People, Ideas & Objects: The Economics of Synallagi
People, Ideas & Objects is the name I chose immediately after reading Ronald Bailey’s December 2001 Reason interview, “Post-Scarcity Prophet,” with Paul Romer, then a professor at Stanford University. His explanation of the relationship between people, ideas and physical things provided the foundation for the name and the economic thinking behind our work. reason.com
Romer expressed the central distinction plainly: “Ideas can be used by many people at the same time.”
A barrel of oil can be consumed only once. An idea about how to develop a reservoir, organize a transaction or design software can be applied repeatedly. Its use by one person need not diminish its availability to anyone else. Developing that idea may require substantial investment. Applying it elsewhere need not repeat the original development expenditure. paulromer.net
Adam Smith’s specialization and division of labor, articulated in The Wealth of Nations in 1776, and remain foundational to our understanding of productivity. Organizing people so they can develop expertise and coordinate their contributions creates capabilities beyond those available to individuals working independently. The scope for extending these principles across the oil & gas industry remains considerable and unending.
Romer’s October 1990 paper, “Endogenous Technological Change,” explained how deliberate investment in new ideas can sustain economic growth. Knowledge is a productive input with different properties from the physical resources used to apply it. His framework connected incentives to create ideas with the economic benefits of their repeated use. In 2018, he received the Nobel Memorial Prize in Economic Sciences for integrating technological innovation into the analysis of long-term growth. doi.org
For People, Ideas & Objects, the opportunity lies in bringing these principles together. Specialization develops deeper capabilities. Reusable ideas extend the reach of those capabilities. Appropriate organization makes both commercially productive.
Cloud Computing provides a practical illustration. A producer can obtain computing services from a specialist whose infrastructure serves many customers. Capacity can be allocated as required, while the development of common software and operating methods supports a much broader market. Resource pooling and access on demand are defining features of the model. CSRC
The distinction between the resources matters. Servers, electricity, processing capacity and people’s time remain scarce and carry costs. The non-rival elements include the software, designs and codified methods that can be reused across customers. Cloud Computing combines this reuse with specialization and more effective utilization of physical infrastructure. paulromer.net
For a producer, this creates a demanding commercial test for internal IT expenditure. What advantage justifies independently building and maintaining capabilities available from specialist providers? Ownership brings responsibility for staffing, security, upgrades, resilience and continuing investment. Each of those obligations belongs in the comparison.
People, Ideas & Objects extends this economic logic into the administration and accounting of the oil & gas industry. Through Synallagi, our user community and its independent service provider organizations, we propose to share the development and maintenance costs of common capabilities across participating producers.
An accounting process, transaction design or software improvement should be developed so that its benefits can extend throughout the participating industry. Specialists can deepen their expertise in particular functions and apply it across many properties. An innovation developed through one engagement can become a reusable capability wherever it is applicable.
This is what we mean by the Sharing of Non-Rival Costs Organizational Construct. The reusable capability is shared; the work required to apply it remains measurable. Actual time, resources and services are charged to the Joint Operating Committee receiving them. That provides a basis for identifying the economics of each property and holding those delivering services accountable for their contribution.
The resulting savings can strengthen margins, fund innovation, rebuild service capacity and support investor returns. Their value becomes greater when the same organizational changes also improve the quality and timeliness of decisions.
Artificial Intelligence works a double shift in this model.
First, it allows the costs of developing sophisticated models and supporting services to be recovered across a large population of users. Each producer gains access to capabilities that would be prohibitively expensive to recreate independently. Training a model and using it are different activities with different costs; each customer need not repeat the original research and training effort.
Second, AI can increase what people accomplish with their expertise. Engineers can investigate more alternatives. Geologists can examine more interpretations. Accountants can direct more attention to exceptions and commercial consequences. Service providers can turn recurring problems into improved processes and software. The opportunity is to shorten the interval between identifying a problem, developing a response, testing it and applying what has been learned.
Synallagi is designed to connect these activities to the transactions and economics of the property. Autonomous Asynchronous Transaction Orchestration provides a means to coordinate work among people, service providers and AI agents, with defined authority, recorded decisions and accountability. The commercial objective is better decisions and more profitable operations.
This is the context in which I assess concern about AI capital expenditure. The scale of a vendor’s spending, considered alone, tells us little about its economic justification. The relevant comparison includes the number of users it can serve, the capabilities it makes available and the value those users can create.
Viewed against that potential, investments that initially appear excessive may represent disciplined commitments to a much larger productive opportunity. My view is that the economic value made possible by this infrastructure could substantially exceed what conventional comparisons suggest.
Each vendor must still earn a return. Utilization, pricing, operating costs, financing and the pace of technological change will determine the outcome of particular investments. New Growth Theory explains the opportunity; commercial performance establishes whether a business has captured it.
The same discipline should govern proposals to bring AI infrastructure back inside the producer firm. An open source licence does not eliminate the costs of hardware, integration, security, maintenance or accountable operation. Specific requirements for confidentiality, latency or customization may support an internal deployment. Those requirements should be demonstrated through a complete business case.
The relevant question is what arrangement delivers the required capability at the best total economic result. Preserving an internal department’s mandate provides no evidence of that result. Every proposal to rebuild capabilities already available through specialist providers should face rigorous scrutiny.
The incentives to develop those capabilities matter as well. Romer’s framework recognizes that an idea can be non-rival while access to it remains controlled. Sharing the use of an innovation is compatible with compensating those who create and maintain it. Synallagi’s Intellectual Property Organizational Construct belongs alongside specialization, innovation and the sharing of non-rival costs for this reason. paulromer.net
These principles bring us back to the organization of the producer. AI’s commercial value depends on how people are authorized to use it, how their work is coordinated and how results are measured. A producer that introduces advanced tools while retaining ineffective decision processes can preserve the very constraints those tools were intended to address.
Everything undertaken in Synallagi is focused on providing the most profitable means of oil & gas operations. At the property level, that requires knowing the full economics and acting on them. Unprofitable production is shut in, and the property enters an inventory of innovative projects whose purpose is to restore profitable production. AI, specialized service providers and shared capabilities expand the means available to accomplish that objective.
I believe the combination of specialization, reusable knowledge and Artificial Intelligence can materially raise the economy’s growth trajectory. Realizing that possibility requires organizations capable of converting better ideas into better commercial outcomes.
Consider what this means for the people working in U.S. oil & gas: deeper specialization, access to more capable tools, less duplicated effort and greater scope to apply their judgment to productive problems. Consider what it means for an industry whose future depends on profitability and the capacity to reinvest.
People, Ideas & Objects was named for this opportunity almost twenty years ago. Synallagi is being developed to make it practical. The industry’s established methods should now be required to demonstrate how they can deliver a better result.

