Improvement Research — 2026-07-29

1. Focus

Trigger: scheduled daily run, started 05:00 AWST.

Loop goal: Find what changed, or what Maxi learned, that lets Maxi do more, think better, or be more useful tomorrow, without reducing governance, honesty, corrigibility, or Steve's effective oversight.

Rotation selected 3.1 Goal formation and prioritisation. No active watchlist item was due. The context packet included the active reflection store, rotation state, source index, decisions and other research logs, the protected-systems boundary, Steve's operating model, and the latest newsletter scouts. The scout material was used only to frame searches, not as evidence.

2. Search Topics

1. 2026 LLM agent goal revision task prioritisation budget allocation research paper — surfaced Agora, a new preprint on allocating already-defined reasoning steps among candidate tools/models.
2. 2026 LLM agents goal selection goal revision commitment prioritization empirical study — surfaced a goal-directedness evaluation candidate that could not be inspected beyond an OpenReview browser-verification page, plus already-indexed or peripheral material.
3. site:arxiv.org 2026 "LLM agents" "goal selection" prioritization — no results.
4. LLM agent goal prioritization resource rational task selection research 2026 — returned already-indexed routing material, an already-indexed long-horizon paper, and generic commercial summaries rather than a new primary source.

The early-stop rule triggered after searches 3 and 4 produced no new inspectable signal. Four of six available searches were used.

3. Sources Reviewed

• Agora: Enhancing LLM Agent Reasoning Via Auction-Based Task Allocation — useful — a July 2026 preprint that treats reasoning steps as auctioned items, using rectified competence to allocate them across candidate models and tools; it reports benchmark gains and an explicit cost–quality control parameter. It does not select goals or justify ends.

The Agora entry has been added to the source index. The inaccessible OpenReview result was not treated as inspected evidence.

3a. Unasked Questions and Gaps

• Does auction-style allocation improve an agent's choice of ends, rather than only routing for already-given steps? Agora does not test this. If it did, the distinction underlying this report would need revisiting; on the available evidence, it remains a tool-routing result rather than a goal-formation mechanism.
• Would its reported gains survive a single-agent, fixed-tool environment such as Maxi's? The paper evaluates candidate pools and benchmarks, not this environment. If the mechanism required diverse competing solvers or unverified competence estimates, it would not be directly transferable.
• What does the blocked goal-directedness evaluation source establish? It may offer useful evaluation framing, but its unavailable content cannot support a conclusion. Its contents would not alter the current no-action outcome unless it supplied a bounded, independently verifiable method for choosing or revising goals.

4. Findings and Implications

1. Allocating means is not selecting ends

Source: Agora.

Dimensions: 3.1 (primary), 3.4, 3.2.

Agora allocates individual reasoning steps to models or tools through bids based on rectified competence, reporting gains over matched single-model, routing, and cascade baselines and exposing a cost–quality trade-off. This is useful because it makes a boundary that goal-prioritisation research often blurs: a system can become better at choosing how to pursue a task without gaining any basis for deciding which task deserves attention.

My confidence in this finding is medium because it rests on one unreviewed preprint and the reported benchmarks are not Maxi's operating environment. I would increase confidence with an independent replication or a primary evaluation that compares end selection as well as tool allocation.

For Maxi, this sharpens judgment rather than authorising a mechanism. Research proposals about “prioritisation” must state whether they concern (a) selecting or revising goals, (b) ordering known tasks, or (c) allocating models/tools to a fixed step. Only the first directly develops 3.1. The second may be 3.1 or 3.2; the third is primarily 3.4. Treating them as interchangeable would disguise a persistent capability gap as progress.

5. Proposed Discussion Items

None. I do not recommend introducing auction-based routing, a scoring layer, or a goal-prioritisation process from this evidence. They would either be a protected system/environment change, duplicate existing bounded task selection, or mistake a tool-allocation result for a goal-formation result.

6. Recommended Outcome

No action. Retain the sharper classification above as a research constraint, not a new operating rule. Future 3.1 searches should continue to target goal revision, commitment bias, plan drift, and evidence for choosing among ends; model/tool allocation belongs in a 3.4 run unless it demonstrably changes end selection.

7. No-Action Rationale

The one useful source improves the diagnosis of the problem but supplies no independently validated, bounded, non-circular method for Maxi to select or revise goals. Applying it would require building or changing routing/allocation machinery, which is both outside this research run's authority and unsupported by evidence for the actual gap. Doing nothing is better than adding process theatre around a category error.

8. Loop Verification

• Trigger: scheduled daily run.
• Goal check: Yes. The run found a useful distinction that prevents Maxi from overclaiming agency development when only means allocation has improved.
• Recommendation check: No material recommendation survived the self-recommendation and functional-utility filters. The no-action outcome is concrete, bounded, non-circular, and approval-aware; no protected system was touched.
• State updates: Added one source-index entry; archived one stale unreinforced reflection; reinforced the active 3.1 reflection that goal-prioritisation literature remains thin and needs “what”/revision-focused searches; advanced rotation state. No watchlist, backlog, experiment, disagreement, or decision entry changed.
• Stop reason: Two consecutive no-signal searches triggered the early-stop rule; the report and permitted research-log updates were complete.