“AI trading journal” is a product category, not a standard capability. Some products use language models to summarize notes or suggest categories. Others use deterministic calculations and market the overall experience as AI. Evaluate the exact input, output, privacy boundary, and verification step instead of relying on the label.
What AI May Be Used For
- summarizing a batch of written notes;
- suggesting tags for later review;
- grouping similar language or stated setup names;
- drafting questions about repeated process deviations.
These outputs can be incomplete or wrong. A model cannot recover missing fills, know an unwritten plan, or determine causation from a short history. Suggested tags should remain editable and traceable to the source records.
Keep Calculations Deterministic
P&L, fees, position size, holding time, and R-multiples should come from inspectable arithmetic applied to validated records. Language-model output should not silently change those values. Imported trades need symbol, timestamp, side, quantity, and fill validation before any summary is trusted.
Protect Sensitive Records
Before sending notes or trade history to an AI provider, review data retention, training, deletion, access, and export policies. Remove account numbers, credentials, and unrelated personal information. A journal should explain whether processing occurs locally, through the product’s server, or at a third-party model provider.
Separate Description From Advice
A generated statement such as “late entries appeared in this sample” is a review prompt, not proof of a behavioral cause or a recommendation for the next trade. Require links back to the underlying records, keep sample size visible, and verify the statement before turning it into a rule.
Evaluate the Category Honestly
Ask whether the AI output adds something beyond filters, grouping, and deterministic flags. Check how the product handles missing data, conflicting notes, edits, deletion, and unsupported claims. More fluent language is not the same as stronger evidence.
What MAC Terminal Does Today
MAC Terminal’s current Journal imports supported CSV or pasted fills and calculates P&L, win rate, R-multiples, time-of-day breakdowns, and rule-based behavior flags. It does not generate personalized AI feedback from journal notes. MAC Terminal’s AI-labeled workspace contains scheduled shared market analysis and themes, separate from member Journal review.
Educational only. AI output can be inaccurate and should not be treated as individualized trading, financial, psychological, tax, or legal advice.