Steven's profile, qualifications and contact details have been verified by our experts
Steven
- Rate RM282
- Response 24h
-
Students12
Number of students accompanied by Steven since their arrival at Superprof
Number of students accompanied by Steven since their arrival at Superprof
RM282/h
Contact
- Python
- Programming languages
- Artificial Intelligence
- C#
- PostgreSQL
AI Setup for OpenClaw, Introduction, System Requirements & Environment Prep, Installing, SettingUp, Connecting OpenClaw AI Models, API Keys & External Integrations, Adding Tools & Plugins
- Python
- Programming languages
- Artificial Intelligence
- C#
- PostgreSQL
Lesson location
About Steven
I’m a senior full-stack engineer and cloud architect who has spent more than a decade building high-performance, production-grade systems across major Australian enterprises. My background spans frontend, backend, cloud, microservices, and event-driven architecture — and now I apply that same engineering discipline to modern AI systems, local model deployment, and agent-based automation.
I’ve delivered systems that operate at real scale, from Optus’ SUBHUB MVP “serving over 2 million local Australian users” to transforming Woolworths’ loyalty platform where I “increased system performance from 5 TPS to 100+ TPS on a single EC2 instance.” These experiences taught me how to design systems that are fast, reliable, and efficient — the same principles that matter when building AI agents and OpenClaw workflows.
My focus today is helping developers understand AI the way real engineers use it:
running models locally, integrating them with tools, building agents, automating workflows, and deploying practical AI systems that actually solve problems.
This course is built from real engineering experience — not theory. You’ll learn how to:
Set up local AI models (Ollama, LM Studio)
Connect them to OpenClaw
Build agents that use tools, memory, and workflows
Automate real tasks end-to-end
Deploy AI systems the same way we deploy production software
If you want to learn AI from someone who has built large-scale systems, solved real performance problems, and now applies that same mindset to AI engineering, you’re in the right place.
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About the lesson
- Primary
- Secondary
- SPM
- +12
levels :
Primary
Secondary
SPM
Form 6
STPM
Adult education
Bachelor
Masters
Diploma
Doctorate
Beginner
Intermediate
Advanced
Professional
Kids
- English
All languages in which the lesson is available :
English
# AI Setup for OpenClaw — Course Outline
# 1. Introduction to OpenClaw
- What OpenClaw is and what problems it solves
- Core components (agents, tools, pipelines)
- Typical use cases (automation, RAG, local AI workflows)
---
# 2. System Requirements & Environment Prep
- Supported operating systems (Windows, macOS, Linux)
- Hardware considerations (CPU vs GPU, RAM, storage)
- Installing required dependencies
- Python
- Node.js (if needed)
- Git
- Virtual environments
---
# 3. Installing OpenClaw
- Installing via package manager or source
- Folder structure overview
- Configuration files and their purpose
- Verifying installation with test commands
---
# 4. Setting Up Local AI Models
- Supported model backends (Ollama, LM Studio, etc.)
- Installing Ollama
- Pulling models (e.g., `mistral-nemo:12b`)
- Model quantization options and performance considerations
- Testing model responses locally
---
# 5. Connecting OpenClaw to Local Models
- Configuring model endpoints
- Setting up API routes
- Testing model connectivity
- Troubleshooting common issues
---
# 6. API Keys & External Integrations
- When API keys are needed
- Setting environment variables securely
- Integrating OpenAI, Anthropic, or others (optional)
- Best practices for key management
---
# 7. Adding Tools & Plugins
- What tools are and how OpenClaw uses them
- Installing built‑in tools
- Creating custom tools
- Testing tool execution
- Safety and sandboxing considerations
---
# 8. Building Your First Agent
- Agent structure
- Prompt templates
- Memory configuration
- Tool access permissions
- Running the agent end‑to‑end
---
# 9. Workflows & Automation
- Creating multi-step workflows
- Scheduling tasks
- Trigger-based automation
- Logging and monitoring
---
# 10. Debugging & Optimization
- Debugging agent behavior
- Improving model responses
- Reducing hallucinations
- Performance tuning for local inference
---
# 11. Packaging & Deployment
- Running OpenClaw as a service
- Local deployment vs server deployment
- Sharing agents with others
- Version control best practices
---
# 12. Capstone Project
Students build a fully functional OpenClaw agent including:
- Local model
- Tools
- Workflow
- Documentation
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Recommendations
Recommendations come from relatives, friends and acquaintances of the teacher
1
I am delighted to recommend Steven as a programming tutor specializing in JavaScript for both front-end and back-end development. Their deep understanding of the language and ability to explain complex concepts clearly have significantly improved my programming skills. Steven employs a structured yet flexible teaching approach, making learning engaging and effective. Steven is always patient, responsive, and supportive, ensuring I fully grasp each topic. Without a doubt, Steven would be an invaluable resource for anyone looking to excel in JavaScript programming and programming in general.
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Rates
Rate
- RM282
Pack rates
- 5h: RM1409
- 10h: RM2819
online
- RM282/h
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