Author
@akramsrazor akramsrazor
grade Ax.com/akramsrazor ↗
Deep AI-infrastructure bottleneck analyst turning macro frameworks into specific stock calls
Builds original fundamental theses around AI compute/power/m
trader score
-0.76
hit rate
55%
mean α
-0.35%
signals 14d
11
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 20 scored bets: 55% hit rate, -0.35% mean alpha, trader score -0.76. Their last-14d mentions, direction-adjusted, have moved +0.3% since posting (mean over 3 mentions with price data).
Recent signals11receipts included
| date (PT) | ticker | author | sent | what they said | since then | receipt |
|---|---|---|---|---|---|---|
| 2026-08-27 | · | @akramsrazor | · | Satirical framework warns that concentrated AI compute and debt-financed replacement create systemic risk. | · | tweet ↗ |
| 2026-08-27 | GTLB | @akramsrazor | +0.30 | Author discloses an OKTA long and argues enterprise software complexity benefits OKTA, NOW and GTLB despite AI doubts. | +0.1% | tweet ↗ |
| 2026-08-27 | OKTA | @akramsrazor | +0.35 | Author discloses an OKTA long and argues enterprise software complexity benefits OKTA, NOW and GTLB despite AI doubts. | -3.9% | tweet ↗ |
| 2026-08-27 | NOW | @akramsrazor | +0.30 | Author discloses an OKTA long and argues enterprise software complexity benefits OKTA, NOW and GTLB despite AI doubts. | +4.5% | tweet ↗ |
| 2026-08-23 | · | @akramsrazor | · | Satirically reframes AI bull and bear assumptions and anticipates a future compute glut. | · | tweet ↗ |
| 2026-08-23 | · | @akramsrazor | · | Explains why token volume is an unreliable proxy for physical compute use or serving cost. | · | tweet ↗ |
| 2026-08-23 | · | @akramsrazor | · | Argues useful intelligence is rapidly deflating in cost and mature agents may require far fewer LLM calls. | · | tweet ↗ |
| 2026-08-23 | · | @akramsrazor | · | Argues DeepSeek-like models use fewer FLOPs per token and could drive major compute deflation. | · | tweet ↗ |
| 2026-08-20 | · | @akramsrazor | · | Argues reported usage reflects ChatGPT distribution and says Codex had 5 million weekly users before changes. | · | tweet ↗ |
| 2026-08-18 | · | @akramsrazor | · | Criticizes a comparison by noting the server market was about $10B quarterly and racks and data centers were much smaller. | · | tweet ↗ |
| 2026-08-18 | · | @akramsrazor | · | Argues memory, not intelligence, limits agents and is central to future AI consumption revenue. | · | 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.