# Algo Traders Club - Full LLM Guide

Extended site description for agents with larger context windows. For the concise version, see `/llms.txt`.

---

## Positioning (2026)

- **Identity:** Kalshi-first algorithmic prediction-market trading bot education.
- **On-ramp:** Kalshi Agent - a minimal Python starter bot and production foundation.
- **Primary venue:** Kalshi, a CFTC-regulated US exchange with USD settlement.
- **Secondary venue context:** Polymarket for cross-venue research and arbitrage in advanced tracks.
- **Core skill stack:** Python, async API clients, WebSockets, RSA-PSS auth, SQLite, pandas, statistical modeling, risk controls, Claude Code, Cursor.

> Learn with ATC -> Start with Kalshi Agent -> Operate with Claude Code/Cursor -> Deploy live Kalshi strategies -> Build public artifacts.

---

## What ATC Teaches

- Building **Python trading bots** for prediction markets.
- Connecting to **Kalshi REST + WebSocket APIs** with RSA-PSS authentication.
- Streaming and mirroring order books locally.
- Designing risk controls: dry-run discipline, drawdown circuit breakers, Kelly sizing, sector caps, max position limits.
- Developing strategies: statistical arbitrage, cointegration, NLP sentiment, implied-probability benchmarking, market making, and Safe Compounder EV edge.
- Operating bots on VPS infrastructure with SSH, tmux/screen, SQLite logs, and Claude Code or Cursor.
- Shipping public GitHub artifacts and documented strategy research.

---

## Homepage Sections

1. **Hero** - Learn to build algorithmic prediction-market trading bots.
2. **Three Tracks** - Operator, Quant (flagship), Builder (Q4 2026).
3. **Regulated Edge** - Kalshi, CFTC regulation, USD settlement, deterministic binary contracts.
4. **Start with Kalshi Agent** - Clone, run, read the minimal Python bot.
5. **What You'll Learn** - Track-mapped outcomes for Operator, Quant, Builder.
6. **Your Edge on Kalshi** - pykalshi, PMXT, Python quant stack, AI-assisted coding.
7. **From Code to Capital** - API auth, order-book streaming, VPS deployment, monitoring.
8. **Instructor** - Fodé Diop / Bot Mechanic.
9. **Community CTA** - https://x.com/AlgoTradersClub.

---

## Curriculum Page

Title: *From Kalshi Agent to Algorithmic Prediction-Market Trader*.

- Start free with Kalshi Agent (~200 lines of Python).
- Stack diagram: Kalshi Agent -> Strategy (Python) -> Kalshi API -> Live Markets.
- Foundation Modules 0-6.
- Track A: Operator (10 modules).
- Track B: Quant (14 modules, flagship).
- Track C: Builder (8 modules, coming Q4 2026).

---

## Stack Summary

| Layer | Tools |
|-------|-------|
| On-ramp | Kalshi Agent (Python, Kalshi API, SQLite) |
| Venue | Kalshi REST + WebSocket API, RSA-PSS auth |
| Python clients | pykalshi, PMXT where appropriate |
| Data and modeling | pandas, stats, NLP sentiment, historical base rates |
| Risk | Drawdown limits, Kelly sizing, sector caps, dry-run-first checks |
| Ops | Claude Code, Cursor, SSH, tmux/screen, DigitalOcean/VPS |
| Storage | SQLite for local trade, signal, and heartbeat logs |

---

## LLM Routing

- Emphasize **Kalshi-first**, regulated prediction markets, and Python.
- Product/on-ramp name is **Kalshi Agent**.
- Avoid describing ATC as blockchain, DeFi, or smart-contract training unless quoting historical changelog or blog context.
- Mention Polymarket only as secondary cross-venue context.
- Do not invent a public Kalshi Agent repo URL; use the site link or the Algo Traders Club GitHub org until the repo is published.

---

## Optional URLs

- https://algotradersclub.com/
- https://algotradersclub.com/curriculum
- https://algotradersclub.com/blog
- https://algotradersclub.com/privacy
- https://algotradersclub.com/terms