Author
@AndrewMayne AndrewMayne
grade Cx.com/AndrewMayne ↗
Transparent ex-OpenAI insider reasoning publicly on AI capability and labor macro
Posts reply-driven commentary and macro frameworks on fronti
trader score
-0.63
hit rate
69%
mean α
-0.39%
signals 14d
7
Grade = how their written analysis reads (A best). Trader score = how their last-20 timestamped calls performed vs SPY.
Their picks, scored
Across their last 13 scored bets: 69% hit rate, -0.39% mean alpha, trader score -0.63. Their last-14d mentions, direction-adjusted, have moved +4.5% since posting (mean over 1 mentions with price data).
Recent signals7receipts included
| date (PT) | ticker | author | sent | what they said | since then | receipt |
|---|---|---|---|---|---|---|
| 2026-10-14 | · | @AndrewMayne | · | Argues compute delivered per dollar will continue improving rapidly. | · | tweet ↗ |
| 2026-10-07 | · | @AndrewMayne | · | Argues DeepSeek Flash's higher token use narrows its apparent advantage over GPT-6 Luna. | · | tweet ↗ |
| 2026-10-07 | · | @AndrewMayne | · | Argues AI tools will expand rather than replace human work in mathematics and science. | · | tweet ↗ |
| 2026-10-05 | · | @AndrewMayne | · | Describes strong speech-to-text capability in a 17MB model | · | tweet ↗ |
| 2026-10-05 | · | @AndrewMayne | · | Demonstrates an AI agent designing, simulating and documenting a gear assembly | · | tweet ↗ |
| 2026-10-05 | · | @AndrewMayne | · | Compares AI models on token efficiency, performance and suitable workloads | · | tweet ↗ |
| 2026-10-05 | AAPL | @AndrewMayne | +0.25 | Historical framework credits NeXT and Jobs with Apple's corporate comeback | +4.5% | tweet ↗ |
Grade is our human read-worthiness rating; trader score is a rolling 20-bet hit-rate/alpha composite — different things, often disagreeing. “Since then” is direction-unaware in the table; the summary line above adjusts for which way they leaned.