AI Trading Coaching: What It Can and Cannot Tell You

Educational guide. Examples and named scenarios are illustrative, not verified customer results or research findings. Journal patterns describe recorded history; they do not establish causation or predict returns.

What AI coaching can do

AI can help summarise available journal evidence and suggest questions for a review. Check any conclusion against the contributing trades, sample size and data coverage.

What it cannot establish

A pattern does not prove a cause. Notes can be incomplete or ambiguous, and AI can misinterpret them. A profitable historical group does not guarantee future returns. AI review is not continuous market supervision or a substitute for your own trading decisions.

Combine the tools that suit your review

CybillAI includes private mentor workspaces for accepted connections with explicitly selected records and revocable access. Human feedback and AI assistance can support different parts of a review; neither guarantees performance.

Start with the evidence

Import or record your trades, then check net realised P&L, average winners and losers, fees, timestamps and sample sizes. Open positions and practice results should be read separately. A high win rate can still accompany a loss.

Review one practical focus

CybillAI offers automatic saved-data tags, Discipline Review, weekly review tools and progress tracking. Behaviour tags are candidates to investigate, not proof of a mistake. Choose one focus and compare subsequent recorded outcomes with its starting baseline.

Understand the plan and data limits

The Free plan allows up to 30 saved trades. Pro is US$37/month or US$360/year and adds AI coaching conversations, visual playbooks, performance comparisons and backtesting/replay practice. TradingView webhook analysis requires Pro + Realtime Trade Analysis. Broker and market-data coverage varies. Historical R requires the original risk in the reporting currency.

See current pricing · Read the user guide