Extension: Zhenfeng Cao, Agentic Software: How AI Agents Are Restructuring the Software Paradigm (arXiv:2606.05608v2, 2026)

Record: kaal:position:2026-09-12-005 · 2026-09-12

The benchmark evidence Cao cites shows agents degrading over continuous runs as errors compound. Kaal's position is that this pattern is authority drift: every step passes its check while the whole run goes beyond what was authorized. Evaluation must cover the whole run, and authority tied to tasks must expire when the work stops.

Affirmed commentary position. This record extends a source-bound scholarly claim but is not a verbatim paper claim.

Holds when

Cao's paper is a position paper citing benchmark evidence, not an empirical test of these claims.
The position is Kaal's own argument in the essay Prompts Don't Govern Agents. Reputation Does.
The position does not validate Cao's figures, benchmark methodology, or reported benchmark results.
The position is limited to continuous runs, aggregate authorization, and task-scoped authority.

Current debate

Zhenfeng Cao, Agentic Software: How AI Agents Are Restructuring the Software Paradigm (arXiv:2606.05608v2, 2026)

Scholarly basis

kaal:claim:7314479-015
Wulf A. Kaal, Institutional Requirements for Sovereign Local Agent Runtimes (2026). SSRN: https://ssrn.com/abstract=7314479
Source PDF sha256: debace24a155ae924a155b1fafe98856d98cf83689feff2f87a32f1c06171ce6

Topics

consensus-and-security governance-design ai-and-agents

Provenance

Affirmed in kaalvis:2026-09-12:prompts-reputation-essay-six-v1 on 2026-09-12. Review record.

Verify

Canonical markdown sha256: f9b8a8a8e465f7f8f4524bac46536f89b35d06ff9caba42635c200f61fe02e48
curl -s https://wulfkaal.github.io/positions/2026-09-12-005.md | sha256sum