Two real estate command centers. One private dashboard.
This site is now split into Anchor Capital for internship/work learning and Personal Real Estate for Henry’s own future business with Eden.
This site is now split into Anchor Capital for internship/work learning and Personal Real Estate for Henry’s own future business with Eden.
Anchor is for learning Anchor’s world, markets, tasks, and research. Personal is for building Henry’s future deal machine, business plan, owner network, and market thesis.
Professional workspace for Anchor-related research, property tracking, market notes, contacts, and internship learning.
Founder workspace for Henry’s own real estate business: deal ideas, target markets, business planning, learning, and future company building with Eden.
Daily overview for internship work, Anchor-style research, and becoming more useful professionally.
Use Anchor Capital to organize what you are learning at Anchor: properties they care about, markets they discuss, people/companies worth knowing, and questions to bring back to the team.
Track properties related to Anchor’s markets, research, and learning. Keep these separate from personal opportunities.
Study markets Anchor cares about: NYC, Long Island, borough submarkets, industrial/flex nodes, and areas mentioned internally.
Deeper work memos, zoning notes, rent/sale comps, company research, and questions to ask at Anchor.
Targeted real estate news for Anchor’s world: NYC, Long Island, industrial, capital markets, zoning, and major sales.
Owners, brokers, developers, tenants, lenders, and companies connected to Anchor-related research.
Your internship notebook for lessons, questions, vocabulary, coworker advice, and things to remember.
Ideas for how Goose can better help you serve Anchor: faster research, cleaner property analysis, smarter questions, and stronger market awareness.
Overview for Henry’s own future real estate business: deals, target markets, owners, learning, and business planning with Eden.
Use Personal Real Estate to build your own deal machine before graduation. This is where your ideas become target markets, owner lists, deal stages, and a business plan.
Your own property database for anything that could someday matter to your future company.
Move serious personal opportunities through a simple pipeline from idea to research to outreach to underwriting.
Markets Henry may realistically study, visit, invest in, or build a thesis around.
Relationship database for owners, brokers, lenders, contractors, attorneys, investors, and people who could matter later.
The blueprint for Henry and Eden’s future real estate company.
Real estate finance, development, underwriting, books, videos, lessons from Anchor, and skills to master before graduation.
Broader news that helps Henry’s own company: student housing, small multifamily, development, rates, and local market trends.
Notebook for ideas with Eden, lessons from your dad, deal thoughts, market observations, and future company planning.
Ideas for how Goose can help Henry and Eden build a sharper real estate business: deal sourcing, owner outreach, underwriting practice, market thesis work, and task automation.
The latest morning real estate briefing appears here automatically from Hermes cron output.
data/dashboard.json.Live-ish operating view of Hermes scheduled jobs, recent status, and new automation ideas Goose recommends.
Focused paper-trading lab for NYC Central Park / KNYC daily high-temperature markets. One market, one station, one repeatable process.
We are modeling the official Central Park high temperature used by Kalshi settlement — not generic NYC weather. Paper only until the sample proves durable edge.
Run dashboard refresh to load KNYC forecast data.
Pull public NYC Kalshi weather markets and rank them by tradability. This is read-only market data, not order execution.
Scanner idle. Uses Kalshi public market-data endpoints.Read-only public Kalshi data for KXHIGHNY. Settlement is Central Park / KNYC.
Rejected trades matter too — they show whether our filters are working.
Hypothetical trade ideas only: fair value vs current Kalshi entry price.
NYC-only operating sheet for every KXHIGHNY / KNYC high-temperature contract we are watching today. This is the clean table Goose uses to decide paper trade, watch, or reject.
The automation filters to KXHIGHNY and official Central Park / KNYC settlement. Other large weather markets stay out unless we later prove that adding them improves expected value.
The dashboard data feed is refreshed by Hermes cron and can also be refreshed manually by Goose before we make decisions. No real orders are placed.
Bid/ask, fair value, edge, decision, and close time for the current NYC weather board.
Paper-trade ledger, rejected-trade learning, P&L, forecast accuracy, and post-mortems.
Read-only test against settled KXHIGHNY markets and Kalshi candlestick prices. This helps us improve before risking real money.
Backtest output tracks forecast error and settled-market P&L. Next improvement is adding official NWS station observations directly.
Track every idea, including losers and rejected trades. If the ledger does not show durable edge after enough samples, we do not scale.
Dedicated operating view for every automation, job, and recommendation connected to the NYC weather trading project.
The system only promotes a market when data, model, risk, and journal checks all pass.
Henry is the CEO. Goose commands the agent team, reviews their work, and brings only decision-ready items to Henry for approval.
The system is built around human approval. Agents can research, draft, organize, and recommend. Goose reviews. Henry approves what becomes action.
Each agent has one lane. They prepare work; Goose reviews; Henry approves.
Anything meaningful passes through this queue before action.
The default path for every mission: request, assign, work, Goose review, CEO approval, complete.
Start practical: research, property data, database, documents, underwriting, and monitoring.