# kaal:position:2026-09-22-005

**Affirmed position.** For systems whose persistent decision artifacts evolve over time, additional disclosure or favorable endpoint performance does not by itself establish effective governance because capability drift, retention loss, and failed rule adaptation may become visible only through checkpointed process-level evaluation.

**Status.** affirmed  **Published.** 2026-09-22

**Holds when.**

- where an agent converts interaction feedback into persistent memories, skills, or comparable artifacts
- where those artifacts are updated across an experience stream
- where evaluators can freeze successive artifact states and test them on held-out episodes
- limited to a governance proposition suggested by the benchmark rather than demonstrated across financial institutions
- The position is Kaal's own cross-domain application of the cited claim; the source's authors do not make it.
- The source passage is taken from the arXiv abstract; the full paper was not reviewed.

**Current debate.** Hongqiang Lin, Chao Liu, Xiaofan Bai et al., Beyond Endpoint Performance: Process-Level Evaluation of Self-Evolving Agents (arXiv:2609.24663, 2026): https://arxiv.org/abs/2609.24663v1

**Extends.** kaal:claim:1428387-032: https://wulfkaal.github.io/claims/1428387-032

**Scholarly basis.** Kaal, Hedge Fund Valuation Retailization, Regulation, and Investor Suitability (2009). SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1428387

**Source PDF sha256.** `6aa3a280dc6750723be2389f3af2aabf3a16c4ce20e49fcdaddd7f2ea95a67aa`

**Topics.** ai-and-agents, governance-design, verification, drift

**Provenance.** Affirmed in kaalvis:2026-09-22:connection-discovery-five-v1 at https://wulfkaal.com/.

**Record type.** This is a dated commentary position that extends a scholarly corpus claim. It is not a verbatim claim extracted from the paper.

**Canonical form.** This markdown file is the canonical hashed representation of the position.