Live Online + On-Site Enablement · Dual Delivery Modes
Enterprise AI Agent Training Program
Five scenario-based enterprise training courses · OpenClaw + Claude Code + Harness Engineering
As AI moves from a "chat assistant" to a 24/7 autonomous "digital employee," the working paradigm of every role in the enterprise will be fundamentally reshaped. This training series is designed specifically for enterprise teams, helping organizations build end-to-end AI Agent capabilities — from "awareness alignment" to "secure production" — in the shortest possible time.
5Scenario-Based Courses
6Days, Complete System
100,000+Trainees
Course System Overview
Course A Awareness
AI Agent Strategic Awareness & Quick Start
Course B Hands-on
AI Agent Enterprise Hands-on Bootcamp
Course C Security
AI Agent Security Governance & Production Deployment
Course D Advanced
Claude Code Dev Productivity Revolution
Course E Systems
Harness Engineering · Production-grade Agent Systems
Recommended Combinations
A + B 3 days Quick Start
A + B + C 4 days Secure Production
Full Suite 6 days Complete Enablement
Course A · Awareness
AI Agent Strategic Awareness & Quick Start
Helps every role understand how AI Agents unlock organizational efficiency, and lets you build your first Agent hands-on within a single day.
Role-Based Benefits
| Role | Transformation Pain Point | Capabilities After Training |
|---|---|---|
| Ops / SRE | Daily inspections, alert triage, and SOP execution consume huge amounts of time | Can configure a Heartbeat autonomous inspection Agent: scheduled service-status checks, automated basic remediation, and tiered alerting |
| Frontend / Backend / Full-stack | Many repetitive development tasks, with no AI-assisted development methodology | Understand how to use Agents to automate code review, test generation, and documentation maintenance, and master Skill extension capabilities |
| Product Manager | Competitor monitoring, user-feedback consolidation, and requirements drafting are extremely time-consuming | Can configure an information-aggregation Agent that performs competitor inspection plus automated entry into multidimensional tables |
| Business / Finance | Heavy manual reporting, data reconciliation, and report compilation | Understand how Agents enable cross-system data scraping, form filling, and report generation |
Course Outline
Morning Strategic Awareness & Organizational Value
Module 1 · The AI Agent Wave & the Organizational Efficiency Revolution
- Three leaps in AI capability: Copilot → single Agent → multi-Agent systems
- Real-world enterprise Agent adoption across industries: 3x+ ROI growth
- Global Agentic AI market trends (CAGR 43.8%)
Module 2 · The Enterprise Data Dilemma & How Agents Break Through
- The average enterprise runs 897 applications, with 71% siloed and disconnected
- Agents as the glue for business workflows: API + browser automation + file operations
- Local-First data-sovereignty architecture vs. the three major risks of cloud Agents
Module 3 · OpenClaw Architecture Deep Dive & Ecosystem Overview
- Endorsed by Jensen Huang at GTC 2026 + a phenomenal 250K-Stars product
- Five design philosophies: Local-First / LLM-Agnostic / IM-as-the-interface
- Side-by-side comparison of the four major frameworks and an enterprise selection guide
Afternoon Hands-on Quick Start & Role-Based Scenario Workshop
Module 4 · 10-Minute Hello World & Multi-Platform Integration
- One-click OpenClaw installation and the Onboard wizard
- Integration demos for WeChat, WeCom, and Feishu
- First taste of extending capabilities with Skills
Module 5 · Shaping the Agent Soul & a First Look at the Heartbeat Mechanism
- The disruptive power of plain-text configuration with SOUL.md
- Hands-on four-layer construction: Identity / Style / Rules / Boundaries
- Heartbeat: the paradigm shift from passive response to proactive inspection
Module 6 · Role-Based Scenario Workshop & Adoption Roadmap
- Group discussion: designing Agent scenarios by role
- Group sharing + instructor feedback
- 30/60/90-day adoption plan
Course B · Hands-on
AI Agent Enterprise Hands-on Bootcamp
Two days to walk your technical team through the full pipeline: deployment → tuning → memory management → automation closed loop.
Role-Based Benefits
| Role | Transformation Pain Point | Capabilities After Training |
|---|---|---|
| Ops / SRE | Drowning in daily alerts and executing SOPs by hand | Can independently deploy an OpenClaw + Heartbeat inspection system for automated monitoring, tiered alerting, and basic self-healing |
| Frontend / Backend / Full-stack | Heavy repetitive development, time-consuming code review, lagging documentation | Master Skill development + browser automation, and can build customized business Agents |
| Architect | Need to evaluate Agent technology choices, security architecture, and cost models | Master hybrid model routing + Fallback fault tolerance + zero-trust deployment architecture |
| Product Manager | Has business ideas but depends on the engineering backlog | Can build business Agent prototypes using SOUL.md + existing Skills |
Course Outline
Day 1 Infrastructure Deployment + Soul Tuning + Memory Architecture
Module 1 · Enterprise-Grade Deployment in Practice
- Domestic cloud server selection and ROI calculation
- Docker + systemd dual-safeguard daemon architecture
- Tailscale zero-public-IP secure tunneling solution
- Hands-on: deploy a production environment from scratch in 30 minutes
Module 2 · Deep Tuning of SOUL.md
- Full breakdown of the Workspace "seven swords" and the three-layer architecture model
- Four-layer SOUL.md construction: Identity / Style / Values / Boundaries
- Five rules of writing + Good/Bad Case comparison
- Hands-on: forge the soul of an enterprise R&D assistant + boundary-breach red/blue exercise
Module 3 · Four-Layer Memory Architecture & Persistence Management
- Immutable core → dynamic tools → semantic memory → real-time sessions
- Dual-engine retrieval: hybrid Embedding + BM25 strategy
- Hands-on: the four-step memory surgery (view, correct, export, clone)
Module 4 · Heartbeat + Cron Autonomous Scheduling System
- A five-step decision tree for Cron vs. Heartbeat scenario selection
- HEARTBEAT.md design and the four golden rules
- Hands-on: Cron report generation + Heartbeat integrity inspection
Day 2 Skill Extension + Cost Control + Role-Based Hands-on Closed Loop
Module 5 · The ClawHub Ecosystem & Custom Skill Development
- Skill architecture and the four-layer priority override network
- ClawHavoc supply-chain security and the five-step selection method
- SDL syntax and production-grade SKILL.md authoring
- Hands-on: end-to-end development of a business-data inspection Skill
Module 6 · Hybrid Model Routing & Extreme Cost Control
- Token economics: real cost breakdown and the three-layer pyramid model
- Dual-Provider configuration: dynamic switching between a domestic base model and an overseas flagship
- Fallback fault-tolerance chains and a three-tier cost defense line
- Hands-on: configure hybrid routing + trigger and verify silent degradation
Module 7 · Role-Based Business Automation in Practice
- Core principles of browser automation and locating business objects
- Ops team: automated inspection reports + fault-triage Agent
- Dev team: cross-system data filling + automated testing Agent
- Product/business team: competitor monitoring + intelligent daily briefing Agent
Module 8 · Showcase & Adoption Planning
- Each group demos its results + instructor feedback
- Enterprise Agent adoption roadmap (30/60/90 days)
- Delivery of the configuration template library and follow-up learning resources
Course C · Security
AI Agent Security Governance & Production Deployment
Addresses the security concerns of CTOs/CISOs and clears the final obstacles to taking enterprise-grade Agents live.
Role-Based Benefits
| Role | Transformation Pain Point | Capabilities After Training |
|---|---|---|
| CTO / VP of Engineering | Need to assess the risk of launching Agents, but lack a security framework to reference | Master the full landscape of enterprise-grade Agent security architecture and make well-grounded launch decisions |
| SRE / Ops Architecture | No standards for network exposure, access control, and log auditing in Agent deployments | Can independently configure a zero-trust network + Docker sandbox + a complete audit logging system |
| Security Team | Lack hands-on experience with emerging threats like supply-chain attacks and prompt injection | Master ClawHavoc attack postmortems + Skill auditing methods + hands-on prompt-injection defense |
Course Outline
Morning Threat Awareness & Security Architecture
Module 1 · The Full Landscape of Agent Security Threats
- The security crisis of 135,000 exposed instances and the five-step trap chain
- Full postmortem of the ClawHavoc supply-chain poisoning incident
- Analysis of the CVE-2026-25253 remote code execution vulnerability
- The MIT/Harvard/Stanford "Agents of Chaos" research warning
Module 2 · Zero-Trust Architecture & Security Hardening
- Zero-public-IP deployment architecture: Tailscale Serve/Funnel
- The six locks of systemd security hardening and Docker sandbox isolation
- Secure API Key migration: four-layer resolution priority + chmod 600
- Hands-on: configure a complete zero-trust network architecture
Afternoon Production Governance & Compliance Practices
Module 3 · ClawHub Supply-Chain Security & Skill Auditing
- The limits of triple scanning (independent audits detect only 2.3%)
- The five-step secure selection method + hands-on Skill code review
- Four principles of System Prompt hygiene
Module 4 · Cost Circuit Breakers & Model Security Defenses
- The risk of runaway Token costs: 200 vs. 5,000+ CNY per month
- A three-tier cost defense line: hard circuit breaker + silent degradation + post-hoc audit
- Jailbreak defense and the principles of an LLM firewall
Module 5 · The Production Deployment Checklist & Wrap-up
- A three-layer security checklist covering the network, authentication, and operations layers
- Dynamic key rotation + strong API authentication
- Hands-on: complete the ultimate Production-Ready checklist
Course D · Advanced
Claude Code Dev Productivity Revolution
Use an AI terminal agent to reshape your engineering team's coding, review, testing, and operations workflows.
Role-Based Benefits
| Role | Transformation Pain Point | Capabilities After Training |
|---|---|---|
| Backend / Full-stack Developer | Heavy repetitive coding, time-consuming manual code review, lagging documentation | Master the three core Claude Code commands and use AI to perform code review, batch refactoring, and automatic PR summary generation |
| SRE / Ops | Accumulating technical debt and delayed discovery of security vulnerabilities | Deploy an OpenClaw + Claude Code overnight self-healing system that scans for vulnerabilities in the early hours and submits fix PRs |
| Architect / Tech Lead | Refactoring large legacy codebases carries high risk | Master multi-project collaborative analysis across 50+ files and design AI-based engineering pipelines |
Course Outline
Morning Claude Code Core Capabilities & Engineering in Practice
Module 1 · The Awakening of the CLI Agent & the Security Sandbox
- Returning from cloud Agents to foundational infrastructure: why the terminal is the most powerful vehicle for refactoring
- The efficient instant-feedback workflow of the REPL read-eval-print loop
- Enterprise security boundaries: sandbox rules, file-system allowlists, and OAuth integration
- Hands-on: practice the three core commands /edit · /search · /run
Module 2 · Multi-File Collaboration & Legacy Code Refactoring
- Memory-control and dependency-graph strategies for 50+ source files
- Tracing legacy API call chains across projects and automatically generating patches in batches
- Hands-on: integrate a CI/CD pipeline — pre-commit hook + security pre-scan + PR semantic summary
Afternoon AI-Driven Data Analysis & the Overnight Self-Healing System
Module 3 · Building an End-to-End Data Analysis Pipeline
- Claude Code-driven three-stage architecture: collection & parsing → reasoning engine → rendering & generation
- Hands-on: build a Python data-analysis script using natural-language commands
- Observe how the AI self-diagnoses errors and retries corrections
Module 4 · The Overnight Code Self-Healing Lab
- Bridging via the MCP protocol: a dual-engine architecture with OpenClaw orchestrating and Claude Code executing
- Heartbeat wakes up in the early hours → clones a branch → scans from both attacker and defender perspectives
- Hands-on: deploy a complete overnight self-healing workflow
Module 5 · Showcase & Dev Productivity Planning
- Each group demos its results + instructor feedback
- Planning the AI toolchain for the engineering team
- Q&A + paths for further deepening
Course E · Systems
Harness Engineering · Production-grade Agent Systems
From "it works" to "it's reliable": build the engineering system that lets AI Agents run autonomously, verifiably, and observably in production.
Why this course is essential right now: The biggest mindset shift in AI engineering in 2026: the model itself is no longer the decisive variable — the "harness engineering" around the model is. By improving the Harness alone, the LangChain team jumped from 30th to 5th place on Terminal Bench 2.0 without changing the model. Anthropic research confirms that 65% of Agent failures stem from Harness defects rather than insufficient model capability.
Role-Based Benefits
| Role | Transformation Pain Point | Capabilities After Training |
|---|---|---|
| Architect / Tech Lead | Agents can demo but can't go to production; no systematic method for making them reliable | Master the five-layer Harness architecture (orchestration/validation/memory/guardrails/observability) and design production-grade Agent runtime architectures |
| Platform Engineer / SRE | Agents aren't observable or auditable, and failures are hard to reproduce | Can deploy a complete Agent observability system: tracing + cost dashboard + session replay + anomaly alerting |
| AI Engineering Lead | Teams produce more output with Agents but can't measure quality and ROI | Master the four Harness Engineering metrics (cost per PR / time to merge / review speed / compute spend per developer) |
Course Outline
Morning Harness Engineering Theory & Architecture Design
Module 1 · The Four Paradigms of AI Engineering & the Core Idea of the Harness
- Evolution of four paradigms: Prompt Eng → Context Eng → Agent Eng → Harness Eng
- The core formula: Agent = Model + Harness — the model is a stateless reasoning engine, the Harness is the runtime control plane
- METR assesses that Claude Opus 4.6 can independently complete 14.5h human tasks
- The Mitchell Hashimoto principle: "Every time an Agent makes a mistake, engineer a fix for it"
Module 2 · A Deep Breakdown of the Five-Layer Harness Architecture
- Layer 1 Tool Orchestration: dynamic error recovery + cross-tool chained calls + MCP in practice
- Layer 2 Validation Loop: a generation-evaluation separation architecture (applying GAN ideas to Agents)
- Layer 3 Context & Memory: cross-session state retention + PROGRESS.md + Compaction vs. Reset
- Layer 4 Guardrails: permission boundaries + transactional rollback + human approval gates
- Layer 5 Observability: tracing / Token attribution / session replay / cost attribution
- Hands-on: design a five-layer Harness blueprint for an existing Agent
Afternoon Building the Harness in Practice & the Metrics System
Module 3 · Agent Failure Modes & Hands-on Harness Fixes
- A deep postmortem of Anthropic's three major failure modes
- Victory Declaration Bias: the Agent claims completion without verifying
- Context Anxiety: a hasty wrap-up when context runs out
- One-shotting Overreach: doing too much at once and losing control
- Hands-on: diagnose failure modes in a real business Agent + apply Harness fixes
Module 4 · Multi-Agent Collaboration & Long-Running Harnesses
- Anthropic's long-running Agent architecture: the dual Initializer + Coding Agent system
- Multi-Agent division of labor: a three-stage Planner → Generator → Evaluator pipeline
- Context management strategy: choosing between Compaction and Context Reset
- Hands-on: build a generate-evaluate-iterate multi-Agent workflow
Module 5 · The Metrics System & Organizational Adoption Planning
- The four core Harness Engineering metrics
- The AI Velocity Paradox: the organizational risk of more code but invisible quality
- A Harness maturity assessment framework and a 90-day adoption roadmap
- Q&A + customized recommendations for each team
Dual Delivery Modes
All course content is identical, with flexible switching between two hands-on environments
Mode A
AI Agent Workstation Delivered with the Course
The instructor brings a pre-configured AI Agent workstation on-site, ready to use out of the box, sparing trainees any environment setup time. After the training, the device is left with the client as the team's always-on Agent runtime node.
Mode B
Bring Your Own Device + On-Site Deployment
Trainees use their own laptops or the company's servers and deploy on-site following the one-click installation script provided by the instructor. Setting up the environment is itself the first hands-on exercise of Course B, with zero additional hardware cost.
Build a Custom Training Plan for Your Team
We'll recommend the optimal course combination and delivery mode based on your organization's specific needs
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