The latest AI Hackerspace Live session on July 25th showcased some innovative work happening in AI swarm orchestration and dashboard design. Community members gathered to demonstrate cutting-edge developments that are transforming how we visualise, manage, and scale artificial intelligence agents.

🎥 Watch from the beginning

Dashboard Design: From Wargames to Modern UX

rUv's Retro-Inspired Command Center

rUv demonstrated his Wargames-inspired dashboard that provides real-time visibility into Claude-flow and Cloud Code operations. The system offers:

• Concurrent swarm management - Run multiple AI swarms simultaneously

• Real-time monitoring - Track agent activities as they happen

• Manual tool execution - Direct control over individual operations

• Stream JSON output integration - Live data feeds from Claude Code

🎥 See the dashboard demo

rUv used streaming JSON output from Claude Code, which allows for real-time monitoring without the traditional "flicker" that makes swarm activities hard to track. As he explained: "Now I can see exactly what's happening. I can see the full JSON response or whatever I need to see from it."

Bron's 3D Swarm Visualisation

Bron presented a sophisticated 3D visualisation system built with Three.js that tackles a fundamental question: "What exactly are these swarms doing?" His dashboard provides:

• Drag-and-drop swarm management - Move and organise swarms visually

• Agent hierarchy visualisation - See relationships between different agents

• Resource monitoring - Track CPU, RAM, and disk usage

• Swarm persistence - Save and reload successful configurations

🎥 Explore the 3D interface

One of Bron's key insights was recognising that traditional AI-generated diagrams showing connections between swarms are often misleading: "When you actually dig down they don't exist like none of the swarms are connected at the moment they're all independent."

The One-Prompt Evolution

Perhaps the most jaw-dropping demonstration came from Bron's showcase of what AI swarms can accomplish with minimal guidance. Using just one prompt - "Make me a website about this repo" - his swarm generated a complete, professional-grade website from his github repository featuring:

• Interactive swarm topology visualisations

• Performance metrics dashboards

• MCP tools integration

• Dynamic content organisation

• Modern UI/UX design patterns

🎥 Watch the one-prompt magic

As Bron noted with amazement: "This thing just cranked this out the whole thing... I don't think I could have made this myself it would taken me like I don't know a day or two days you know like to think about it make it and this thing's just cranked this out one you just pointed it... at the repo."

Advanced Swarm Architectures and Competition

Agent Competition and Evolution

John Petty shared his innovative approach to swarm optimisation through competitive evolution. His system:

1. Spawns five different agent solutions for each problem

2. Evaluates performance using scoring and prediction metrics

3. Iteratively evolves the best-performing agents

4. Maintains diversity by keeping agents with different approaches

🎥 Learn about competitive agents

This approach has shown "pretty good success" in solving complex problems by leveraging the competitive dynamics that drive natural selection.

The Challenge of Scale

The session addressed one of the biggest challenges in swarm orchestration: scaling beyond individual swarms to massive agent networks. As Bron pointed out:

"When you have a million ants you know what are they all doing and how do they work together to achieve their goal so uh we got a little tiny high but you know again once we hook up if we can hook up the whole agentics.org everyone brings their 20, 30 even if we each have a cloud code but we hook up 80 cloud codes."

🎥 Discuss scaling challenges

Technical Architecture and Infrastructure

Real-Time Monitoring Solutions

Both presenters emphasised the critical importance of visibility in swarm operations. Key architectural patterns emerged:

• WebSocket integration for real-time data streaming

• SQLite databases for rapid local data storage

• Hook-based event systems for custom monitoring

• API endpoints for external integrations

🎥 Deep dive into architecture

Container and Cloud Strategies

The discussion revealed practical insights about deployment:

• GitHub Codespaces for isolated development environments

• Docker containerisation for consistency across platforms

• Fly.io and Railway for scalable cloud deployment

• Port forwarding for secure remote access

Security considerations were also addressed, with recommendations for multi-layer protection including anonymous keys, CORS policies, and JWT authentication.

Vision Language Models and Robotics Integration

The session touched on emerging applications in robotics and computer vision, particularly around Vision Language Action (VLA) models. Discussion points included:

• Real-time image analysis capabilities

• Integration with robotics platforms like FIRST robotics

• Local inference options for edge computing scenarios

• Cellular connectivity for mobile robot applications

🎥 Explore VLM applications

Community Building and Collaboration

Global Meetup Network

The session highlighted the growing international community around AI agent development:

• Indianapolis meetup showing strong turnout

• Denver event scheduled for August 13th

• Toronto gathering planned for August 12th

• Austin expansion under discussion

🎥 Community updates

Open Source Collaboration

Multiple participants expressed interest in contributing to and expanding the showcased projects. The open-source nature of these tools is accelerating innovation across the community.

Looking Forward: The Implications

This session revealed several transformative trends:

1. Democratisation of Complex Development

What once required weeks of expert development can now be accomplished in minutes with well-orchestrated AI swarms.

2. Real-Time Observability

The ability to monitor and understand AI agent behavior in real-time is becoming essential for managing complex systems.

3. Collaborative AI Networks

Future systems will likely involve federated networks of AI agents working across organisational boundaries.

4. Visual Programming Paradigms

3D visualisations and drag-and-drop interfaces are making swarm orchestration more accessible to non-technical users.

Key Takeaways

• Visualisation is crucial for understanding and managing AI swarm behavior

• One-prompt generation is becoming increasingly powerful for complete application development

• Real-time monitoring solves the "flickering" problem that made swarms hard to track

• Competitive evolution among agents can improve overall system performance

• Community collaboration is accelerating innovation in agent orchestration

The July 25th AI Hackerspace Live session demonstrated that we're at an inflection point in AI development. The tools and techniques showcased aren't just incremental improvements - they represent a fundamental shift toward persistent, collaborative AI ecosystems that operate at scales previously unimaginable.

As one participant noted early in the session, we're moving beyond individual applications toward frameworks where AI systems run continuously, collaborate seamlessly, and evolve autonomously. The future of software development may well be defined by how effectively we can orchestrate these intelligent swarms.

Want to join the conversation? Connect with the AI Hackerspace community and explore these cutting-edge developments in agent collaboration.

Total Session Duration: 91 minutes Key Technologies: Claude-flow, Cloud Code, Three.js, WebSockets, Docker

🎥 Watch the complete session