Tool or Technology
TT0184

Mastering Poe

Advanced Multi-Model AI, Bots & Intelligent Application Development

Poe
Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced expertise in using Poe as a unified environment for working across multiple frontier, open, multimodal, and community-created AI models.
  • Design specialised AI assistants using Prompt Bots, governed knowledge bases, custom instructions, source citations, and reusable interaction patterns.
  • Build sophisticated multi-model applications using Script Bots, Server Bots, tool calling, multimodal models, and programmatic orchestration.
  • Create interactive AI applications through Canvas Apps and integrate Poe models into external applications using Poe APIs and OAuth.
  • Bring organisation-owned or externally hosted AI models onto Poe using API Bots and compatible inference endpoints.
  • Establish responsible practices for model selection, privacy, application security, cost control, testing, content governance, and human oversight.

Technology covered

PoeMulti-Model AI ChatFrontier & Community ModelsPrompt BotsKnowledge BasesScript BotsScript Bot CreatorPoe PythonServer Botsfastapi_poePoe ProtocolAPI BotsBots REST APICanvas AppsApp CreatorPoe Embed APIPoe Bot Query APIOpenAI-Compatible APIAnthropic-Compatible APITool CallingPoe OAuthMulti-Bot OrchestrationAttachmentsPrivacy Shields & Creator Monetization

Who should attend

  • Generative AI Professionals
  • AI Application Developers
  • AI Engineers
  • Prompt Engineers
  • Automation & AI Workflow Professionals
  • Software Developers
  • Solution Architects
  • Product Managers
  • AI Product Teams
  • Research & Innovation Professionals
  • Knowledge Management Teams
  • Learning & Development Technology Teams
  • Content & Creative Technology Teams
  • Digital Transformation Professionals
  • Enterprise AI & Innovation Teams

Prerequisites & Participant Readiness

  • Basic understanding of Generative AI and Large Language Models
  • Familiarity with prompt-based AI applications
  • Basic understanding of text, image, audio, and video generation is useful
  • Python knowledge is recommended for Script Bot and Server Bot modules
  • Familiarity with APIs, JSON, HTTP, and authentication is beneficial
  • Basic HTML, CSS, and JavaScript knowledge is useful for advanced Canvas App activities
  • Understanding of tool/function calling is beneficial but not mandatory
  • Access to advanced models and API functionality may depend on Poe subscription and available points
  • Model availability, pricing, capabilities, and context limits may evolve over time
  • Completion of shorter Poe programmes is not required

TOC Modules

Concepts
  • Understanding Poe as a unified AI model and application platform
  • Understanding frontier models, open models, creator Bots, and multimodal AI
  • Understanding model providers versus Poe-created and community-created Bots
  • Understanding context windows, reasoning capabilities, modalities, latency, and usage economics
  • Understanding when different models are appropriate for different business problems
Practical activities
  • Exploring representative text, reasoning, image, video, and audio models
  • Testing the same requirement across different models
  • Comparing responses based on quality, speed, modality, and task suitability
  • Building Requirement → Model Selection → Prompt → Output → Evaluation

Scenarios

Multi-Model Research & Decision Intelligence Assistant

Business Question → Poe Router → Multiple Frontier Models → Approved Knowledge Base → Specialist Analysis → Cross-Model Comparison → Verification Model → Cited Synthesis → Human Review

Participants create an AI research assistant that intentionally combines multiple models instead of depending on one LLM, using source-grounded knowledge and cross-model verification to generate stronger decision-support outputs.

AI-Powered Multimodal Application Factory

User Requirement → Script Bot / Canvas App → Text Model → Image / Audio / Video Model → Python Logic / Tools → External API → Quality Validation → Interactive Output

Participants build an end-to-end Poe application that orchestrates several AI modalities, custom logic, tools, and interactive interfaces while controlling security, costs, model selection, and final human validation.

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