Cognitive Trader · v0.9.4 · Private beta
Building in public

Deterministic Momentum.
Agentic Reflection.

A high-integrity trading architecture where hard rules pick the direction and an LLM-driven memory layer judges every execution—learning from every win and every scar.

Figure 1. Live cycle output, sanitized ~/cognitive-trader
cycle 4218 — local
Bring your own API keys
Runs offline · Logs stay local
Flat $129/yr · No success fee
14-day trial
Not for beginners — know your risk
§01 — Architecture

Why this isn't just another trading bot.

Most "AI trading bots" are a webhook and a prompt. Cognitive Trader is a full agentic architecture — built so the LLM never decides direction, only learns from outcomes.

Source Telegram Stream Binance API FAST_MODEL PreClassifier 45s Guard Analysis Momentum Decision Engine COGNITIVE CYCLE Calibration Dreaming Vector RAG W2 Memory Two-Key Gate Risk Engine MDD & Sizing ACT Persistent Storage Postgres + pgvector TTL: 45s VETO KILLSWITCH: -$500
01 / Logic Gate Deterministic

Two-Key Confirmation

No ACT fires without signal alignment. The rules engine computes market_direction via sign(24h_change_pct) (threshold 1.5%) while the LLM provides thesis_confirmation. If trading_goal (0.50) isn't paired with market momentum (0.70), the Go-side gate blocks execution. Defense in depth.

02 / Memory Wires Agentic

Dual-Wire Learning

W1: Manual fact extraction on trade close (source_channel='trade_outcome'). W2: Vector similarity retrieval via Ollama nomic-embed-text. The agent retrieves the 5 most-similar past trades into the prompt context. It doesn't just "remember"—it performs local RAG on its own historical scars.

03 / Risk Control Critical

MDD Killswitch

A hard-coded circuit breaker in the cognitive_cycle. If 24h PnL (excluding pnl_unknown) breaches -$500, the system enters lockdown. It automatically cancels orphan STOP_MARKET and TAKE_PROFIT algo orders via the Binance API. No human cleanup required.

04 / Calibration Adaptive

Behavioral Policy

The ActionThreshold is dynamic (range 0.35–0.85). Every cycle, the lifecycle engine runs CalibrateFromOutcomes, adjusting weights based on a 30-day rolling PnL window. Realized profits tighten the threshold; the agent earns its right to be aggressive.

05 / Reflection Dreaming

Nightly Dreaming

At 23:00 daily, the agent processes the day's internal_monologue and paper_trades. It generates dream_insights that are injected into the next day's working memory. This is where "curiosity-driven" parameters like intrinsic_motivation are calibrated offline.

06 / Data Integrity Freshness

45s Freshness Guard

In volatile regimes, anchoring on stale prices is fatal. If all prices in the market_stats feed are >45s old, the system enters Manage-Only mode. It will close or adjust existing positions but strictly blocks new opens. Real-world safety for live futures.

// supporting evidence · BYO-keys
  Typical "AI trading" SaaS Cognitive Trader
Custody Custodied or "read + trade" delegated. Your keys. Never leave your machine.
Inference cost Their cloud, per-call pricing. Local LLM via Ollama (optional). SearXNG for news. Zero spend.
Decision logic Black box. Strategy is "trust us." Rules-engine direction. Source-readable supporting stack.
Fees % of AUM or % of P&L. Flat $129/yr early-adopter. No skim.
§02 — Honest framing

What this system actually is (and isn't).

There is a lot of dishonest marketing in algo trading. We'd rather lose the sale than oversell. Here's the straight version.

It is— affirmative
  • A local-first agent that runs the same loop forever: scan, decide, execute, reflect, remember.
  • A memory layer that turns every closed position into a labelled lesson the next cycle can read.
  • Disciplined risk: hard stops, position sizing, regime-aware throttling — all configurable.
  • A serious tool for traders who already understand what they're doing and want their process automated.
It is not— negation
  • ×A money printer. There is no guaranteed edge and we will not pretend otherwise.
  • ×A signal service. You don't subscribe to calls — the agent decides and acts on your venue.
  • ×A black-box LLM trading hype machine. The model is a small piece. Most of the system is plain code.
  • ×Appropriate for someone still learning what a stop-loss is. Sit this one out.
§03 — The memory loop

Why this is different.

Most bots forget. Every cycle starts from zero — same indicators, same heuristics, same mistakes.

Cognitive Trader writes a short lesson at the end of every closed position: what the regime looked like, what the agent thought, what actually happened. Those lessons are indexed and fed back as context on the next decision. The bot doesn't just trade — it builds an internal book of what worked here last time.

This is the layer worth paying for.

Figure 2. Lesson entry, post-trade (inferred) memory/lesson_2842.md
symbolETHUSDT
sideSHORT
entry / exit3,182.40 → 3,247.10
pnl−0.81 R
regimeRANGING (ADX 14.2)
thesislower-high break, news beta neg

Shorted ETHUSDT into a ranging regime on a "break of structure" that wasn't. ADX was below 18 the whole session. Don't trade trend-continuation logic when the classifier flags RANGING — wait for ADX > 22 or sit out. Next time this pattern shows in RANGING, skip.

§05 — What ships

What's in the box.

Three things: the binary that does the work, the supporting stack it talks to, and the parts you bring yourself.

01 / Core Logic
Autonomous Binary
  • Cognitive Cycle: Background loop enforcing a 15-minute STAY_SILENT vs ACT decision cadence.
  • Two-Key Gate: Mandatory signal alignment—LLM thesis MUST pair with deterministic rules-engine momentum.
  • Risk Engine: Hard-coded 1:2 R/R auto-targets and 5% sanity-capped stops (validation-side).
  • MDD Killswitch: Active 24h PnL monitoring halts new opens at -$500.
02 / Persistence Stack
Self-Hosted Infra
  • Vector Store: SQLite + FAISS for persistent RAG-based memory retrieval (Wire 2).
  • Data Stream: Binance USDT-M futures integration (paper & live) with algo order ID tracking.
  • Local Inference: Ollama integration for nomic-embed-text embeddings and local model fallback.
  • High-Integrity Ledger: Postgres backend for every conversation, internal thought, and trade audit.
03 / Operating Rails
System Parameters
  • Action Threshold: Adaptive 0.35–0.85 (PnL-weighted calibration).
  • Signal Weights: 0.50 (goal) to 0.90 (contradiction) priority scale.
  • Freshness Guard: 45s hard timeout on market data inputs.
  • Readiness Gates: Explicitly moving through Gate 5 (Profitability) logic.
Backtest runs

Every run. Every verdict.

One JSON file per run. Fully versioned in git. Click a row to see the full breakdown — config, results, regime splits, and the honest notes on why it lived or died.

§06 — Pricing

Buy in early. Or wait.

Early-adopter pricing — while we're still finding the bugs. Price goes up at 1.0.

Early Adopter · Building in public

Buy now. Build with us.

$129 / YEAR $199
  • Lifetime access at $129/yr — never re-priced for you
  • Private Discord with the maintainers · direct line to dev
  • Vote on the next strategy module
  • Every weekly build, every honest bug post, in your inbox
  • 14-day refund, no questions
Claim early-adopter price Buy now — $129/yr

Locks in $129/yr as long as you keep your subscription active. You're buying a seat on the build, not a finished product.

Software is provided as-is. You are responsible for your trades. Numbers above are hypothetical performance examples, not forecasts. Not financial advice.

§07 — FAQ

Questions we get asked.

Replace these four entries with the FAQ verbatim from the one-pager.

Talk to us first.

We're building in public. The Discord is where the work happens — strategy notes, regime-classifier tweaks, beta drops. Email comes later, once there's something to send.

C
Cognitive Trader 1,247 online · 4,892 members
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