Understand Agent Basics
Explain how LLMs use tokens, embeddings, context, and prediction so you can design clearer prompts and workflows.
Launch Your OpenClaw from Scratch
Taught by Michael Shimeles
Learn how to plan, launch, and refine your OpenClaw agent.
What you'll learn
Prompt with Precision
Write concise instructions that define the task, constraints, process, and definition of done for reliable agent behavior.
Set Up OpenClaw
Deploy OpenClaw, connect model access and communication, and configure the core files that shape identity, tools, memory, and routines.
Connect Practical Tools
Connect services such as Notion, Trello, Google Calendar, search, and email, then validate each tool with real actions.
Automate Workflows
Build skills, subagents, and scheduled automations that preserve context and handle repeatable work without blocking your main agent.
Refine and Scale
Improve OpenClaw over time with recursive skill refinement, reverse prompting, memory, and lean context management.
Course curriculum
1 part · 11 chapters
About Michael Shimeles
DevX Engineer @ Convex
Michael Shimeles is a Toronto-based full-stack engineer and AI builder. He has experience building real automation systems and agent-oriented tooling. Michael focuses on mental models, practical prompt strategy, and agent orchestration so builders can move beyond experimentation to systems that work reliably.
You’ll learn from his direct experience integrating agents like OpenClaw into workflows and architecting recursive improvement structures.
