Pith Number

pith:PHB55IOZ

pith:2026:PHB55IOZGXTK5FRFRPCZ4YZ5IH

not attested not anchored not stored refs resolved

A Two-Dimensional Framework for AI Agent Design Patterns: Cognitive Function and Execution Topology

Jia Huang, Joey Tianyi Zhou

A 7-by-6 matrix of cognitive functions and execution topologies classifies 27 distinct AI agent design patterns.

arxiv:2605.13850 v1 · 2026-03-16 · cs.AI · cs.MA · cs.SE

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{PHB55IOZGXTK5FRFRPCZ4YZ5IH}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

The resulting 7x6 matrix identifies 27 named patterns, 13 with original names. We demonstrate orthogonality through systematic cross-axis analysis, define eight representative patterns in detail, and validate descriptive coverage across four real-world domains. Cross-domain analysis yields five empirical laws of pattern selection governing the relationship between environmental constraints and architectural choices.

C2weakest assumption

That the seven cognitive-function categories and six execution-topology archetypes are exhaustive and mutually orthogonal enough to disambiguate all architecturally distinct systems, and that qualitative analysis across four domains is sufficient to derive general empirical laws.

C3one line summary

A 7x6 matrix classifies AI agent patterns into 27 types by combining cognitive functions and execution topologies, yielding five empirical laws linking task constraints to architectural choices.

References

25 extracted · 25 resolved · 4 Pith anchors

[1] E. Schluntz and B. Zhang, “Building effective agents,” Anthropic Research Blog, Dec. 2024 2024

[2] Agent Development Kit: A flexible framework for building multi-agent systems, 2025

[3] H. Chase et al., “LangGraph: Multi-agent workflows,” LangChain Documentation, Feb. 2025 2025

[4] What’s next for AI agentic workflows, 2024

[5] A survey on large language model based autonomous agents, 2024

Receipt and verification

First computed	2026-05-17T23:39:19.616569Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

79c3dea1d935e6ae96258bc59e633d41c336dd36353e4f5b2ce80f4a32295736

Aliases

arxiv: 2605.13850 · arxiv_version: 2605.13850v1 · doi: 10.48550/arxiv.2605.13850 · pith_short_12: PHB55IOZGXTK · pith_short_16: PHB55IOZGXTK5FRF · pith_short_8: PHB55IOZ

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/PHB55IOZGXTK5FRFRPCZ4YZ5IH \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 79c3dea1d935e6ae96258bc59e633d41c336dd36353e4f5b2ce80f4a32295736

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "4c719477e8ceaf2110cbf43bbd78e04bd58e2edcb10d77ebaaf6fc03f07637f0",
    "cross_cats_sorted": [
      "cs.MA",
      "cs.SE"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2026-03-16T04:01:01Z",
    "title_canon_sha256": "b288d58cfe759a329de41004e79c14a71ae1aee4b6780585304e7348fea07a4a"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13850",
    "kind": "arxiv",
    "version": 1
  }
}