Buildability / Receipt
This public receipt window renders only fields present in the canonical receipt object, deterministic fixture receipt, or canonical evidence receipt. Missing compute, demo, hash, signature, approval, telemetry, and adoption fields stay explicit.
Public buildability page receipt window
/buildability/from-experience-to-skill-multi-agent-generative-engine-optimization-via-reusable-strategy-learning
Subject: From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning
Verdict
Build Now
Verdict is Build Now because viability and implementation proof cleared the Wave 1 scaffold thresholds.
Time to first demo
Insufficient data
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Data
{"file name": "input.pdf", "number of pages": 18, "author": "Beining Wu; Fuyou Mao; Jiong Lin; Cheng Yang; Jiaxuan Lu; Yifu Guo; Siyu Zhang; Yifan Wu; Ying Huang; Fu Li"
Truth Boundary
Buildability surfaces only report computed viability and proof receipts. They do not claim live production usage, pilot outcomes, founder sign-off, public Brier calibration, judge divergence, or external adoption unless explicitly sourced.
Compute
{"file name": "input.pdf", "number of pages": 18, "author": "Beining Wu; Fuyou Mao; Jiong Lin; Cheng Yang; Jiaxuan Lu; Yifu Guo; Siyu Zhang; Yifan Wu; Ying Huang; Fu Li", "title": "From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning", "creation date": null
Inference
{"file name": "input.pdf", "number of pages": 18, "author": "Beining Wu; Fuyou Mao; Jiong Lin; Cheng Yang; Jiaxuan Lu; Yifu Guo; Siyu Zhang; Yifan Wu; Ying Huang; Fu Li", "title": "From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning", "creation date": null
Hardware
{"file name": "input.pdf", "number of pages": 18, "author": "Beining Wu; Fuyou Mao; Jiong Lin; Cheng Yang; Jiaxuan Lu; Yifu Guo; Siyu Zhang; Yifan Wu; Ying Huang; Fu Li", "title": "From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning", "creation date": null
Receipt path
/buildability/from-experience-to-skill-multi-agent-generative-engine-optimization-via-reusable-strategy-learning
Paper ref
from-experience-to-skill-multi-agent-generative-engine-optimization-via-reusable-strategy-learning
arXiv id
2604.19516
Generated at
2026-04-22T20:32:43.398Z
Evidence freshness
stale
Last verification
2026-04-22T20:32:43.398Z
Sources
4
References
0
Coverage
83%
Lineage hash
2e79bba958eb272a1d9503f94fa48be4a4ef57594d95849262b28618755f2161
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
No founder, registry, pilot, or production-adoption signature is attached to this receipt.
Verification
not_verified
Verification is blocked until an external signature is provided.
Some score or evidence fields are outside the preferred freshness window.
references