From Ideas to Reality: A First Look at Autonomous Innovation
See how modular design and deep agent collaboration are transforming innovation
Hey everyone,
I’m excited to share a sneak peek of a project I’ve been deeply involved in – a multi-agent system designed to unlock autonomous innovation. I’ll be demonstrating this system at Davos later this month, and I’m thrilled to give you, my cherished subscribers, an early look!
Before we dive in, I want to extend a huge thank you to everyone who responded to my call on LinkedIn for feedback on this demo. Your insights were invaluable in refining the presentation.
Live Demo from Earlier Today:
What is Agento and GenSpring?
This system, which I’m calling Agento, is all about harnessing the power of AI agents to not just chat, but to actually bring those ideas to life. It’s built on three core innovations:
Modular Architecture: This allows for rapid experimentation and seamless integration of new technologies. Think of it like building with LEGOs – you can easily swap out parts and add new ones without rebuilding the entire structure.
Deep Agent Collaboration: The agents in this system are designed to work together in a way that mirrors successful human collaboration. They can reason deeply about complex problems, provide constructive criticism, and iterate towards a high-quality solution.
GenSpring - The Idea Engine: This is where things get really exciting. The most innovative modules is called GenSpring, which is designed to continuously generate new ideas, evaluates them, and feed the most promising ones into the development pipeline through all the other modules. It’s like having a perpetual brainstorming machine!
Why This Matters
I believe this technology has the potential to revolutionize how we innovate across a wide range of fields. Imagine a future where:
AI agents can autonomously generate and develop solutions to complex problems, like disaster response or affordable housing.
New products and services can be brought to market faster than ever before, thanks to the accelerated innovation cycles enabled by this system.
Organizations can become more agile and adaptable, thanks to the modular architecture and the ability to integrate new technologies seamlessly.
Demo in Action
To complement the conceptual design above, here are key moments from the actual system demonstration. In this practice run, you’ll see:
A slide deck and key talking points outlining this approach to using AI agents.
A demo of the system taking a user-defined goal and breaking it down into an actionable plan.
Multiple agents, powered by models like GPT–4o, Claude 3.5 and Gemini 1.5, working together to refine the plan through a process of revision requests and evaluations.
The importance of clear communication and well-defined evaluation criteria for successful agent collaboration.
The final output in both JSON and Markdown formats, demonstrating the system’s ability to produce structured, machine-readable, and human-readable results.
The role of GenSpring is as a kind of initialization module that can be swapped in instead of the user-defined goal input, so as to enable a fully autonomous general purpose innovation pipeline prototype.
Presentation Deck & Key Moments
These slides and talking points form the foundation of how I am currently communicating the system’s capabilities, novel design, and broader potential:
“What innovative challenges can we solve together?”
"What if AI agents could continuously generate breakthrough ideas AND autonomously develop them into real solutions? I've created a system that does exactly that through three key innovations: First, a modular architecture that enables rapid experimentation and seamless integration of new technologies without disrupting the whole system. Second, a sophisticated approach to AI agent collaboration that enables deep reasoning and effective handling of complex challenges. And third - perhaps most exciting - GenSpring, an 'idea engine' that constantly generates and evaluates new opportunities, feeding promising innovations directly into development."
"This modular architecture isn't just about flexibility - it's about enabling a new paradigm for AI innovation. Each module accepts structured inputs and produces structured outputs, creating clear interfaces where teams can plug in their preferred approaches. This means you can rapidly experiment with different technologies, frameworks, or entirely new approaches without rebuilding the whole system.
But here's where it gets interesting: this modularity ALSO opens the door to something bigger. Any team that believes they have superior agent technology can prove it by taking standard inputs from one module and showing they can produce better outputs. It's an open invitation to demonstrate real capabilities rather than just talk assert the superiority of a given implementation or approach."
"What makes this system unique is how it orchestrates AI conversations in a way that mirrors successful human-AI collaboration patterns. The agents can guide each other back to relevant topics, seek revision of outputs that don't meet quality benchmarks, and engage in deeper reasoning about complex challenges. By finding that crucial balance between steering and enabling, these agent conversations can adapt to tackle virtually any problem. Think of it as creating the conditions for AI creativity to flourish while ensuring the results remain practical and focused.
The power isn't in controlling every interaction, but in establishing the right design patterns for productive collaboration. Think of it as creating the conditions for AI creativity to flourish while ensuring the results remain practical and focused.”
"GenSpring is where this system truly breaks new ground. Imagine having access to a perpetual wellspring of innovative ideas - not just random concepts, but carefully validated opportunities that are novel, useful, and crucially, achievable. This isn't just an idea generator - it's a complete pipeline that continuously identifies promising innovations and filters them through sophisticated analysis to ensure real-world value creation.
What makes GenSpring transformative is its seamless integration with our modular architecture. Each idea is structured precisely to flow into subsequent modules - from detailed planning to implementation, testing, and eventual deployment. As the system runs, successful innovations feed back into the process, creating an ever-evolving fountain of refined, practical solutions."
"The implications of this modular, agent-driven approach extend far beyond any single organization or industry. By establishing clear interfaces for AI systems to exchange value - whether that's ideas, services, or solutions - we're laying the groundwork for an entirely new kind of innovation economy.
Imagine a future where AI-driven companies can seamlessly exchange specialized capabilities, where breakthrough ideas can flow freely between organizations, and where innovation isn't limited by organizational boundaries. This isn't just about accelerating R&D or reducing costs - it's about creating the fundamental infrastructure for a new era of open, collaborative innovation. Just as standardized shipping containers revolutionized global trade, standardized AI interfaces could transform how we create and exchange value in the digital age."
“What innovative challenges can we solve together?”
I’d Love Your Feedback!
This is just a first glimpse, and I’m eager to hear your thoughts. What aspects of the system are most exciting to you? What questions do you have? What potential applications do you see? Let me know in the comments.
Want a One-on-One Demo and Chat?
If you’re a paid subscriber and would like a personalized demo and a chance to discuss this technology further, I’d love to connect! I’d be happy to answer any questions and talk through how these approaches to AI agents could be useful in your contexts. Please reach out to me using this form, https://forms.gle/8LnVNGEs6u9n5UGT6, and be sure to use the same email and name you use for your Substack subscription so I know it’s you.
Looking Ahead
I believe that multi-agent systems like Agento and components like GenSpring have the potential to transform the way we approach innovation. By combining the creative power of AI agents with the structure and rigor of modular design, we can unlock new levels of productivity, problem-solving, and even new value creation. I’m excited to continue developing this technology and exploring its possibilities with you.
Thanks for being a part of this journey!
Best,
Dazza Greenwood
P.S. For a deeper dive into the legal aspects of LLM-powered agents, check out my Stanford CodeX project site: https://law.stanford.edu/codex-the-stanford-center-for-legal-informatics/projects/agentic-genai-transaction-systems/ and the first of three blog posts as part of that research on issues and opportunities for transactional AI Agents is now live at: https://law.stanford.edu/2025/01/14/from-fine-print-to-machine-code-how-ai-agents-are-rewriting-the-rules-of-engagement.
And for insights on empowering consumers with personal AI agents, see these posts I wrote with Consumer Reports Innovation Lab: https://innovation.consumerreports.org/empowering-consumers-with-personal-ai-agents-legal-foundations-and-design-considerations/ and https://innovation.consumerreports.org/engineering-loyalty-by-design-in-agentic-systems/.
Also, earlier today, some MIT colleagues and I published a pre-print of a new research paper on a potential way to use and extend OAuth 2 and OpenID Connect technical specifications to enable “Authenticated Delegation and Authorized AI Agents”. You can learn about that here: https://arxiv.org/abs/2501.09674