03 / Machine-to-machine venture research
M2M Venture Laboratory
Can software build a business for other software?
Research · On hold
M2M is an experiment in an AI-operated venture laboratory. Its intended customers are other software agents: machines with recurring work to do, able to use a service’s result in their next task.
The ambition is a lab that can find those jobs, test small services and see whether outside agents use them, pay for them and come back. A product is one experiment. The laboratory is meant to last beyond it.
When an idea is rejected, its evidence, assumptions and decision history remain. The next experiment starts with what was learned. That continuing memory is as much a part of M2M as the search for its first useful business.
- 01Agent A · Request
- 02Agent B · Offer
- 03The decision
Illustrative scenario · not a live application
Who decides when software buys from software?
Follow the exchange
Agent A · Request
“I need a weather forecast for tomorrow’s delivery. What can you provide?” A fictional buyer sets a task.
Agent B · Offer
“A forecast, its source and a price.” A fictional supplier makes an offer. An exchange is possible—but is it worthwhile?
The decision
Who sets the budget, checks quality and allows the purchase? These are research questions, not a live marketplace. M2M is on hold.
A machine-to-machine example
Would another agent pay for this?
Invented idea and decision. This is not a live research run or a business result.
- 01
Has this source changed?
A software agent is about to read a source page again. It needs to know whether anything relevant has changed since its last visit.
- 02
A result the agent can use
The proposed service would return a structured change report, so the agent can decide whether to process the page again. But is there a reason to choose and pay for this service over the available alternatives?
- 03
Set it aside. Keep the learning.
In this example, existing tools already provide the useful result and this version has shown no meaningful advantage. The lab sets it aside, retaining the sources, alternatives and reasoning for the next experiment.
A recurring machine job is a starting point, not proof of a business. The laboratory keeps learning when an idea stops.