Questions & answers

ObliNet is a proposed coordination layer that makes explicit who commits to deliver what to whom, by when, under which conditions, and how the result will be confirmed. Links between commitments reveal what depends on other participants’ actions.

ObliNet organizes coordination around the commitment as the primary object of the system. Before acceptance, feasibility is checked: authority, resources, conditions and dependencies. After confirmation, execution, changing conditions and confirmation against agreed criteria are tracked. AI assists participants in this work; authority remains with the respective participants.

A task describes work, while a promise expresses an intention to do it. A confirmed commitment also specifies who may expect which result, under what conditions, and who accepts it. In ObliNet’s approach, it follows clarification and confirmation by the respective participants. Recording a promise does not by itself turn it into a legal contract.

Participants do not need identical worldviews or interests. To work together, they need to clarify what a particular action depends on: the expected outcome, conditions, resources, authority and dependencies. A confirmed commitment records this agreement and the grounds on which participants may rely on it. It does not guarantee that assumptions are correct, so conditions and evidence require further scrutiny.

Are the result and acceptance criteria clear? Does the participant have the authority, resources and time? Which permissions and actions by others are needed? Are those dependencies confirmed? Unknowns remain explicit: checking helps identify risk but does not guarantee success.

Yes. At the proposal stage, a participant can decline, request clarification or propose different terms. Identified infeasibility is a reason to revise the proposal before confirmation. Changing an already accepted commitment requires taking existing agreements and the parties’ authority into account.

Identify the affected commitment and those who depend on it, then agree on the next steps. Original terms, the reason for change and the confirmed revised agreement remain in the history. The system must not silently rewrite participants’ commitments.

Result criteria and acceptance authority are defined in advance. AI can compare evidence against criteria, but confirmation remains with the authorized party. In a disagreement, positions and evidence are recorded and the issue follows an agreed escalation process. A record marked “completed” is not proof of completion by itself.

It helps identify possible commitments in conversations, formulate conditions, find gaps and dependencies, compare options and assess evidence of fulfillment. Its conclusions can be wrong and must be open to verification. An AI assumption does not create the parties’ consent.

Technical capability alone does not confer authority. An agent may act on a participant’s behalf only within an explicit mandate. Beyond that mandate, a decision by the appropriate authorized participant is required. A model does not automatically gain the right to enter into or confirm commitments, or accept fulfillment.

No. Making commitments observable does not require exposing all correspondence or private life. Access should depend on role, authority and the purpose of verification. Each pilot must specify what information is collected, who can access it and how long it is retained.

Yes, that is a risk. Formalization is justified where the cost of ambiguity exceeds the effort of clarification. Start with one important interaction and a minimal set of fields. A pilot must measure both benefits and participants’ time, rather than treating more records as success.

In the proposed approach, an assignment is clarified into a confirmed commitment: who is responsible for the result, what they need from colleagues, when the work is ready and who accepts it. A manager can identify overload and incompatible deadlines earlier, while a participant can state conditions or propose a revision. For example, a designer confirms a deadline after agreeing when materials will arrive. Fewer missed commitments and less manual supervision are expected benefits to test, not established outcomes.

Commitments connect departments and independent participants: sales, production, procurement, logistics and the customer. A promised delivery date is checked against capacity, supplies and acceptance. A changed dependency reveals which agreements need revision. This complements existing accounting and management systems; authority is defined by the organization’s charter, contracts and rules, rather than by AI.

A resident’s request can be connected to the responsible body’s authority, a specific commitment, funding, implementers and result criteria. Repairing a shelter, for example, depends on access, inspection, funding, work and acceptance. City officials see obstacles between services, while residents see the agreed result and available evidence of its achievement. Resident feedback complements formal acceptance within an established procedure. Closing a request should not substitute for solving the problem.

A public programme is represented as a network of linked commitments by ministries, regions, municipalities and implementers. Before a public promise, authority, resources, conditions and dependencies are clarified; afterward, execution and confirmation of results are tracked. AI helps detect conflicting plans and assess evidence. Political priorities, budget allocation and conflicts of interest remain matters for legitimate human and institutional decisions.

A commitment at one level becomes an explicit dependency at another. If a municipality relies on national funding, the funding conditions, responsible parties and confirmed status are recorded. A delay reveals which local deadlines and results are affected. Authorized participants agree on changes; the system must not automatically shift responsibility onto someone who does not control the cause of the delay.

The approach does not in itself entail such a replacement. It proposes making the connection between authority, commitments, actions and results observable within existing institutions and between independent participants. AI assists analysis but gains no right to appoint, punish or remove leaders on its own. Better accountability depends on reliable data, the right to challenge decisions, privacy protection and participants’ willingness to follow the rules.

Leaders should know that significant decisions, their grounds and consequences are available for assessment by those who delegated authority and by authorized oversight bodies. Delegating authority entails the ability to scrutinize its use in a company, institution, municipality or state. Disclosure is governed by reviewers’ authority and data protection requirements. A record does not prove that a decision was justified: evidence must be checked and assessments must be open to challenge. In public governance, this principle complements existing electoral and oversight institutions.

In business handoffs, client–contractor relationships, research projects, AI-agent workflows and the execution of public decisions. Repairing a facility, for example, depends on access, permits, funding, contractor work and acceptance. These are proposed applications, not claims of proven effectiveness across these settings.

An experimental platform already exists for testing individual ObliNet mechanisms: commitment clarification and checks, dependencies, revision and acceptance. The next stage is an end-to-end pilot within a specific organizational process. Comparisons in the experimental environment show the relative effectiveness of rules within specified scenarios and assumptions. They do not establish effectiveness in real organizations, which remains to be tested in end-to-end pilots. Having a mechanism does not mean it detects every error or guarantees feasibility.

See what already exists →

Choose one recurring process, its participants and a problem, such as a missed dependency or ambiguous acceptance. Record baseline measures and evaluation criteria. Compare explicit commitments with the previous process: timing, misunderstandings, renegotiations, confirmed results and time spent.

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