AI & Trading
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Workflows, prompts, guardrails
Updated weekly
AI, for traders.
Workflows, prompts, and honest takes. No predictions, no signals, no magic. Just how serious traders use AI in 2026, with the limits stated up front.
Three core workflows
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Tested daily
All levels
N° 01
Claude Projects
The pre-market brief.
Set up a Claude Project with your trading style, instruments, and risk parameters as system context. Each morning, paste overnight news, your watchlist, and yesterday’s P&L. Get a one-page brief: what changed, three setups with invalidation, the risk you might be missing. The model uses your context, not a stranger’s.
Beginner · Intermediate
15 min one-time setup
N° 02
Claude Sonnet
The journal auditor.
Log every trade as structured CSV: setup, entry, exit, R-multiple, emotion, mistake. At week end, paste the file. Ask for the three repeating patterns ranked by impact on R. The model surfaces leaks the eye misses in 40+ rows. Useful for pattern detection. Not a substitute for live coaching.
Intermediate · Advanced
15 min weekly
N° 03
Perplexity Pro
The setup memory.
Before any new position, ask Perplexity (with sources enabled): “Find the last five times this setup occurred in the past ten years.” You get cited cases with dates, outcomes, drawdowns, sources. Cuts recency bias. Forces a base rate before conviction. Verify each source before trusting it.
Advanced
5 min per setup
Prompt library
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Copy, paste, adapt the bracketed parts
14 prompts · 4 categories
Structuring the open. What you set up before risk goes on.
Pre-market brief generator.
WHEN TO USE Thirty minutes before the open, after I have reviewed overnight data personally and need a synthesis I can act on, not a summary I have to re-read. ROLE You are a research analyst for a discretionary [futures / equities / FX] trader. You write structured briefs, not opinions, and you assume the inputs have been vetted by the trader. INPUTS I will paste below, in this order: 1. Watchlist: instrument, last close, ATR(14) 2. Overnight headlines and pre-market data I selected 3. Yesterday’s session summary: R outcome, win/loss count, key trades, mistake tags DELIVER, structured exactly as: 1) MATERIAL CHANGES For each instrument: what changed overnight that affects today’s structure, levels, or volatility. One line each. Fact only, no interpretation. If nothing material changed, write "no change". 2) THREE SETUPS The three setups in my playbook that match the changes above. For each: - Trigger condition (price level or pattern, observable) - Invalidation level (price where the thesis is wrong) - Regime context (the conditions under which this setup historically performs) - One yellow flag (the most likely reason this setup fails today given current context) 3) BLIND SPOT The one risk I am underestimating today, with the data point that justifies flagging it. If yesterday’s mistake tags suggest a recurring pattern, weight them here. CONSTRAINTS - No directional prediction. No price targets. No "I expect" or "likely to" language. - If a number is not in my inputs, mark it [unverified]. Do not search. - If you cannot ground a setup’s regime context in my inputs or in widely accepted reference data, write "no base rate data provided" rather than invent one. - No preamble. No closing summary. No motivational language. - Stop after section 3.
Session game plan.
WHEN TO USE At the desk, fifteen minutes before the open, when intent needs to become a written plan I can be held to. ROLE You convert messy pre-market notes into a structured session plan. You enforce discipline, you do not negotiate it. INPUTS 1. Instrument I trade today: [NQ / ES / CL / GC / FX pair] 2. My intended setups, in plain language 3. Max daily loss in R, max trades, remaining account drawdown 4. My recent state: tilt level, days since last loss-day, sleep last night (1-10) DELIVER, in this exact order: 1) GO / NO-GO CONDITIONS Three observable conditions that must be true at the open for me to trade. Each must be checkable in under thirty seconds. If any fail, I stand down. Examples of valid conditions: "ES above yesterday’s high before 9:35", "VIX cash below X", "no FOMC-week constraint active". 2) PRIMARY SETUP Restate my primary intent with: - Trigger - Invalidation - R-based target framework (1R / 2R / runner), not price-based - The single signal that says "do not take this trade today" 3) SECONDARY SETUP Same structure as PRIMARY. 4) HARD LIMITS - Max trades for the session - Max daily loss in R - No-trade hours (lunch, last 15 minutes, etc.) - Cooldown rule after a full-R loss CONSTRAINTS - Reformulate inputs. Do not invent setups not in the input. - No "high probability" language unless I provided base rate data. - If a condition is vague (e.g. "look for momentum"), ask one targeted question. Do not guess. - If my tilt level is 7+ or sleep is under 5, recommend reduced sizing in section 4 and flag it. - Stop after the hard limits.
Watchlist regime check.
WHEN TO USE Once a week, or after any session where the market did not behave like the regime I assumed it was in. ROLE You classify market regime. You do not predict it. INPUTS 1. My watchlist of instruments 2. For each, the following data: 5-day, 20-day, and YTD high/low. ATR(14). Last three closes. 50-day and 200-day SMA position (above/below). TASK Output one row per instrument with these columns and nothing else. | Instrument | Trend | Vol regime | Distance to 20D high (ATR) | Distance to 20D low (ATR) | Above 50/200 SMA | Notable | Definitions to apply: - Trend: uptrend (last close above 5D and 20D SMA, 20D SMA above 50D SMA), downtrend (inverse), range (anything else). - Vol regime: compressed (current ATR below 80% of its 60-day average), normal (80-120%), expanded (above 120%). - Notable: only flag the last three closes if a gap, outsized range, or failure occurred. Otherwise leave blank. CONSTRAINTS - One row per instrument. No commentary between rows. - No directional bias. No "looks bullish/bearish". No "could break out". - If a data point is missing, write "missing" in the cell. Do not extrapolate. - Apply the definitions above strictly. Do not introduce your own. - Stop after the table.
News release decoder.
WHEN TO USE Within ten minutes after a scheduled macro release (FOMC, NFP, CPI, ECB, etc.), when the market is reacting and I need structure before I react. ROLE You decode macroeconomic releases for a trader who already understands the instrument. You write structure, not interpretation. INPUTS 1. The release transcript or summary (paste below) 2. The previous release for the same event 3. Consensus estimate where applicable 4. The OIS-implied path before the release, if I provide it DELIVER, in this order: 1) WHAT CHANGED Every wording shift from the previous statement that carries policy or directional meaning. Format each as: - "Previous wording" -> "New wording" [section of the document] Cite verbatim. Do not paraphrase a shift and present it as a quote. If a shift is one word, the one word is enough. 2) BEAT / MISS / IN LINE For every numeric item: prior, consensus, actual, surprise (in % or basis points). Mark the direction of the surprise. If consensus was not provided for an item, write "no consensus provided". 3) MARKET-IMPLIED PATH Only if I provided the OIS data. State what is now priced for the next meeting versus before the release. Otherwise write "not provided". 4) WHAT TO IGNORE Phrases or numbers that look important but are boilerplate or noise. Be specific. CONSTRAINTS - Verbatim citations only. No paraphrase passed as a quote. - No predictions of post-release price action. No "this is hawkish/dovish". - If a section has no material content, write "no change worth flagging". - Stop after section 4.
Journal pattern auditor.
WHEN TO USE At the end of each trading week, with a clean CSV export of the week’s trades. Not for a single trade. Not on a losing day for emotional reasons. ROLE You audit trading journals as a quant performance reviewer, not a coach. DATA My trade log as CSV. Required columns: date, instrument, setup, entry, exit, stop, R-multiple, hold time, time of entry, emotion at entry (1-10), emotion at exit (1-10), mistake tag. If columns are missing, list which ones and proceed with what you have. TASK Surface the three repeating patterns I am not seeing on my own. Rank them by total R impact across the dataset, positive or negative. OUTPUT, one block per pattern: - Pattern name. Descriptive, one line. Example: "Late entries on third trade of the day". - Trades involved. List of dates and tickers. - Total R impact across these trades. - Frequency. How many trades match the pattern out of how many total. - The single behavioral or structural variable that links them. - One falsifiable question I should answer in next review to confirm or kill the pattern. CONSTRAINTS - Identification only. Do not propose strategy changes. - Do not invent emotions or context not in the CSV. - A pattern needs at least three matching trades. If fewer, do not report it. - If three supported patterns cannot be found, return only what is supported and say so. - Stop after the patterns. No conclusion.
Single-trade post-mortem.
WHEN TO USE Within thirty minutes of closing a trade that matters: a full-R loss, a full-R win taken poorly, a trade I broke rules on, or a trade I cannot explain. ROLE You debrief one trade as a senior desk-mate would, in writing, in five minutes. You are not my coach. You are not validating my decision. INPUTS 1. The trade: instrument, setup, entry, stop, exit, R-multiple, time in trade 2. The chart, described in text or as a screenshot 3. My note on context (regime, news, prior trades today) 4. My emotional state during the trade (1-10 scale at entry, peak stress, exit) DELIVER, in this exact order: 1) THESIS What I was trading, in one sentence. If unclear from my note, say "thesis unclear". 2) EXECUTION Was entry, sizing, and stop placement consistent with the thesis? Yes/no with one line of reasoning each. 3) PROCESS VS OUTCOME One of: "good trade, bad outcome" / "bad trade, good outcome" / "aligned" / "insufficient data". One line of justification. 4) MAE / MFE READ Given my emotional state, did I exit closer to MAE (max adverse excursion) or MFE (max favorable excursion)? What does that say about the exit decision in isolation? 5) ONE PATTERN Does this trade match a recurring tag in my journal? Name the tag. If unknown, write "not enough data". 6) ONE THING TO DO DIFFERENTLY Actionable, observable, testable next session. Not a feeling. A behavior. CONSTRAINTS - No moralizing. No "you should". Facts only. - If a section lacks data, write "insufficient data" and skip it. - Stop after section 6.
Weekly review structurer.
WHEN TO USE Saturday morning, with the week’s full trade log and session notes. Not Friday at 4pm. Distance matters. ROLE You structure a trader’s weekly review. You do not assess the trader. INPUTS 1. Full trade log for the week, as CSV 2. My free-text notes per session 3. My weekly process goals from last week, if any 4. My account state at week’s start and week’s end DELIVER: 1) NUMBERS Compute exactly, from the CSV: - Total trades, win rate, expectancy in R - Largest win, largest loss, both in R - Max consecutive losses - Average hold time of winners vs losers - Average emotion at entry on winners vs losers - Number of trades that violated stated risk parameters If a column is missing, write "missing column" and skip that line. 2) BEHAVIORAL FLAGS Patterns that appeared in three or more trades this week (oversizing, late entry, exit before stop, ignored playbook, etc.). Frequency only. No judgment. 3) GOAL DELTA For each weekly goal: met / partially met / missed. Cite the trades or sessions that demonstrate it. 4) FOCUS NEXT WEEK One process variable to track. Not a P&L target. Examples of valid focus: "log emotion at exit on every trade", "no third trade before reviewing the first two", "stop must be set before entry, not after". CONSTRAINTS - Compute numbers exactly. Do not approximate. - No new strategy suggestions. - No motivational language. No "great week" or "tough week" framing. - Stop after section 4.
Backtest honesty audit.
WHEN TO USE Before risking real capital on a backtested strategy. Or after one month live, when results diverge from the backtest by more than 20% on expectancy. ROLE You stress-test a backtest for hidden flaws. You assume the trader wants to find errors, not validate the system. You are the engineer hired to break it. INPUTS 1. Strategy rules: entry, exit, stop, sizing 2. Backtest results: win rate, expectancy in R, max drawdown, sample size, period covered, instruments tested 3. Data source and timeframe 4. Slippage and commission assumptions used in the backtest TASK Identify every plausible source of optimistic bias in this backtest. Rank by likely impact on real-world expectancy. FOR EACH FLAW: - Name (lookahead, survivorship, slippage absent, regime fit, sample too small, parameter optimization, instrument selection bias, etc.) - Evidence in the setup that suggests it is present - Estimated R impact per trade if corrected. State as a range (e.g. "-0.15R to -0.40R") and note the assumption that drives the range. Never give a single number unless it is computable from the inputs. - One concrete test to confirm or rule out the flaw (e.g. "walk-forward on out-of-sample 2018-2020", "re-run with 1.5 tick slippage") CONSTRAINTS - Do not validate the strategy under any circumstance. Adversarial only. - If sample size is under 100 trades, flag it first regardless of other findings. - If the backtest period covers less than two distinct regimes, flag it. - No "could potentially" hedge language. Either the flaw is plausible given the inputs, or it is not. - Stop after the ranked flaws.
Strategy devil’s advocate.
WHEN TO USE Before scaling a strategy in size. Before adding a new strategy to live capital. After any losing streak that feels longer than the backtest suggested possible. ROLE You are the senior risk manager whose job is to kill bad strategies before they go live. You owe me honesty, not validation. You have seen this fail before. INPUT My strategy below: rules, expected R per trade, expected frequency, drawdown tolerance, instruments, timeframe. TASK Build the strongest possible case that this strategy will underperform expectations in live trading. Cover, in this order: 1) MARKET STRUCTURE What changes in liquidity, regime, microstructure, or participant mix would degrade the edge? Be specific. Cite known regime shifts (volatility regimes, monetary policy regimes, microstructure changes) where relevant. 2) BEHAVIORAL DRIFT What trader-side errors will most likely creep in under this strategy’s specific demands: frequency, hold time, signal clarity, win rate, average loss size? Different strategies break traders in different ways. 3) FRAGILE ASSUMPTIONS The three assumptions whose failure would invalidate the strategy. For each: - The assumption stated explicitly - The data I would need to monitor that it still holds - The threshold at which I should treat it as broken 4) MAE / MFE REALITY CHECK If I provided backtest MAE and MFE distributions: compare them to what would be realistic with live slippage and emotional exits. If realized MAE is likely to exceed backtest MAE by more than 20%, flag the strategy as fragile to live execution. If I did not provide MAE/MFE data, say so and skip. 5) KILL CRITERIA The drawdown depth or win-rate decay at which I shut this strategy down. Defined in advance, in writing, not negotiable in the moment. CONSTRAINTS - Adversarial only. Do not offer encouragement or balance. - No predictions of market direction. - If a section has no genuine concern, write "no material concern" rather than filling. - Do not invent regime references or historical episodes you cannot ground. If a claim cannot be supported, omit it. - Stop after the kill criteria.
Drawdown recovery framework.
WHEN TO USE After a drawdown that crossed my pre-defined threshold. Not in the middle of a single bad session. Not after one losing trade. ROLE You help a trader build a recovery plan from a drawdown. You are not a therapist. You will not encourage me to "get it back". INPUTS 1. Current drawdown: in R, in % of starting capital, in days inside the drawdown 2. Last 10 trades with outcome, setup, and mistake tag 3. My normal risk per trade as % of account 4. My previous drawdowns of similar depth, if any (duration, cause, recovery time) DELIVER: 1) ROOT CAUSE Based on the last 10 trades, what is the dominant pattern? One of: sizing breakdown, tilt cascade, regime mismatch, strategy decay, randomness. One answer, with the trades as evidence. 2) RISK REDUCTION SCHEDULE Risk per trade for the next 20 trades, expressed as a fraction of my normal risk (e.g. 0.5x, 0.25x). Step-up rules: under what observable conditions do I return to 0.75x, then 1.0x? Conditions must be process-based (e.g. "after 10 consecutive trades following plan"), not outcome-based. 3) RE-ENTRY CONDITIONS Observable criteria before stepping back to full size. Examples of valid criteria: "R earned back to within 50% of starting", "5 consecutive A-grade setups executed cleanly regardless of outcome". 4) STOP-TRADING THRESHOLD The drawdown depth or session count at which the correct action is to flat-line and review with a coach or peer, not to keep trading. CONSTRAINTS - Do not suggest revenge-trade sizing or "win it back" framing under any circumstance. - If the data points to randomness rather than a fixable pattern, say so explicitly and recommend reducing risk anyway while it resolves. - No motivational closing. - Stop after the threshold.
Concept explainer with edge cases.
WHEN TO USE When I am about to apply a concept (volatility regime, base rate, expectancy, mean reversion, etc.) to a real decision and I want to verify I understand it the way it actually works, not the way it is taught on social media. ROLE You explain trading concepts to a working trader at [beginner / intermediate / advanced] level. The explanation will be used in real decisions, so accuracy matters more than elegance. INPUT The concept I want explained: [paste here]. My current understanding of it in one sentence (so you can identify where it is wrong): [paste here]. DELIVER: 1) WORKING DEFINITION One paragraph. No jargon unless defined inline. The definition a working trader would use, not a textbook one. 2) WHERE MY UNDERSTANDING IS CORRECT One paragraph, addressing my one-sentence understanding. 3) WHERE MY UNDERSTANDING IS INCOMPLETE OR WRONG One paragraph. Specific. 4) WHEN IT APPLIES The three contexts where this concept is the right framework. Each context as a one-line condition. 5) WHEN IT BREAKS The two contexts where applying this concept is actively misleading. Each as a one-line condition. 6) ONE FALSE ANALOGY A common metaphor used to teach this concept, and why it produces wrong intuition. 7) ONE TEST QUESTION A question an advanced trader could answer but a beginner could not. Provide the answer. CONSTRAINTS - No "it depends" answers without saying on what. - If you cannot verify a claim, mark it [unverified]. - No closing motivation. - Stop after the test question.
Setup historical comparator.
WHEN TO USE When I see a setup today that feels familiar and I want to compare it to historical analogues by structure, not by hope. ROLE You are a research analyst who pulls historical analogues for a trader. You compare structure, not outcomes. INPUTS 1. The setup I am looking at today: instrument, pattern description, market context, regime (trend/range, vol regime) 2. The lookback period I want covered (e.g. "last 5 years on this instrument") 3. The structural features I consider essential to the match (e.g. "must be at a 20-day high after compression") TASK Find the three closest structural analogues in the lookback. For each: - Date and instrument - Why it matches, by structure. Cite the structural features explicitly. - Macro context at the time of the analogue - How it resolved: actual outcome over the next N sessions, where N matches my intended holding period. Present this as information, not as guidance. - The one variable that was different from today. This is the most important field. DELIVER ALSO: - A summary line: "Of these three analogues, X resolved as expected, Y resolved against, Z was mixed." CONSTRAINTS - Past resolution is information, not a prediction. - Do not fabricate dates, prices, or outcomes. If you do not have verified data for the lookback period on this instrument, state "insufficient verified data for the requested lookback" and stop. A wrong analogue is worse than no analogue. - If you can ground only one or two structural matches, return only those and label clearly. - Do not suggest a trade or direction based on the analogues. - Stop after the summary line.
Asset class research brief.
WHEN TO USE Before adding a new instrument to my book. Not as casual reading. The output should be enough to know whether I can legitimately trade this instrument or whether I am gambling. ROLE You produce a one-page research brief on an asset class for a discretionary trader expanding scope. INPUTS 1. The asset class: [crude oil futures / gold futures / EUR/USD / 10Y Treasuries / etc.] 2. My existing experience with it: [none / some / proficient] 3. My base instrument (the one I trade today) for comparison DELIVER: 1) DRIVERS The three primary fundamental drivers of price in this asset, ranked by influence over a one-week horizon. For each, the data release or condition I should track and at what frequency. 2) STRUCTURE - Contract specs where relevant (tick size, point value, expiration, settlement) - Session hours and the two hours that account for most volume - Key correlation pairs (positive and negative), with rough correlation coefficients if known 3) REGIME MARKERS Observable conditions that signal which regime this asset is in (trending, range, news-driven, expansion vs compression). 4) PITFALLS The three errors traders coming from my base instrument most often make when starting here. Be specific to the cross-over (e.g. "ES traders entering CL often misjudge weekly inventory volatility"). 5) RESOURCES Three weekly sources to follow. Mainstream and verifiable only. CONSTRAINTS - If you cannot verify contract specs or session hours without source access, mark them [unverified]. - No directional opinion on the asset. - No "great opportunity" framing. - Stop after the resources.
Macro context synthesizer.
WHEN TO USE Once a week, ideally Sunday. The goal is to have one screen of macro context I can carry into next week without needing to re-derive it. ROLE You build a one-screen macro snapshot for a trader who needs context, not a thesis. You do not predict. INPUTS 1. The week’s released data: CPI, PCE, NFP, ECB, FOMC, retail sales, PMIs, etc. Headlines and prints. 2. Current rates: 2Y and 10Y yields. Week-on-week change in basis points. 3. DXY level and weekly change. WTI level and weekly change. Gold level and weekly change. 4. The instrument I trade and the two macro variables I track for it. DELIVER: 1) WEEK SUMMARY, IN FOUR LINES - Growth shift - Inflation shift - Labor shift - Policy-expectation shift One line each. Fact-based, no causation language. 2) RATES MAP - 2Y move in basis points - 10Y move in basis points - Curve shape change (steepening / flattening / parallel shift) with the basis-point number 3) CROSS-ASSET CONTEXT Weekly moves in DXY, oil, gold, and what they imply for liquidity and risk appetite. Avoid causal claims. Format: "DXY +X.X%, consistent with [observation about cross-asset], inconsistent with [other observation]". 4) RELEVANCE TO MY INSTRUMENT The one or two macro variables that, based on the data I provided and widely accepted reference relationships, drive my instrument right now. State what changed in those variables this week. If the linkage is contested or unstable, say so explicitly. CONSTRAINTS - No forward predictions. No "expect" or "should". - If a data point is not provided, write "not provided" and skip. - No geopolitical speculation. - Stop after section 4.
Honest note
No signals, no price prediction, no substitute for judgment. Verify every number outside the model.
Anatomy of a great prompt
N° 01
ROLE: You are a senior trader’s research analyst.
N° 02
CONTEXT: I will paste my overnight headlines, my watchlist, and yesterday’s P&L below.
N° 03
TASK: Deliver a one-page brief covering material changes, three setups, and the blind spot.
N° 04
FORMAT: Three numbered sections. Each setup with trigger, invalidation, and 1R sizing logic.
N° 05
CONSTRAINTS: No predictions. No hedge language. Mark unverified numbers as [unverified].
N° 06
VERIFICATION: Stop after the three sections. No closing summary.
What to build in
Six components of a working prompt
What to rule out
Six things AI doesn’t do well
N° 01
The role
Open with who the model is. “You are a research analyst for a futures trader” gets you a desk briefing. No role gets you a chatbot answer. One line, written like a job title.
01
Predicting price.
No model knows the next bar. Decades of quant research say direction is the hardest problem in finance, and a chatbot does not change that. Use it to prepare, never to predict.
N° 02
The context
Paste your actual material: watchlist, last session’s results, the headlines you read. The model only knows what is in the message. Thin context in, generic advice out.
02
Personalized financial advice.
The model does not know your account size, your open risk, or your tax situation. Whatever it suggests is general research. The decision, and the sizing, stay with you.
N° 03
The task
One verb, one deliverable, numbered. “List three setups with the price that proves each one wrong” works. “What do you think of the market” returns noise that sounds smart.
03
Critical math without a calculator.
Language models predict text, they do not compute. They will get a position size confidently wrong. Anything that touches capital goes through a calculator, every time.
N° 04
The format
Say what the answer should look like: a table, three sections, ten lines max. Without it you get long paragraphs you skim, and you miss the one number that mattered.
04
Citing fresh data without sources.
A model can state yesterday’s CPI with total confidence and be wrong. If there is no source link you can click, the number is unverified. For live data, use web-connected tools.
N° 05
The constraint
State what is off-limits. “No predictions. Flag any number you cannot verify as [unverified].” This is the line that turns the model from a salesman into an analyst.
05
Reading charts from images, precisely.
Show it a chart screenshot and it sees the shape, not the numbers. It will misread your levels by ticks or full points. Paste prices and levels as text instead.
N° 06
The verification
End with a stop. “Stop after section 3. No summary.” Models fill space by default. A hard stop keeps the output the length of your attention and makes the gaps visible.
06
Replacing a coach or accountability.
It can spot patterns in your journal, on the days you ask. It will not catch you oversizing at 9:31 or call you out after a losing week. Spotting a habit is not breaking it.
What we use, daily
01
Claude (Anthropic)
Long-context reasoning, journal pattern detection, document analysis. We use Claude Projects for persistent trader context and Claude Sonnet 4 for daily tasks. Default for anything that needs care.
02
Perplexity Pro
Live market research with cited sources. Anything that needs fresh data and traceable citations: setup base rates, news verification, asset class research.
03
ChatGPT
Brainstorm, quick rewrites, casual exploration. We use Custom GPTs for specific repeatable tasks. The tool we reach for when thinking out loud.
We pay for these subscriptions ourselves. No affiliate links, no sponsorship, no referral commission. We list them because they earn their place in the workflow. Nothing more.