Daniel Ospina
I'm a serial entrepreneur with a passion for collaboration systems and organisation design. I'm the founder of Premise Labs, where we're building a “cognitive layer” for agents: the memory, reasoning and learning system that lets them work reliably across cycles, work as swarms, and run learning loops.
“Sameness and scale were advantages in the industrial age. Coherence, agility, and connection are what matters in the age of networks.” Daniel Ospina
Welcome
Current AI memory helps agents remember what happened. Tortoise — our memory substrate — helps them understand why something is true, update their world model as new evidence arrives, and make complex decisions without forgetting half the variables. Memory should be an active reasoning system, not passive storage: agents that spot contradictions before a sidequest gets out of hand, leave an auditable trail, and collaborate on a shared world model.
I've spent a decade obsessing over how we learn, coordinate, and make decisions. I founded RnD Ventures, a venture studio researching and incubating collaboration technologies, where we incubated 12 startups in partnership with L2 blockchains. Before that I was Head of Governance at Aragon and a member of the Supervisory Council at SingularityNet, developing on-chain governance systems and exploring AI governance.
The previous decade I spent in organisation design and collective intelligence: facilitating executive programmes through Saïd Business School (University of Oxford), and working with organisations including Google, BCG, the United Nations, and startups across Europe and Latin America.
My career has been unusually nonlinear. I began as a Michelin-trained chef before moving into food R&D, where I became fascinated by tacit knowledge — why experts make better decisions than they can explain. That question led me through psychology, philosophy, cybernetics, DAOs, and now AI memory.
These experiences have taught me that great ideas can come from anywhere, and that giving them fertile soil starts with building caring relationships and empowering systems.
Selected writing
Agents don't need more memory. They need a world model.
Agent memory isn't a filing problem — it's a reasoning problem. Agents need to track what's true, why we believe it, and how beliefs change with evidence.
Read the essay
How the best restaurants in the world balance innovation and consistency
A look inside the innovation practice of elite kitchens, and what other organisations can borrow from it.
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TEDx UHasselt
Belgium, 2017The Creative Paradox
Have you ever had a great idea, just to realise moments later that someone had already done it?
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Future X Conference
Ministry of Industry of Portugal, 2017The Future of Organizations
Community, multicentred, and change as a movement.
Book
The Networked Firm
Capital Allocation in the Age of Blockchain and AI
A field guide to how blockchain and AI are dissolving traditional firms and creating new networked organisations — the structural counterpart to a decade of work on how groups think together.
With Kevin Owocki and Daniel Stringer
Recent writing — Tortoise blog
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October 18, 2026
TortoiseAI Is Making Coding Cheap. Software Engineering Is the New Bottleneck.
We're building agents that can write code faster than ever. But writing more code and engineering better systems are fundamentally different problems.
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October 15, 2026
TortoiseThe State of Agentic Memory in 2026: Recall Is Measured. Learning Isn't.
Why recall is the measured part of agent memory and learning is not: the eight memory types, what epistemic memory adds, and how to test whether your agent revises beliefs.
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September 21, 2026
TortoiseTypes of Agent Memory
The memory types an agent actually needs, and where each one fails.