docs/dream-cycles/2026-07-22-intelligence-sota.md
TL;DR: In 2026, agent intelligence is bifurcating into query-type routing (dispatch factoid vs. multi-hop vs. synthesis to specialized pipelines) and intrinsic metacognition (agents modifying their own learning process). Ruflo has neither; the gap is architecturally addressable with one new module.
| Finding | Source | Confidence |
|---|---|---|
| Supra Cognitive Modes (SCM): routed memory architecture scores 84.87% LoCoMo, 86.00% LongMemEval via frozen classifier dispatching queries to lexical+dense, graph multi-hop, or synthesis paths | arXiv 2607.19096, July 21 2026 | B — self-reported, single paper, no independent repro yet |
| Single-agent LLMs outperform multi-agent systems on multi-hop reasoning under equal token budgets | arXiv 2606.13003, June 2026 | B — arXiv, results on standard benchmarks |
| HyperAgents (META/UBC/Oxford/NYU): intrinsic metacognitive self-improvement — agents modify their own modification procedure, transferring learned improvement strategies across novel domains | March 2026, published research | B — multi-institution, cross-domain transfer demonstrated |
| ResearchArena: training-data sabotage is caught <50% of the time by state-of-art monitors even with artifact execution access | arXiv 2607.19321, July 21 2026 | B — dedicated benchmark, four task types |
| OSWorld computer-use SOTA at ~38% as of April 2026 | benchmarkingagents.com | C — single aggregator source |
| CrewAI v1.12: hierarchical memory isolation, Qdrant Edge backend, 60% Fortune 500 adoption | CrewAI release notes 2026 | B — vendor claim, corroborated by multiple outlets |
| LangGraph v1.1.3 GA: per-node timeouts, durable streaming, powers Klarna/Uber/LinkedIn | LangGraph release notes 2026 | B — vendor claim, corroborated |
| AG2 Beta redesign: event-driven, streaming, dependency injection — AutoGen in maintenance mode | AG2 blog 2026 | B — confirmed by Microsoft |
| Zep Graphiti: 63.8% on LongMemEval temporal retrieval sub-task | mem0.ai state-of-memory-2026 | C — single benchmark source, vendor |
| Feature | Status | Evidence |
|---|---|---|
| HNSW vector search | Active | Measured ~1.9×–4.7× vs brute force at N=5k–20k |
| SONA adaptation | Active | 0.0043ms/adapt, target <0.05ms met |
| MoE routing (model selection) | Active | Gate confidence 0.13→0.88 after rewards |
| Query-type cognitive mode routing | Absent | No dispatcher for factoid vs. multi-hop vs. synthesis |
| Intrinsic metacognitive loop | Absent | SONA adapts task behavior; does not modify its own adaptation heuristics |
| LongMemEval tracked benchmark | Absent | ADR-088 adds evaluation but no tracked CI score |
| Training-data sabotage detection | Absent | No equivalent to ResearchArena monitoring |
| Competitor | Intelligence Routing | Long-Term Memory | Published Benchmark Score | 2026 Status |
|---|---|---|---|---|
| LangGraph v1.1.3 | Per-node timeout + durable streaming | None built-in (external) | No LongMemEval published | GA, production at Klarna/Uber |
| CrewAI v1.12 | Role-based hierarchical isolation | Qdrant Edge backend | No LongMemEval published | 60% Fortune 500, 44k stars |
| AG2 (AutoGen) Beta | Event-driven typed tools | None built-in | No LongMemEval published | AutoGen maintenance mode |
| OpenAI Swarm | Composable self-organizing | None built-in | No intelligence benchmark | Research-only, no production release |
| SCM (research) | Frozen classifier → 3 specialized pipelines | Full episodic + graph | 86.00% LongMemEval (B-grade) | Academic, July 2026 |
| Ruflo | MoE model routing (not query-type) | HNSW + AgentDB | Not tracked on LongMemEval | Needs CMR module |
| Benchmark | SOTA Score (2026) | Who | Grade | Ruflo Score |
|---|---|---|---|---|
| LongMemEval | 86.00% | SCM (arXiv 2607.19096) | B | Not tracked |
| LoCoMo factoid | 84.87% | SCM | B | Not tracked |
| MemoryAgentBench (MAB) | 61.49% | SCM | B | Not tracked |
| LongMemEval temporal | 63.8% | Zep Graphiti | C | Not tracked |
| OSWorld (computer-use) | ~38% | Multiple | C | Not applicable |
No 2026 grade-A reproducible intelligence benchmark was identified for Ruflo's specific architecture. Grade-A claim would require independent reproduction of SCM results on public data.
| Field | Value |
|---|---|
| Session commit | 26c35b59b40a0a95b286ccf5ac675a15edcc995f |
| Report SHA-256 | 5ab9f7f71551649c97bc683529b2ac767213cb754162b9c148a7b1f8d1e1582b |
| Witness stamp | 0c59c02c3e855c4907cf7cd9445f61a5624b5b486c4825f6cc9ceab83d1038d7 |
| Verifier | sha256(report) + session_commit → sha256 = WITNESS |
Implement Cognitive Mode Router (CMR) in @claude-flow/memory: add a frozen semantic classifier that routes incoming memory queries to one of three specialized pipelines — (a) lexical+dense factoid lookup, (b) graph multi-hop traversal, (c) long-form synthesis — mirroring SCM's architecture. Track LongMemEval score in CI. Target: match or exceed Zep Graphiti's 63.8% temporal sub-task within 2 sprints.
Add intrinsic metacognitive hook to SONA: extend the SONA adaptation loop so the agent can evaluate the effectiveness of its own adaptation heuristics (not just task outcomes) and rewrite those heuristics when trajectory confidence is low for ≥5 consecutive rounds. This closes the extrinsic→intrinsic metacognition gap identified by HyperAgents research.
Establish ResearchArena-style sabotage monitor: given that training-data sabotage evades detection <50% of the time even with artifact execution access, add an integrity verification hook in @claude-flow/security that computes and stores a cryptographic manifest of agent-produced artifacts before and after training runs, alerting on divergence exceeding a threshold. This directly addresses the ResearchArena blind spot.