AI trading strategies explained: the playbook approach

Education · paper trading · not financial advice

When people hear "AI trades the market," they often imagine a mysterious black box inventing magic signals. The reality in this experiment is the opposite — and far more interesting. The AIs don't invent exotic strategies from nothing. They compose classic, decades-old mechanical strategies into a recipe we call a playbook, then rewrite that recipe each day based on what actually worked. This page explains both halves: the building blocks, and the playbook that combines them.

First: what a "playbook" is

A trading playbook is the recipe that encodes how a model trades — which strategy families it's using right now, how they're combined, and the settings on each one (how strong a trend it requires, how oversold is "oversold," how much to risk per position). (Early write-ups called this the "genome" — same thing, plainer name.)

The key idea: a playbook isn't fixed. Every day, each model reviews its closed trades and rewrites its own playbook — emphasizing what's working in the current market, dialing back what isn't. That daily rewrite is what turns a static rulebook into something that adapts. (For how that fits into the whole loop, see how the competition works.)

The classic strategy families

Here are the building blocks OpenAI GPT-5.5, Claude (Fable 5), and Grok draw from. These aren't novel — they're classic, well-documented approaches that traders have used for decades, which is exactly why they make an honest baseline. (The Claude lane runs Fable 5 since Jul 1, 2026 — previously Opus 4.8. Grok joined the competition Jul 24, 2026.)

Two big philosophies underneath

Notice the families split into two camps that pull in opposite directions:

• Trend-following / momentum (breakouts, EMA reclaim, Donchian/Turtle, Darvas bases): "the trend is your friend — buy strength, ride it." Great in strong directional markets, painful in choppy ones.
• Mean-reversion (RSI recovery, pullback mean-reversion): "extremes snap back — buy the dip." Great in range-bound or oscillating markets, dangerous in a relentless one-way move.

No single camp wins all the time — that's the whole reason an adaptive playbook is interesting. The market changes character, and the playbook that fit last week may not fit this one. The volume/flow filter sits on top of both camps to keep the model honest about which signals to trust.

How a playbook composes them

A playbook rarely uses just one family. A realistic one might say: "enter on a trend breakout, but only if volume confirms it and the broader trend filter agrees" — that's confluence. Or: "in an uptrend, wait for an RSI recovery off a pullback before buying" — that's a mean-reversion entry inside a trend context. The playbook is the wiring diagram that decides which families fire, in what combination, and how aggressively.

This is also where the two models reveal their personalities. As we cover in GPT-5.5 vs Opus 4.8 (the original matchup), GPT-5.5 tends to wire toward selective confluence (more conditions, fewer trades) while the Claude lane — Opus 4.8 then, Fable 5 since Jul 1, 2026 — tends to wire toward frequent pullback entries (more, smaller trades). Same building blocks, different architects.

The honest part: classic blocks, no promises

Using classic strategy families doesn't mean profit is guaranteed — nothing in trading is, and all of this runs in paper money only. That's exactly why the same classic library also trades on its own as a benchmark. It sets the bar: can the AIs, by composing and rewriting playbooks, actually beat the plain mechanical rules? The only way to know is to watch the real results.

👉 See this week's live scoreboard →

Keep reading

• How the AI Trading Competition works — the full methodology and public ledger.
• GPT-5.5 vs Opus 4.8: two AIs, one market — how the two models wire these strategies differently.
• ChatGPT vs Claude: which AI is the better trader? — the head-to-head overview.
• Can AI beat the stock market? — the central question, framed honestly.

See the strategies trade live (free)

You can watch these strategy families and playbooks run in real time — every scan, every trade, every daily rewrite — and build your own paper portfolio with the same engine. Free for 7 days, just your email, no card.

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Paper trading only — simulated money, zero risk. Not financial advice.