This week, Genesys published an article titled “The Rise of Agentic Ecosystems: Building the Intelligent Enterprise.” It describes a new paradigm:
“Organizations that embrace this model will operate with living architectures — where decisions flow dynamically and customer needs are resolved as they appear.”
The article outlines:
- Adaptive networks of AI agents
- Self-orchestrating systems
- Perception, planning, and action loops
- Memory scaffolds that preserve learning across interactions
- Bounded autonomy with governance frameworks
- The shift from static workflows to dynamic systems
Reading it felt like opening a time capsule — because I wrote this architecture in 1998.
The Metaprise: 1998
In the late 1990s, I conducted research funded by the Government of Canada’s Scientific Research and Experimental Development (SR&ED) Program — the federal program that supports systematic investigation advancing scientific knowledge. This wasn’t a grant for thought leadership or white papers. SR&ED funds experimental development with scientific rigor.
The result was the Metaprise framework and agent-based organizational modeling, successfully deployed in a production environment for Canada’s Department of National Defence.
The technical definition:
“A synchronized [versus sequential] architecture (private hub) that simultaneously links or incorporates the unique operating attributes of all transactional stakeholders on a real-world, real-time basis.”
The core components:
- Agent-based models: Autonomous actors operating within defined protocols
- Self-learning algorithms: Feedback loops that improved with each cycle
- Dynamic orchestration: Decisions flowing based on context, not preset rules
- Relational Acquisition Model (RAM): The framework governing how agents interact
- Strand Commonality Theory: Recognizing that seemingly disparate data strands are connected and collectively impact outcomes
This wasn’t theory. It was government-funded research successfully implemented in a production environment.
The DND Proof Case
The Department of National Defence was delivering 51% next-day performance against a 90% SLA. Their request was predictable: “Automate the system.”
But the system wasn’t the problem. The agent behaviors were.
We diagnosed that service technicians were sandbagging orders until 4:00 PM to maximize daily call counts. This created a cascade: late orders meant higher prices on Dynamic Flux commodities, guaranteed customs delays, and missed delivery commitments.
The solution wasn’t better technology. It was replacing manual flow with autonomous coordination across logistics, customs, and supplier selection — an agent-based system where each component operated within defined protocols but responded dynamically to real-time conditions.
The result: 97.3% next-day delivery within three months. Headcount dropped from 23 to 3 FTEs. The system learned continuously.
That was 1998. We called it the Metaprise. Genesys calls it “agentic ecosystems.” The architecture is identical.
The Side-by-Side Comparison
The language has changed. The architecture hasn’t.
The Governance Convergence
Perhaps most telling is Genesys’s statement on governance:
“Governance isn’t a limit; it’s the framework that lets autonomy scale responsibly.”
This is Phase Zero — the readiness assessment that determines whether autonomous systems amplify value or amplify dysfunction.
The same foundational requirement I diagnosed in 1998 is now being rediscovered as essential to scaling agentic AI in 2025. Genesys calls it “bounded autonomy.” I call it readiness-first implementation. The physics are identical:
You cannot scale autonomy without governance architecture.
The DND transformation succeeded not because we implemented clever technology, but because we diagnosed agent behaviors first — technicians sandbagging orders, suppliers positioned incorrectly, customs processes misaligned with order timing. Only after understanding the ecosystem did we build the autonomous coordination layer.
Technology amplifies whatever foundation exists. It doesn’t create one.
That was true in 1998. It remains true in 2025.
The Dismissal
When I introduced these concepts publicly, many leading industry analysts dismissed “agent-based, Metaprise visibility” as rhetoric. The terminology was unfamiliar. The technology to demonstrate it at scale didn’t exist. And the industry was committed to equation-based, tool-first thinking.
They know who they are.
They offered opinions. I had government-funded research and a production deployment with documented results.
The criticism wasn’t engagement with the ideas — it was dismissal of the language. “Rhetoric.” “Obfuscation.” “Academic.”
So I kept working. Kept documenting. Kept refining the frameworks. And waited for the world to catch up.
The Validation: 2025
Now the world is catching up.
Genesys publishes “agentic ecosystems” as thought leadership. The same architecture dismissed as rhetoric 15 years ago is now the foundation of enterprise AI strategy.
What Genesys describes as “Model Context Protocol (MCP)” and “Agent2Agent Protocol (A2A)” are simply the technical protocols needed to execute the agent-based model I built for logistics, courier integration, and customs automation in the late 1990s.
The protocols are new. The architecture is not.
Why This Matters
This isn’t about credit. It’s about pattern recognition.
The procurement industry is facing the same architectural question Genesys is addressing for customer experience: Do we keep layering technology on static workflows, or do we redesign the ecosystem itself?
The answer is the same now as it was in 1998:
Technology amplifies whatever foundation exists. It doesn’t create one.
Agentic ecosystems — whether in customer experience or procurement — require:
- Readiness before automation
- Governance before autonomy
- Architecture before tools
- Foundation before technology
This is the Metaprise. This is Phase Zero. This is the Hansen Method.
The core physics are unchanged. Only the processing speed and terminology have advanced.
The Convergence Continues
In the past week alone, fifteen independent voices have validated this thesis from different angles — Tom Redman, Phil Fersht, ISM, Future Purchasing, Gartner, and now Genesys.
The industry is converging on a truth that’s been documented for 27 years:
Living systems require living foundations. Static workflows cannot support dynamic ecosystems. Governance enables autonomy — it doesn’t constrain it. And readiness determines outcomes.
The analysts who dismissed this as rhetoric two decades ago are now using different words to describe the same architecture.
The words changed.
The physics didn’t.
Twenty-seven years later, the industry is arriving at the same destination.
Jon W. Hansen is the creator of the Hansen Method and the Hansen Fit Score, focused on preventing the 80% implementation failure rate in procurement transformation. His frameworks — including the Metaprise model, Phase Zero readiness assessment, and agent-based organizational modeling — were developed through Government of Canada SR&ED-funded research and validated across government and enterprise implementations since 1998.
Procurement Insights
From Metaprise to Agentic Ecosystems: The 27-Year Journey to Architectural Truth
Posted on December 5, 2025
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This week, Genesys published an article titled “The Rise of Agentic Ecosystems: Building the Intelligent Enterprise.” It describes a new paradigm:
The article outlines:
Reading it felt like opening a time capsule — because I wrote this architecture in 1998.
The Metaprise: 1998
In the late 1990s, I conducted research funded by the Government of Canada’s Scientific Research and Experimental Development (SR&ED) Program — the federal program that supports systematic investigation advancing scientific knowledge. This wasn’t a grant for thought leadership or white papers. SR&ED funds experimental development with scientific rigor.
The result was the Metaprise framework and agent-based organizational modeling, successfully deployed in a production environment for Canada’s Department of National Defence.
The technical definition:
The core components:
This wasn’t theory. It was government-funded research successfully implemented in a production environment.
The DND Proof Case
The Department of National Defence was delivering 51% next-day performance against a 90% SLA. Their request was predictable: “Automate the system.”
But the system wasn’t the problem. The agent behaviors were.
We diagnosed that service technicians were sandbagging orders until 4:00 PM to maximize daily call counts. This created a cascade: late orders meant higher prices on Dynamic Flux commodities, guaranteed customs delays, and missed delivery commitments.
The solution wasn’t better technology. It was replacing manual flow with autonomous coordination across logistics, customs, and supplier selection — an agent-based system where each component operated within defined protocols but responded dynamically to real-time conditions.
The result: 97.3% next-day delivery within three months. Headcount dropped from 23 to 3 FTEs. The system learned continuously.
That was 1998. We called it the Metaprise. Genesys calls it “agentic ecosystems.” The architecture is identical.
The Side-by-Side Comparison
The language has changed. The architecture hasn’t.
The Governance Convergence
Perhaps most telling is Genesys’s statement on governance:
This is Phase Zero — the readiness assessment that determines whether autonomous systems amplify value or amplify dysfunction.
The same foundational requirement I diagnosed in 1998 is now being rediscovered as essential to scaling agentic AI in 2025. Genesys calls it “bounded autonomy.” I call it readiness-first implementation. The physics are identical:
You cannot scale autonomy without governance architecture.
The DND transformation succeeded not because we implemented clever technology, but because we diagnosed agent behaviors first — technicians sandbagging orders, suppliers positioned incorrectly, customs processes misaligned with order timing. Only after understanding the ecosystem did we build the autonomous coordination layer.
Technology amplifies whatever foundation exists. It doesn’t create one.
That was true in 1998. It remains true in 2025.
The Dismissal
When I introduced these concepts publicly, many leading industry analysts dismissed “agent-based, Metaprise visibility” as rhetoric. The terminology was unfamiliar. The technology to demonstrate it at scale didn’t exist. And the industry was committed to equation-based, tool-first thinking.
They know who they are.
They offered opinions. I had government-funded research and a production deployment with documented results.
The criticism wasn’t engagement with the ideas — it was dismissal of the language. “Rhetoric.” “Obfuscation.” “Academic.”
So I kept working. Kept documenting. Kept refining the frameworks. And waited for the world to catch up.
The Validation: 2025
Now the world is catching up.
Genesys publishes “agentic ecosystems” as thought leadership. The same architecture dismissed as rhetoric 15 years ago is now the foundation of enterprise AI strategy.
What Genesys describes as “Model Context Protocol (MCP)” and “Agent2Agent Protocol (A2A)” are simply the technical protocols needed to execute the agent-based model I built for logistics, courier integration, and customs automation in the late 1990s.
The protocols are new. The architecture is not.
Why This Matters
This isn’t about credit. It’s about pattern recognition.
The procurement industry is facing the same architectural question Genesys is addressing for customer experience: Do we keep layering technology on static workflows, or do we redesign the ecosystem itself?
The answer is the same now as it was in 1998:
Technology amplifies whatever foundation exists. It doesn’t create one.
Agentic ecosystems — whether in customer experience or procurement — require:
This is the Metaprise. This is Phase Zero. This is the Hansen Method.
The core physics are unchanged. Only the processing speed and terminology have advanced.
The Convergence Continues
In the past week alone, fifteen independent voices have validated this thesis from different angles — Tom Redman, Phil Fersht, ISM, Future Purchasing, Gartner, and now Genesys.
The industry is converging on a truth that’s been documented for 27 years:
Living systems require living foundations. Static workflows cannot support dynamic ecosystems. Governance enables autonomy — it doesn’t constrain it. And readiness determines outcomes.
The analysts who dismissed this as rhetoric two decades ago are now using different words to describe the same architecture.
The words changed.
The physics didn’t.
Twenty-seven years later, the industry is arriving at the same destination.
Jon W. Hansen is the creator of the Hansen Method and the Hansen Fit Score, focused on preventing the 80% implementation failure rate in procurement transformation. His frameworks — including the Metaprise model, Phase Zero readiness assessment, and agent-based organizational modeling — were developed through Government of Canada SR&ED-funded research and validated across government and enterprise implementations since 1998.
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