Tanacast 02. Building AGENT in Tana from scratch [FULL TUTORIAL]

This episode explores building AI agents within the Tana workspace, focusing on a Portuguese language learning tutor as a practical example. Against this backdrop, the hosts demonstrate a scalable framework for agent creation, starting with a simple prompt and progressively adding features like specific knowledge integration, dynamic memory, and voice interaction. More significantly, they leverage multiple AI tools, such as NotebookLM for knowledge synthesis and Lindy for external agent integration, illustrating a multi-tool approach to AI development. For instance, the hosts demonstrate how to incorporate best practices from various sources into the agent's system prompt and dynamically update it based on the user's performance. The integration of voice input allows for contextual learning, capturing real-world language needs. Ultimately, this showcases how a collaborative, iterative approach can rapidly build powerful, personalized AI agents within a knowledge management system like Tana, highlighting emerging patterns in AI-powered learning tools.

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Andrew Altshuler

Introduction: Building an AI Agent for Language Learning

Creating the Basic Portuguese Tutor Agent

Initial Agent Interaction and Contextual Understanding

Refining the Agent with GPT-4 Pro

Crafting and Implementing an Enhanced System Prompt

Testing and Evaluating the Enhanced Agent

Integrating External Knowledge Sources

Leveraging NotebookLM for Knowledge Synthesis

Curating and Implementing Best Practices

Building a SuperTag System for Best Practices

Version 3: Adding Vocabulary Extraction

Implementing and Testing Vocabulary Extraction

Improving Vocabulary Extraction and Handling Duplicates

Creating Vocabulary Groups and Refining the Workflow

Building a "Practice Vocab" Command and Handling Search Nodes

Refining the Vocabulary Practice Command and Model Selection

Addressing Remaining Challenges in Vocabulary Management

Version 4: Adding Dynamic Memory and Self-Improvement

Building the "Evaluate" Command for Personalized Learning

Refining the "Evaluate" Command and Mistake Management

Testing and Refining the "Evaluate" Command

Integrating Mistake Analysis into the Agent's Knowledge Base

Version 5: Adding Voice Interaction

Building the Voice Interaction Functionality

Refining Voice Interaction and Handling Specific Phrases

Version 6: Connecting to External Agents (Lindy)

Full System Demo: Voice Input and Vocabulary Acquisition

Full System Demo: Vocabulary Practice and Spaced Repetition

Full System Demo: Integrating Voice Notes and Spaced Repetition

Full System Demo: External Agent Integration and Data Synchronization

Full System Demo: Lindy's Contextual Vocabulary Selection

Conclusion: Building a Personalized Language Learning System

Course Promotion and Next Steps

Detailed Overview of Version 6 and Lindy Integration

Final Demo and Conclusion

Final Demo Walkthrough and Course Call to Action

Tanacast 02. Building AGENT in Tana from scratch [FULL TUTORIAL]

Andrew Altshuler

00:00Introduction: Building an AI Agent for Language Learning

Introduction: Building an AI Agent for Language Learning

02:28Creating the Basic Portuguese Tutor Agent

Creating the Basic Portuguese Tutor Agent

05:05Initial Agent Interaction and Contextual Understanding

Initial Agent Interaction and Contextual Understanding

08:24Refining the Agent with GPT-4 Pro

Refining the Agent with GPT-4 Pro

11:17Crafting and Implementing an Enhanced System Prompt

Crafting and Implementing an Enhanced System Prompt

16:15Testing and Evaluating the Enhanced Agent

Testing and Evaluating the Enhanced Agent

19:05Integrating External Knowledge Sources

Integrating External Knowledge Sources

21:22Leveraging NotebookLM for Knowledge Synthesis

Leveraging NotebookLM for Knowledge Synthesis

26:30Curating and Implementing Best Practices

Curating and Implementing Best Practices

31:16Building a SuperTag System for Best Practices

Building a SuperTag System for Best Practices

35:44Version 3: Adding Vocabulary Extraction

Version 3: Adding Vocabulary Extraction

41:16Implementing and Testing Vocabulary Extraction

Implementing and Testing Vocabulary Extraction

44:21Improving Vocabulary Extraction and Handling Duplicates

Improving Vocabulary Extraction and Handling Duplicates

49:08Creating Vocabulary Groups and Refining the Workflow

Creating Vocabulary Groups and Refining the Workflow

53:12Building a "Practice Vocab" Command and Handling Search Nodes

Building a "Practice Vocab" Command and Handling Search Nodes

58:02Refining the Vocabulary Practice Command and Model Selection

Refining the Vocabulary Practice Command and Model Selection

1:01:17Addressing Remaining Challenges in Vocabulary Management

Addressing Remaining Challenges in Vocabulary Management

1:03:08Version 4: Adding Dynamic Memory and Self-Improvement

Version 4: Adding Dynamic Memory and Self-Improvement

1:06:09Building the "Evaluate" Command for Personalized Learning

Building the "Evaluate" Command for Personalized Learning

1:11:17Refining the "Evaluate" Command and Mistake Management

Refining the "Evaluate" Command and Mistake Management

1:16:10Testing and Refining the "Evaluate" Command

Testing and Refining the "Evaluate" Command

1:20:08Integrating Mistake Analysis into the Agent's Knowledge Base

Integrating Mistake Analysis into the Agent's Knowledge Base

1:23:04Version 5: Adding Voice Interaction

Version 5: Adding Voice Interaction

1:27:25Building the Voice Interaction Functionality

Building the Voice Interaction Functionality

1:31:21Refining Voice Interaction and Handling Specific Phrases

Refining Voice Interaction and Handling Specific Phrases

1:34:11Version 6: Connecting to External Agents (Lindy)

Version 6: Connecting to External Agents (Lindy)

1:39:16Full System Demo: Voice Input and Vocabulary Acquisition

Full System Demo: Voice Input and Vocabulary Acquisition

1:44:24Full System Demo: Vocabulary Practice and Spaced Repetition

Full System Demo: Vocabulary Practice and Spaced Repetition

1:50:04Full System Demo: Integrating Voice Notes and Spaced Repetition

Full System Demo: Integrating Voice Notes and Spaced Repetition

1:55:08Full System Demo: External Agent Integration and Data Synchronization

Full System Demo: External Agent Integration and Data Synchronization

2:00:19Full System Demo: Lindy's Contextual Vocabulary Selection

Full System Demo: Lindy's Contextual Vocabulary Selection

2:03:10Conclusion: Building a Personalized Language Learning System

Conclusion: Building a Personalized Language Learning System

2:06:22Course Promotion and Next Steps

Course Promotion and Next Steps

2:07:47Detailed Overview of Version 6 and Lindy Integration

Detailed Overview of Version 6 and Lindy Integration

2:12:36Final Demo and Conclusion

Final Demo and Conclusion

2:13:26Final Demo Walkthrough and Course Call to Action

Final Demo Walkthrough and Course Call to Action