Raised datacenter mix assumption
assumption changed in NVDA v3
subThesis is an agentic investment research workspace. It tracks your assumptions, evidence, decisions, and outcomes as each thesis evolves — while AI agents, tailored to how you invest, work in the background, scenarios branch and run in parallel, and company financials stay current in real time. Every revision is sourced, timestamped, and reviewable, so your process compounds instead of disappearing into notes and memory.
5 positions · 117 research commits · last synced 2m ago
+1.38%
portfolio · today
Research version control
subThesis records the chain from assumption to evidence to decision to outcome. You can inspect what changed, who changed it, what source supported it, and whether reality later confirmed or broke the call.
What must be true for the thesis to work.
The filing, transcript, note, or datapoint behind each claim.
Why you bought, added, trimmed, held, or changed conviction.
What actually happened, tied back to what you believed then.
assumption changed in NVDA v3
source added to revenue claim
conviction +6 with memo attached
miss logged against base case
compare decision:b911 against outcome:2d07
See the exact evidence available at the decision point, then review what the market and company reported afterward.
Versioned thinking
Investment theses evolve. subThesis tracks every version — what you believed, when you believed it, and why it changed. Look back at v3 of your NVDA thesis and see exactly what evidence shifted your conviction.
Hyperscaler capex guidance continues to outrun foundry capacity. Lead times on datacenter GPUs extended again this quarter.
changed in v3
Datacenter revenue mix rose to 92% — gaming is no longer material to the thesis.
Primary risk: a capex air-pocket if AI training ROI disappoints. See scenario branch capex-peak-2026.
Evidence
Every claim in your thesis is anchored to filings, transcripts, and your own research notes. Memos compound into a permanent record of your thinking — append-only, never overwritten, always citable. And everything is stored as plain, open Markdown, so your research stays portable and never locked into a proprietary format.
NVDA · append-only · 41 entries
Segment disclosure confirms the shift. Re-rated conviction +6.
CFO: lead times "extended versus last quarter" — capacity still the binding constraint.
Cross-checked three cloud capex guides. All raised. Demand side intact.
Timeline
See thesis versions, sourced evidence, buy or hold decisions, and realized outcomes on a single time axis. Pan into the past to understand what you knew then. Pan forward to see which assumptions reality confirmed, contradicted, or left unresolved.
Pan left to see the assumptions, evidence, and decisions that built conviction. Pan right to compare those calls against realized outcomes.
Holdings
subThesis reads your position and trade activity — entries, adds, trims, and sizing — alongside the thesis behind each move. Every decision is tied back to the reasoning that drove it, so you can spot drift between what you believe and how you're actually positioned.
5 positions · 117 research commits · last synced 2m ago
+1.38%
portfolio · today
AI research agents
Pick a research task. The agent reads the 10-Q, scans monitored sources, executes the analysis, and lands a structured finding in your inbox. Some tasks run once. Some run forever — like watching a competitor's IR page every week, pinging you only when something changes.
Each agent is an AI tailored to your workspace and deeply personalized to your flow — it knows your theses, your sources, and how you reason, so every finding lands in your context. You decide what to track, what to investigate, and what to believe. The agent handles the legwork.
Re-underwrite on Q1 10-Q
triggered by filing
Segment-margin breakdown
one-time
Read 10-Q, draft thesis update
62% · ~8m left
Watch competitor IR page
weekly
Datacenter-mix finding
conviction +6
Capex cross-check
no change
10-Q lands. Thesis update drafted within 30 minutes.
Substack, X, IR pages, RSS — surface what's relevant to your positions.
Track speculative claims separately. Accept them into the thesis when evidence accumulates.
Confirmed, contradicted, missed — see how reality is testing your thesis in real time.
Gaps
Agents read your thesis against the evidence and flag what's missing — an untested assumption, a claim with no source, a risk you never priced. Gaps surface as work to do, not surprises after the fact, so the weak points in your reasoning are visible while you can still act on them.
NVDA · append-only · 41 entries
Segment disclosure confirms the shift. Re-rated conviction +6.
CFO: lead times "extended versus last quarter" — capacity still the binding constraint.
Cross-checked three cloud capex guides. All raised. Demand side intact.
Data layer
subThesis indexes SEC filings, earnings transcripts, and IR materials for every tracked position and keeps them current in real time. Explore company financials as they update — search across line items, drill into segment data, model scenarios with reverse-DCF and sensitivity tables. Your research is grounded in primary source documents — structured for how you actually think.
Q1 FY26 Quarterly Report
May 2026
Q1 FY26 Earnings Transcript
May 2026
FY25 Annual Report
Feb 2026
Investor Day — slide deck
Jan 2026
Q1 FY26 · pulled from 10-Q
Scenarios
Branch your main thesis into scenarios and run them in parallel. What if AI capex peaks in 2025? What if China demand drops 10%? Each branch evolves on its own — its own price target, conviction level, and per-event interpretation — letting you carry and stress-test multiple futures at once without losing your conviction in any single one.
Supply-constrained through 2027.
Training ROI disappoints; orders soften.
Export curbs tighten; mix absorbs most of it.
National compute programs add a demand leg.
subThesis builds the memory for you — what you thought, why you thought it, and what changed your mind, all kept and sourced. Six months in, you have a structured archive of your thinking. Two years in, it's irreplaceable.