use the LP executor and controller for automated liquidity management across different exchange types and DeFi protocols.

Demystify the jargon and gain a practical understanding of how to use agent harnesses like OpenClaw, Claude Code, and Condor to create personal AI agents. Learn how Hummingbot MCP and Skills fit into the overall architecture. Understand how Condor provides a flexible interface for your AI model of choice to interact with the Hummingbot API and create AI-powered trading agents. Explore the architectural differences between various harnesses and AI models, and learn when to build agents versus when to add skills to existing harnesses.

Create an AI-powered trading agent that combines Hummingbot's robust data collection and trade execution capabilities with intelligent, autonomous decision-making. Learn how the Hummingbot Agent Specification defines a reliable, autonomous trading system that seamlessly integrates Hummingbot execution with AI-driven decision logic. Build a fully functional trading agent that can run across Condor, OpenClaw, and other harnesses, ensuring compatibility and portability across different deployment platforms.

Learn to deploy, monitor, and manage agent swarms—coordinated groups of trading agents that work together and learn from their collective performance over time. Discover best practices for swarm orchestration, comprehensive logging, and performance optimization when running multiple agents across different environments. Understand how to implement feedback loops that enable your agents to adapt their strategies based on market conditions and historical results.

Get personalized help with your agent design, implementation questions, and competition preparation from Mike.

Get personalized technical support for your agent swarm implementation and deployment from Federico.

Present your strategy to fellow cohort members and industry experts to earn your official Hummingbot certification. After presentations, we unleash the participating agents in a 48-hour live trading competition where they compete autonomously for USDC prizes in real market conditions.

Review the final results of the 48-hour live trading competition and dive into detailed analysis of the most interesting agents. Celebrate the achievements of all participants as we award USDC prizes to the winners and recognize outstanding contributions to the cohort.