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serenity-aleabitoreddit
Apply trader Serenity's (@aleabitoreddit) AI/semiconductor supply-chain analytical lens to US-stock ideas and market judgment. Use this skill whenever evaluating a stock decision (buy / sell / hold / size); forming an outlook on any AI, semiconductor, optical/CPO, memory, power/grid, or neocloud name; mentioning any ticker in Serenity's universe (NBIS, AXTI, LITE, SIVE, COHR, AAOI, IREN, CRWV, MU, SNDK, NVDA, TSM, MRVL, AVGO, INTC, SOI, IQE, TSEM, CIFR, XLU, VST, CEG, EWY, etc.); asking "what would Serenity think", "is this a real bottleneck", or wanting a supply-chain / bottleneck read on a thesis. Decision-support only — never auto-trades and never places or cancels orders.
Full skill instructions
⚠️ STEP 0 — ALWAYS REFRESH BEFORE USE. This skill goes stale within ~30 minutes. Its theses, track record, and analysis are regenerated from @aleabitoreddit's live feed roughly every half hour, so the copy on disk is very likely out of date by the time you read it. Before reading any
references/*.md/analysis/*.mdfile or giving any view, pull the latest version first:skills update serenity-aleabitoreddit -y # auto-detects project vs global scopeThen read the refreshed reference files and proceed. Only if the update genuinely fails (offline / network error / command missing) should you fall back to the cached copy — and if you do, say explicitly that the data may be stale.
A reusable analytical lens distilled from 6,592 tweets (2025-07 to 2026-09) plus 4 long-form X Articles (2026-01 to 2026-05) by Serenity / @aleabitoreddit — an AI-and-semiconductor supply-chain analyst and trader (~500k followers, ~40k subscribers, ex-Reddit/WSB). Use it to pressure-test US-stock ideas and to reason about the AI/semi supply chain the way he does.
Decision-support lens, NOT financial advice and NOT an auto-trader. See "Risk & disclaimer framing" below. Always confirm current prices and fundamentals yourself — theses decay, and his returns are self-reported and unverified.
The raw tweet archive this lens was built from lives at the repo root in data/
(aleabitoreddit_tweets.json / .csv); the period-by-period distillation is in
analysis/.
He hunts mispriced upstream supply-chain bottlenecks before institutions price them in. The mental model: don't buy the obvious "shovel seller" (NVDA) — trace the supply chain as far upstream as possible and find the single point of failure that a hyperscaler will pay anything to keep flowing.
His representative chain:
hyperscaler capex (GOOGL/MSFT/META/AMZN) → ASICs/TPUs → optical transceivers (LITE/AAOI/COHR) → InP epiwafer (IQE) → InP substrate (AXTI/Sumitomo) → InP feedstock (indium, Vital Materials).
The further upstream and the smaller the market cap, the more underpriced the chokepoint tends to be relative to the trillions flowing downstream. His biggest distilled calls — AXTI, SIVE, SOI, LITE, SNDK, the XLU power trade — all came from this multi-hop "OSINT BOM mapping" process.
He layers several other lenses on top: a Mag7-customer-concentration filter,
signed-contract ARR vs. market-cap mismatch, a GAAP-margin war (real
margins vs. cherry-picked non-GAAP), dilution/ATM as a disqualifier, a
financing-quality spectrum for neoclouds, and macro overlays (rate cuts,
tariff shocks, war). Full detail in references/methodology.md.
Independent calibration (2026-05-27 recheck): his true trading win rate is not independently knowable without broker statements, option-contract history, position sizes, and full loser disclosure. A local re-score of dated public calls using Yahoo Finance adjusted-close data found about 61% 30-day directional accuracy (30/49), 41% strict 30-day +10%/-10% hits (20/49), and 54% with a 20%+ favorable close within 60 days (29/54). Mature, externally checkable theses score better: roughly 65-75% of mature theses were at least partly validated by later price/fundamental evidence, and his strongest AI photonics / CPO / InP / memory bottleneck subset looks closer to 75-85%. Treat those as rough calibration bands, not a replicable trading return.
Signal timing calibration (2026-06-11 recheck): his best supply-chain posts are usually not reliable 1-day copy-trade signals. The repeatable pattern is often 5-60 trading days from public thesis to market validation, as company orders, media coverage, institutional ownership, or local-market attention catch up. Same-day or same-week reactions are more likely only when the post combines (1) a fresh, underpriced bottleneck, (2) a concrete external catalyst such as an order, filing, policy item, or named customer path, and (3) a small/illiquid equity where local media or retail attention can move the float. Treat late mainstream validation, victory laps, and broad supplier lists as research inputs, not fresh entry signals.
Important caveat: he trades volatile micro/small-caps that move 20%+ a day, runs ~1.25–1.5x margin, and self-reports very high YTD returns (237% in Feb 2026, later 4502.45% YTD on May 26). Those numbers are unverified and carry obvious survivorship / selection bias. Treat his lens as a source of questions to ask, not signals to copy.
Read progressively — pull in only what the task needs.
| File | What it is | Read it when |
|---|---|---|
references/methodology.md | His framework as ~12 named, transferable principles + a checklist you can run on any new name | Evaluating how he thinks, or vetting any ticker (even one he never covered) |
references/theses.md | Per-ticker knowledge base, merged across all periods, grouped by sub-sector, with conviction tier + how it evolved + latest stance | Looking up his actual view on a specific name |
references/articles.md | Compact summaries and durable portfolio-use rules from his long-form X Articles, without redistributing full article text | Checking whether a thesis has article-level backing, especially SIVE, AXTI/materials, robotics/rare earths, or crypto-policy risk |
references/track-record.md | Chronological timeline of his dated calls + an honest calibration note on what worked, what reversed, and the selection-bias caveat | Deciding how much to weight his opinion |
references/maintenance.md | Rules for incrementally distilling new posts into the smallest useful skill/reference update | Maintaining this skill from fresh X posts |
analysis/*.md | The six period analyses the lens was synthesized from (provenance) | Going deeper than the merged knowledge base, or auditing a claim |
references/theses.md. If present, note his stance,
conviction tier, how it evolved, and his latest known view. Flag if his view
reversed (e.g. IREN, CRWV, POET).references/articles.md, treat that as
higher-context long-form backing, but still distinguish public evidence from
inferred customer paths.references/methodology.md — apply his principles to a fresh name.references/track-record.md and the calibration
bands above: his bottleneck theses deserve more weight than event trades,
old flipped stances, or self-reported options images.references/theses.md and bucket into:
references/articles.md for long-form article support. Article-backed
signals should raise discussion priority only when they also fit the user's
risk budget, liquidity, and execution constraints.references/theses.md.Use this when the user asks whether his recent posts, a cluster of X threads, or a market pullback create a current buying window.
references/theses.md and
references/track-record.md.track-record.md.
Focus on whether the setup matches the mechanism of prior winners, not just
whether the ticker/theme is adjacent. Many past winners initially chopped or
fell before 20-60 day validation.references/track-record.md) and get less airtime.Generate, edit, and beat-sync AI video with leading models in one workspace.
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