WTKRESEARCH + ENGINEERING

AI Agent Research and Falsification Experiments

Research questions, methods, and evidence.

WTK investigates what makes agents and teams useful, accountable, portable, and capable of improving. Outside research and implementation experience inform experiments that can support, narrow, or change the design.

Questions informing WTK development

Each area connects a practical problem to current questions, published research, and experiments. These are investigations, not claims that WTK has solved the problem.

Agent usefulness and outcome evaluation

Did the agent accomplish the intended goal?

A completed task or a convincing answer may still miss what a person needed. We study how to define useful outcomes and test whether agents deliver them.

Authority, security, and oversight

What may an agent do, and when should a human decide?

As agents take on more work, mistakes can have greater consequences. We investigate permissions, independent review, and the limits of automated decisions.

Agent-team coordination and reliability

Does the team work reliably as a whole?

Agents that perform well individually can fail when they share work. We study delegation, handoffs, disagreement, and responsibility for the final result.

Portability and reuse

What needs testing when an agent moves to another environment?

Changing a model, tool, or runtime can change behavior. We investigate how to preserve an agent’s purpose and history while identifying what needs fresh evidence.

Governed improvement and progressive automation

How can changes to agents and their models be evaluated and governed?

We study how changes to agents and their underlying models are evaluated, approved, and deployed. The question is how to improve useful outcomes while preserving independent evaluation and human oversight.

External research and its implications

Research notes distinguish the source findings from WTK’s interpretation and proposed tests. An outside result is not a WTK result.

Engineering journal

Research, testing, and revision

Questions lead to proposed tests. Results may change the implementation or leave the question unresolved. Development records explain changes; the evidence ledger retains the limits of what can be claimed.

Have an approach, result, or counterexample?

You may be asking the same question, or may already have a useful answer. Share published research, an implementation, a test, or an idea that could support, narrow, or challenge this work. Distinguish what you tested from what remains a hypothesis.

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