Agents on Canvas: Orchestrating in tldraw
I remember the first time I played with tldraw — I connected my React components and watched as the canvas came alive. It's not just about drawing; it's about orchestrating AI agents right there in real-time. Let's dive into how I got this setup working and what you can expect. In this journey, we'll explore AI integration, agent orchestration, and practical applications. I'll share insights from the Make Real project, AI model training challenges, and the security measures I implemented. It's all about making complex AI concepts actionable and efficient.
I remember the first time I played with tldraw — I connected my React components and watched as the canvas came alive. What I found is that tldraw isn't just a drawing tool. It's a playground for orchestrating AI agents in real-time. So, how did I get this setup working? Let me take you on my journey with tldraw, where AI integration and agent orchestration come to life. We'll explore the Make Real project and its impact in 2023, tackle AI model training challenges for structured data, and discuss the security considerations I implemented. Along the way, I'll share my mistakes (because yes, I got burned more than once) and how I overcame them. We'll also dive into Teal Draw's desktop app and its functionalities. So, if you're ready to move from theory to practice, join me on this adventure.
Exploring Teal Draw's Capabilities and Applications
To kick off with Teal Draw, I set up my environment using React. This made component integration on the canvas truly seamless. It's one of those things where, once you start, you wonder how you managed before. The Make Real project in 2023 was a real game changer. It allowed non-technical users to create technical prototypes without writing a single line of code.
In 2025, I'm looking forward to the cursor tool arrival, which promises to significantly enhance user interaction. But watch out, the learning curve for integrating AI features is steep. It's a challenge, but trust me, it's worth it.
- Easy integration with React for component fluidity.
- Make Real 2023: Enabling code-free prototyping.
- 2025 cursor tool: A major upcoming improvement.
- Significant learning curve for AI features.
AI Integration: From Model Training to Prompt Engineering
AI model training for structured data gave me a hard time. I had to iterate several times on prompt engineering to get satisfactory results. First, I defined clear data structures, then I trained the models, but don't underestimate the time this takes.
Prompt engineering is crucial. It's not just about the data, but how you ask for it. I faced challenges with overfitting, which I overcame by diversifying data inputs.
- Define clear data structures before training.
- Prompt engineering: Crucial for consistent results.
- Overcome overfitting by diversifying data inputs.
Agent Orchestration and Interaction on the Canvas
Orchestrating agents is like conducting an orchestra — coordination and timing are key. I used specific workflows to manage agent interactions, focusing on efficiency and responsiveness.
The biggest hurdle was ensuring agents didn't overlap in tasks, which required careful planning. It's essential to sandbox these processes to prevent unexpected behavior.
- Use workflows for efficient agent interactions.
- Avoid task overlap through careful planning.
- Sandboxing essential to prevent unexpected behaviors.
Developing the Teal Draw Desktop App with Electron
For developing the Teal Draw desktop app, I chose Electron for its flexibility in building cross-platform applications. Security was a priority — sandboxing was crucial to protect user data.
The desktop app enhances performance, but watch out for resource consumption. Future updates will focus on optimizing the app's speed and reliability.
- Chose Electron for flexibility and cross-platform capabilities.
- Sandboxing to secure user data.
- Performance enhancements with future updates.
Security and Future Directions with Teal Draw
Security concerns are real — I implemented sandboxing to mitigate risks. User engagement is evolving, and I plan to incorporate more interactive features by 2026.
The future of Teal Draw is promising, but balancing innovation with security remains a challenge. Stay tuned for updates on new tools and features aimed at enhancing user experience.
- Implemented sandboxing to reduce security risks.
- Add interactive features to boost user engagement.
- Balance innovation and security for a promising future.
Working with tldraw has been quite the journey. I've integrated AI, ensured security, and at each step, learned more about optimizing efficiency and orchestration. Here are the key takeaways:
- tldraw's Capabilities: Integrating AI and collaborative features on the canvas really changes the game.
- Make Real Project (2023): This showed me direct team efficiency improvements.
- AI Model Training: Watch out for challenges with structured data—I've stumbled a few times but found solutions.
As we move forward, I'll focus on refining these processes to make them even more robust and user-friendly. If you're diving into tldraw, start experimenting with these workflows, and don't forget to share your experiences. We're all learning together. I highly recommend watching Steve Ruiz's video 'Agents on the Canvas in tldraw' for a deeper dive. It's a real peer-to-peer exchange. YouTube link
Frequently Asked Questions
Thibault Le Balier
Co-fondateur & CTO
Coming from the tech startup ecosystem, Thibault has developed expertise in AI solution architecture that he now puts at the service of large companies (Atos, BNP Paribas, beta.gouv). He works on two axes: mastering AI deployments (local LLMs, MCP security) and optimizing inference costs (offloading, compression, token management).
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