AI Agents Training in Auckland

This instructor-led, live training in Auckland (delivered online or on-site) is tailored for advanced-level AI engineers, robotics developers, and automation specialists who wish to harness DeepSeek to build intelligent AI agents and autonomous systems.

By the conclusion of this training, participants will be able to:

• Understand the architecture and capabilities of DeepSeek AI models.
• Integrate DeepSeek into AI agents to support decision-making and automation.
• Apply reinforcement learning techniques to train autonomous systems.
• Deploy AI-driven autonomous agents in real-world environments.

Autonomous AI agents are being rapidly integrated into decision-making processes across sectors such as defence, healthcare, finance, and infrastructure. As these systems gain greater independence and autonomy, there is an urgent need for robust ethical frameworks, governance mechanisms, and regulatory oversight to guide their design and deployment.

This instructor-led, live training (online or on-site) is designed for advanced-level professionals who wish to explore the ethical, societal, and regulatory implications of deploying autonomous AI agents in real-world environments.

By the end of this training, participants will be able to:

• Analyse the ethical risks and moral dilemmas posed by autonomous AI agents.
• Evaluate governance frameworks and regulatory models relevant to high-stakes AI deployment.
• Assess accountability, explainability, and transparency mechanisms in autonomous systems.
• Develop strategies for aligning AI agent behaviour with legal, ethical, and societal values.

Format of the Course

• Interactive lectures and discussions.
• Case studies and role-playing simulations.
• Hands-on analysis of governance models and ethical frameworks.

Course Customisation Options

• To request customised training for this course, please contact us to arrange.

AI-powered automation merges the flexibility of no-code platforms with the intelligence of large language models and autonomous agents to deliver scalable, intelligent systems.

This instructor-led, live training (available online or onsite) is designed for intermediate-level professionals seeking to design, build, and refine automation pipelines enhanced by AI-driven decision-making, orchestration, and self-execution capabilities.

By the conclusion of this training, participants will be able to:

• Design no-code automation workflows enriched with AI interpretation and responsive actions.
• Leverage prompt chaining, webhook triggers, and APIs to construct scalable logic flows.
• Develop intelligent applications that seamlessly connect services and interpret data autonomously.
• Understand, design, and deploy AI agents capable of goal-oriented planning and execution.

Course Format

• Interactive lectures and guided discussions.
• Abundant hands-on exercises and practical practice.
• Real-time implementation within a live-lab environment.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.

This instructor-led, live training in Auckland (available online or on-site) is designed for intermediate-level AI developers, security specialists, and compliance officers who aim to design and implement secure AI agents while effectively addressing ethical concerns and ensuring system robustness.

By the end of this training, participants will be able to:

• Identify security risks and ethical challenges inherent in AI agent development.
• Apply security-first design principles to AI models.
• Implement adversarial robustness techniques to protect AI agents from attacks.
• Ensure adherence to ethical AI guidelines and regulatory standards.

Edge & Lightweight Agents is a hands-on course dedicated to deploying agentic AI workloads on resource-constrained devices. Participants will learn to build, optimise, and manage lightweight agents capable of local reasoning and inference, thereby enhancing speed, privacy, and reliability within distributed environments. The course places a strong emphasis on performance tuning, low-latency design, and the integration of hardware and software.

This instructor-led, live training (available online or on-site) is tailored for intermediate-level professionals who wish to implement and optimise on-device agentic systems using Python and edge AI frameworks.

By the conclusion of this training, participants will be able to:

• Understand the architecture and challenges associated with running agentic AI on edge devices.
• Design lightweight agent loops suitable for constrained environments.
• Implement local inference using TensorFlow Lite, PyTorch Mobile, and ONNX.
• Integrate agents with sensors, actuators, and IoT platforms.
• Optimise performance, energy consumption, and latency for real-time operation.

Course Format

• Interactive lectures complemented by practical demonstrations.
• Hands-on development in local or emulated environments.
• Project-based learning supported by guided implementation exercises.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange a discussion.

This instructor-led, live training in Auckland (online or on-site) is designed for intermediate to advanced-level AI developers, researchers, and multimedia engineers who aspire to build AI agents capable of understanding and generating multi-modal content.

By the conclusion of this training, participants will be able to:

• Develop AI agents that process and integrate text, image, and speech data.
• Implement multi-modal models such as GPT-4 Vision and Whisper ASR.
• Optimise multi-modal AI pipelines for efficiency and accuracy.
• Deploy multi-modal AI agents in real-world applications.

This instructor-led, live training in Auckland (online or onsite) is aimed at beginner-level to intermediate-level developers and designers who wish to understand and build AI-powered personal assistants for various use cases.

By the end of this training, participants will be able to:

• Understand the core principles of AI-powered personal assistants.
• Learn the fundamentals of integrating language models with smart assistants.
• Build and customise a personal assistant using AI frameworks and tools.
• Deploy personal assistants for real-world applications in different industries.

This instructor-led, live training in Auckland (online or on-site) is designed for advanced-level AI engineers, enterprise software developers, and business leaders who wish to customise and deploy LLM-based AI agents for enterprise applications.

By the end of this training, participants will be able to:

• Understand the architecture and capabilities of open-source LLMs.
• Customise and fine-tune LLMs for enterprise use cases.
• Deploy AI agents using LangChain and Hugging Face.
• Integrate LLM-powered agents into business workflows.

This instructor-led, live training in Auckland (available online or on-site) is designed for advanced-level robotics engineers, AI researchers, and automation specialists who aim to develop AI-driven autonomous robotic systems for complex tasks and human-AI collaboration.

By the end of this training, participants will be able to:

• Understand the role of AI agents in robotic decision-making and automation.
• Implement AI-driven navigation and obstacle avoidance.
• Develop human-AI collaborative robotic systems.
• Deploy AI-powered perception and control systems in robots.

This course explores the design, coordination, and implementation of multi-agent systems (MAS) using Python. Participants will learn how to build agents that communicate, collaborate, and adapt to achieve shared objectives in complex, dynamic environments.

This instructor-led, live training (online or on-site) is aimed at advanced-level professionals who wish to design and implement multi-agent systems for intelligent automation, simulation, and decision-making applications.

By the end of this training, participants will be able to:

• Understand the architecture and principles of multi-agent systems.
• Develop agents capable of communication, coordination, and negotiation.
• Implement distributed environments for agent interactions.
• Apply reinforcement learning and planning in multi-agent contexts.
• Simulate cooperative and competitive agent behaviours.
• Design hybrid workflows combining humans and intelligent agents.

Course Format

• Instructor-led lectures and live demonstrations.
• Hands-on exercises using open-source agent frameworks.
• An applied group project simulating a multi-agent scenario.

Course Customisation Options

• To request customised training for this course, please contact us to arrange.

This instructor-led, live training in Auckland (online or on-site) is designed for intermediate-level financial professionals, risk analysts, and AI engineers who wish to develop and deploy AI-driven solutions for financial automation and fraud detection.

By the end of this training, participants will be able to:

• Understand the role of AI in financial automation and fraud detection.
• Build AI models to detect fraudulent transactions.
• Leverage machine learning for real-time risk assessment.
• Deploy AI-powered financial monitoring systems.

This instructor-led, live training in Auckland (available online or on-site) is designed for beginner to intermediate-level customer service professionals, chatbot developers, and automation teams who wish to implement AI-driven solutions for customer support and service automation.

By the end of this training, participants will be able to:

• Understand the fundamentals of AI-powered customer support.
• Develop and integrate AI chatbots to handle customer inquiries.
• Leverage natural language processing (NLP) and machine learning to enhance chatbot interactions.
• Deploy AI agents in real-world customer service applications.

This instructor-led, live training in Auckland (online or onsite) is aimed at intermediate-level to advanced-level healthcare professionals and AI developers who wish to implement AI-driven healthcare solutions.

By the end of this training, participants will be able to:

• Understand the role of AI agents in healthcare and diagnostics.
• Develop AI models for medical image analysis and predictive diagnostics.
• Integrate AI with electronic health records (EHR) and clinical workflows.
• Ensure compliance with healthcare regulations and ethical AI practices.

This instructor-led, live training in Auckland (online or onsite) is designed for beginner to intermediate-level AI developers and UI/UX designers who wish to learn how to build, optimise, and deploy AI-powered virtual assistants.

By the end of this training, participants will be able to:

• Design effective conversational AI workflows and UI/UX interfaces.
• Implement AI-driven natural language processing (NLP) models.
• Integrate AI assistants with APIs and third-party platforms.
• Deploy and maintain AI assistants for real-world applications.

Mistral AI is a powerful family of open-source and enterprise-ready AI models designed for language, multimodal, and agentic applications.

This instructor-led, live training (available online or on-site) is tailored for intermediate to advanced professionals who aim to build, deploy, and manage AI agents using Mistral's Medium 3, Le Chat Enterprise, and Devstral models.

By the conclusion of this training, participants will be able to:

• Grasp the architecture and capabilities of Mistral Medium 3, Le Chat Enterprise, and Devstral.
• Design and implement AI agents that leverage Mistral models for both enterprise and developer use cases.
• Integrate coding systems, connectors, and enterprise data into agent workflows.
• Optimise performance, cost, and compliance for agents powered by Mistral.

Course Format

• Interactive lectures and discussions.
• Abundant exercises and practical practice.
• Hands-on implementation within a live lab environment.

Course Customisation Options

• To request a customised version of this training, please contact us to arrange.

Python is the core language powering the development and orchestration of autonomous AI agents. This course focuses on practical implementation using modern SDKs and frameworks such as LangChain and AutoGen to build, connect, and manage agent workflows.

This instructor-led, live training (available online or on-site) is designed for intermediate-level backend engineers, platform engineers, and ML engineers who wish to implement and orchestrate autonomous agents using Python tooling and APIs.

By the end of this training, participants will be able to:

• Set up and configure Python-based environments for agentic systems.
• Use popular agent SDKs like LangChain and AutoGen to create functional agents.
• Integrate tools and APIs to extend agent capabilities.
• Orchestrate multi-agent workflows and communication patterns.
• Apply best practices for debugging, testing, and maintaining agentic codebases.

Format of the Course

• Interactive lecture and discussion.
• Hands-on programming exercises and live demos.
• Practical projects building end-to-end agent workflows.

Course Customisation Options

• To request a customised training for this course, please contact us to arrange.

Google Antigravity is an agentic development environment engineered to create autonomous agents capable of planning, reasoning, coding, and acting through Gemini 3’s multimodal capabilities.

This instructor-led, live training (available online or on-site) is designed for advanced-level technical professionals who wish to design, build, and deploy autonomous agents using Gemini 3 and the Antigravity environment.

Upon completing this training, participants will be equipped to:

• Construct autonomous workflows that leverage Gemini 3 for reasoning, planning, and execution.
• Develop agents within Antigravity capable of analysing tasks, writing code, and interacting with tools.
• Integrate Gemini-driven agents with enterprise systems and APIs.
• Optimise agent behaviour, safety, and reliability in complex environments.

Course Format

• Expert demonstrations combined with interactive discussions.
• Hands-on experimentation with autonomous agent development.
• Practical implementation using Antigravity, Gemini 3, and supporting cloud tools.

Course Customisation Options

• If your team requires domain-specific agent behaviours or custom integrations, please contact us to tailor the program.

This course teaches practical engineering techniques to design, build, test, and deploy agentic (autonomous) systems using Python. It covers the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production considerations.

This instructor-led, live training (online or onsite) is aimed at intermediate to advanced-level ML engineers, AI developers, and software engineers who wish to build robust, production-ready autonomous agents using Python.

By the end of this training, participants will be able to:

• Design and implement the agent loop and decision-making workflows.
• Integrate external tools and APIs to extend agent capabilities.
• Implement short-term and long-term memory architectures for agents.
• Coordinate multi-step orchestrations and agent composability.
• Apply safety, access control, and observability best practices for deployed agents.

Course Format

• Interactive lectures and discussions.
• Hands-on labs building agents with Python and popular SDKs.
• Project-based exercises that produce deployable prototypes.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.

This instructor-led, live training in Auckland (online or on-site) is aimed at advanced-level professionals who wish to master the techniques for deploying and managing AI agents in production environments.

By the end of this training, participants will be able to:

• Design and implement scalable AI deployment pipelines.
• Use tools like Docker and Kubernetes to containerise and orchestrate AI agents.
• Monitor and optimise AI agents in production environments.
• Implement CI/CD workflows for AI agent deployments.
• Ensure compliance with security and data governance requirements.

This instructor-led, live training in Auckland (online or onsite) is aimed at advanced-level AI professionals who wish to master reinforcement learning techniques and implement them for training AI agents in solving complex problems.

By the end of this training, participants will be able to:

• Understand the core principles of reinforcement learning and Markov Decision Processes (MDPs).
• Design and implement RL algorithms such as Q-Learning, SARSA, and Deep Q-Networks (DQN).
• Utilise frameworks like OpenAI Gym and RL libraries for practical applications.
• Train AI agents to solve real-world, multi-step decision-making problems.
• Address challenges such as exploration-exploitation trade-offs and convergence in RL training.

This instructor-led, live training in Auckland (online or on-site) is designed for intermediate-level AI developers and automation specialists who wish to integrate agentic capabilities into AI-powered applications.

By the conclusion of this training, participants will be able to:

• Grasp the core principles of agentic AI and autonomous decision-making.
• Implement goal-driven AI agents using self-optimisation techniques.
• Integrate multi-agent collaboration to tackle complex problem-solving challenges.
• Enhance AI-human interaction through adaptive user experiences.
• Deploy agentic AI models in real-world applications.

This instructor-led, live training in Auckland (available online or on-site) is designed for advanced-level AI professionals seeking to master the skills required to design, build, and deploy MAS that tackle complex, real-world problems.

By the conclusion of this training, participants will be able to:

• Understand the core principles of multi-agent system architectures.
• Implement strategies for communication, coordination, and decision-making within MAS.
• Apply game theory to model agent interactions and resolve conflicts.
• Leverage frameworks such as JADE to create scalable MAS solutions.
• Address key challenges including scalability, trust, and emergent behaviour in MAS.

This instructor-led, live training in Auckland (available online or on-site) is designed for advanced-level professionals seeking to develop and optimise multi-agent systems using Agentic AI frameworks.

By the conclusion of this training, participants will be able to:

• Grasp the core principles of Agentic AI within multi-agent environments.
• Develop AI-driven agents capable of autonomous interaction.
• Implement reinforcement learning to foster adaptive AI behaviour.
• Optimise both collaboration and competition among multiple agents.
• Apply Agentic AI across robotics, gaming, and enterprise automation.

This instructor-led, live training in Auckland (online or on-site) is designed for intermediate-level business analysts, RPA developers, and AI professionals who want to leverage the power of AI agents to drive business process automation.

By the end of this training, participants will be able to:

• Understand the role of AI agents in business process automation.
• Identify opportunities for automation in key business domains.
• Develop AI-driven solutions for customer support, finance, and supply chain workflows.
• Integrate AI agents with existing RPA and business systems.
• Evaluate and optimise AI automation strategies for greater efficiency.

Vertex AI Agent Builder is a no-code/low-code environment for creating grounded agents that combine generative models with retrieval-augmented generation (RAG), enabling teams to rapidly develop agents that leverage enterprise data and search to deliver accurate, context-aware responses.

This instructor-led, live training (available online or on-site) is designed for intermediate-level practitioners who wish to design, configure, and deploy smart agents using Vertex AI Agent Builder and RAG patterns.

By the end of this training, participants will be able to:

• Design grounded agent workflows using Agent Builder.
• Implement RAG pipelines with search and vector stores.
• Integrate enterprise data sources securely for retrieval.
• Evaluate and iterate agent behaviour using testing and metrics.

Course Format

• Interactive lecture and discussion.
• Hands-on labs using Vertex AI Agent Builder and RAG components.
• Project-based exercises to build and refine agents.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.

This instructor-led, live training in Auckland (online or on-site) is designed for intermediate-level game developers and AI enthusiasts who wish to effectively integrate AI agents into gaming applications.

By the conclusion of this training, participants will be able to:

• Understand the role of AI agents in modern gaming.
• Develop decision-making systems using decision trees and finite state machines.
• Implement pathfinding algorithms such as A* for in-game navigation.
• Apply reinforcement learning techniques to create adaptive AI behaviours.
• Optimise AI performance for real-time gaming environments.

LLMs and autonomous agent frameworks such as AutoGen and CrewAI are transforming how DevOps teams automate tasks like change tracking, test generation, and alert triage by emulating human-like collaboration and decision-making.

This instructor-led, live training (delivered online or on-site) is designed for advanced-level engineers who wish to design and implement DevOps automation workflows powered by large language models (LLMs) and multi-agent systems.

By the end of this training, participants will be able to:

• Integrate LLM-based agents into CI/CD workflows for intelligent automation.
• Automate test generation, commit analysis, and change summaries using agents.
• Coordinate multiple agents for triaging alerts, generating responses, and delivering DevOps recommendations.
• Build secure and maintainable agent-powered workflows using open-source frameworks.

Course Format

• Interactive lecture and discussion.
• Abundant exercises and practical activities.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.

This instructor-led, live training in Auckland (online or onsite) is aimed at advanced-level professionals who wish to leverage Agentic AI for decision-making in complex business and technical scenarios.

By the end of this training, participants will be able to:

• Understand the principles of autonomous decision-making in AI.
• Design and implement AI agents that operate with minimal human intervention.
• Integrate Agentic AI into automation workflows and business systems.
• Optimize AI-driven decision processes for efficiency and scalability.
• Ensure compliance, security, and ethical considerations in AI autonomy.

This instructor-led, live training in Auckland (online or onsite) is aimed at intermediate-level professionals who wish to delve deeper into the design and development of autonomous agents for practical applications.

By the end of this training, participants will be able to:

• Understand the foundational concepts of autonomous agents.
• Explore real-world applications of autonomous AI agents.
• Design, train, and implement agents using reinforcement learning.
• Integrate agents into existing systems for automation and decision-making.
• Address ethical considerations and challenges in deploying autonomous agents.

Devstral is an open-source framework designed for building and running coding agents that can interact with codebases, developer tools, and APIs to enhance engineering productivity.

This instructor-led, live training (online or onsite) is aimed at intermediate to advanced-level ML engineers, developer-tooling teams, and SREs who wish to design, implement, and optimise coding agents using Devstral.

By the end of this training, participants will be able to:

• Set up and configure Devstral for coding agent development.
• Design agentic workflows for codebase exploration and modification.
• Integrate coding agents with developer tools and APIs.
• Implement best practices for secure and efficient agent deployment.

Course Format

• Interactive lectures and discussions.
• Abundant exercises and practice opportunities.
• Hands-on implementation within a live-lab environment.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.

This instructor-led, live training in Auckland (available online or on-site) is designed for beginner-level professionals who wish to understand how AI agents function and build their own interactive chatbot systems.

By the end of this training, participants will be able to:

• Understand the fundamentals of AI agents and their practical applications.
• Explore the core principles of natural language processing (NLP).
• Design a conversational flow for a chatbot.
• Develop a functional chatbot using Python and associated tools.
• Deploy the chatbot to interact with real users.

This instructor-led, live training in Auckland (online or on-site) is designed for beginner-level professionals who want to understand and build simple AI agents for real-world scenarios.

By the end of this training, participants will be able to:

• Understand the core concepts of AI agents.
• Identify different types of AI agents and their applications.
• Design and implement basic AI agents for practical tasks.
• Explore tools and frameworks for building AI agents.

This instructor-led, live training in Auckland (available online or on-site) is designed for beginner to intermediate-level developers and cloud practitioners who wish to leverage Alibaba Cloud to build AI agents capable of automating tasks, answering questions, and integrating with business systems.

By the end of this training, participants will be able to: understand AI agent architecture on Alibaba Cloud, build a simple agent workflow, connect an agent to enterprise knowledge and tools, and deploy and monitor an agent within a cloud environment.

This advanced practical seminar is tailored for software engineers, architects, technical leads, engineering managers, and delivery teams seeking to understand how Artificial Intelligence can accelerate the entire software delivery lifecycle—from requirements analysis to production-ready code.

This instructor-led, live training in Auckland (online or on-site) is targeted at beginner, intermediate, and advanced developers and technical professionals who wish to leverage Microsoft Azure to build, test, and deploy AI agents for business applications.

By the conclusion of this training, participants will be able to: understand AI agent architecture on Azure, create and configure a working agent, integrate agents with business knowledge sources, evaluate and prepare agents for deployment.

This instructor-led, live training in Auckland (online or onsite) is aimed at software developers and DevOps teams who wish to use OpenAI Codex CLI to automate coding tasks, review code, and run multi-step workflows from the terminal.

By the end of this training, participants will be able to install and configure Codex CLI, execute tasks via natural language prompts, manage approval modes, and integrate with Git and CI pipelines.

This instructor-led, live training held in Auckland (online or onsite) is aimed at developers who wish to use GitHub Copilot Agent Mode to autonomously build features, run tests, and manage larger coding tasks.

By the end of this training, participants will be able to activate Agent Mode, plan and iterate within the agent loop, execute terminal commands, and implement enterprise governance.

This instructor-led, live training in Auckland (online or onsite) is aimed at developers and leads who wish to use Cursor to build features faster, refactor across files, and manage team-wide AI workflows.

By the end of this training, participants will be able to navigate using Composer and agent mode, target code with context-aware chat, deploy team workspaces, and integrate Cursor with version control.

This instructor-led, live training in Auckland (online or onsite) is designed for intermediate-level solution architects, AI engineers, developers, and technical product teams who want to use Tencent ADP to build enterprise AI agents with RAG, workflow automation, and operational guardrails.

By the end of this training, participants will be able to: design ADP-based agents, create knowledge pipelines, orchestrate workflows and multi-agent patterns, and apply production-grade guardrails.

This instructor-led, live training in Auckland (online or on-site) is aimed at beginner-level / intermediate-level / advanced-level developers and technical practitioners who wish to use Google Cloud to build AI agents that can automate tasks, use tools, and work with business data.

By the end of this training, participants will be able to: explain AI agent concepts, build agents with Vertex AI, connect agents to external tools and data, and deploy agents for business use cases.

This instructor-led, live training in Auckland (online or onsite) is aimed at developers and DevOps professionals who wish to use Hermes Agent to automate development tasks, manage infrastructure, and build persistent AI workflows.

By the end of this training, participants will be able to install and configure Hermes Agent, interact with it across multiple platforms, use 40+ built-in tools, and deploy on various backends.

This instructor-led, live training in Auckland (available online or on-site) is designed for business users, operations teams, and technical professionals who want to use Hermes Agent to automate work, create reusable AI-driven processes, and boost team productivity.

By the end of this training, participants will be able to: explain the fundamentals of Hermes Agent, set up and use core features, build practical workflows, and apply sound operational practices.

This instructor-led, live training in Auckland (online or onsite) is aimed at developers who wish to use Hermes Agent to design and run secure local AI workflows for code assistance.

By the end of this training, participants will be able to: explain Hermes Agent concepts, set up secure local agent environments, build practical coding workflows, and apply safety and governance controls.

This instructor-led, live training in Auckland (online or onsite) is aimed at developers and technical teams who wish to use Ollama and open models to build and run private agentic AI solutions on internal infrastructure.

By the end of this training, participants will be able to: install and configure Ollama, evaluate and run open models locally, create simple agentic and retrieval-based workflows, and apply security and governance controls for regulated environments.

This instructor-led, live training in Auckland (online or on-site) is aimed at backend developers who wish to build MCP-compatible tool servers and integrate them with agent clients.

By the end of this training, participants will be able to implement MCP servers, connect them to Claude Code and OpenClaude, switch transports, and maintain an internal tool registry.

This instructor-led, live training in Auckland (online or on-site) is aimed at beginner-level, intermediate-level, or advanced-level AI professionals who wish to use MCP to connect AI assistants with external tools, data, and enterprise services.

By the end of this training, participants will be able to: explain MCP concepts, identify key architecture components, set up a basic integration, and apply security best practices.

This instructor-led, live training in Auckland (online or on-site) is designed for beginner to intermediate-level developers and technical teams who wish to leverage OpenAI APIs to build AI agents capable of reasoning, utilising tools, and completing multi-step tasks.

By the conclusion of this training, participants will be able to: design agent workflows, connect tools and external data sources, manage context and responses, and test agents for business applications.

This instructor-led, live training in Auckland (online or on-site) is designed for intermediate-level to advanced-level developers and technical professionals who wish to leverage OpenClaw to build and run practical AI agents that automate work through chat and tool integrations.

By the end of this training, participants will be able to: install and configure OpenClaw, connect to an LLM provider, use and adapt skills for automation, and apply basic security and operational guardrails.

This instructor-led, live training in Auckland (online or onsite) is aimed at senior developers who wish to use Pi to build lightweight, customisable terminal agent workflows.

By the end of this training, participants will be able to install Pi, extend it with TypeScript skills, adapt workflows to team standards, and share extensions via npm.

This instructor-led, live training in Auckland (online or on-site) is aimed at developers who wish to use Pi Coding Agent to generate code, review changes, and streamline terminal-based development workflows.

By the end of this training, participants will be able to: explain Pi Coding Agent concepts, set up and use the tool effectively, apply it to practical coding tasks, and adopt safe team workflows.

This instructor-led, live training in Auckland (online or onsite) is aimed at developers who wish to use Windsurf to build features conversationally, execute terminal workflows inside the IDE, and refactor across the codebase.

By the end of this training, participants will be able to use Cascade for navigation, execute terminal commands inside the editor, leverage predictive edits, and customise Windsurf for proprietary stacks.