Your teams are introducing AI across tools and workflows. The next challenge is coordinating that work while keeping requirements, authority, and decisions connected.
Decomposes complex engineering objectives into non-colliding work packages with bounded file touches.
A task can appear complete while the next team still lacks a required input, an approval, or the basis for a decision. Our research examines how those gaps can become visible before downstream work depends on them.
An engineering team proposes a change affecting two connected systems. Follow the work as it encounters a missing requirement, returns for review, and carries its decision forward.
Engineering request EC-014 touches both System A and System B. The affected boundary is identified before work begins.
Intended functionality illustrated with fictional data. This sequence is not a live deployment or recorded test.
Investigating the mathematical topologies, boundaries, and protocols that make autonomous agent work dependable.
We develop and evaluate how agents exchange engineering work through explicit requirements, handoffs, and recorded decisions.
Our engineering and decision-operations runtime provides a proving environment for evaluating coordinated multi-agent software development, dependency gating, and human sign-off boundaries.
We investigate how tasks can receive the information they need while keeping context and review manageable.
Methods for selective context extraction and bounded knowledge injection. We distinguish a research direction from a demonstrated result, presenting evidence alongside workload conditions and limitations.
We study how people, agents, and machines exchange responsibility as work moves between them.
Methodology and interface standards for delegated authority, exception handling, and retained decision rationale. Eliminates silent failures by making handoff contracts explicit.
A proposed structured method to evaluate fit and boundaries before committing broad operational changes.
Identify the workflow owner, connected systems, inputs, and consequential handoffs where unhandled errors create operational risk.
Agree on requirements, permissions, human review points, failure conditions, and a realistic comparison baseline.
Review observed agent behavior, unhandled exceptions, handoff quality, and verified boundaries against the criteria.
Understand what an evaluated capability supports, where it falls short, and what further development or integration would require.
NationOS carries the name of founder Cory Nation. The intended deployed ecosystem carries yours—shaped around your organization's people, systems, and work.
People. Agents. Connected work.
Developed from NationOS · Build TBD Innovation LabsBuild TBD Innovation Labs brings systems-engineering discipline to AI and agentic research. We distinguish a research direction from a demonstrated result, and a demonstration from readiness for your environment.
Results belong with their workload, comparison baseline, system version, observed quality, and limitations. Technical evaluation is scoped to the question your organization needs to answer.
Bring a consequential workflow, a research question, or an interest in your own operational ecosystem.