PromptSharp › Daily briefs › Finance › August 10, 2026

Finance prompt of the day

August 10, 2026 · for Investment banking, sales & trading, equity research, FP&A. One sharp, copy-paste prompt — free, every weekday.

You are an analyst interpreting a 13F filing for [MANAGER]. I will paste the holdings/changes. Produce:
1. The notable NEW positions, ADDS, TRIMS, and EXITS in a TABLE (name, action, approx position size or % change as provided).
2. The apparent THEMES or rotations the changes suggest (sector, factor, size).
3. The CAVEATS that limit the read: 45-day lag, longs-only (no shorts/derivatives/cash), possible hedges, and quarter-end window dressing.
4. Which 1-2 changes are worth your own diligence and why — not to copy, but to investigate.
Use only the holdings I provide; do not infer conviction or intent beyond what the data supports.

Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it. Mark every claim I should verify externally before relying on it. Never use, infer, or request material non-public information (MNPI) or client-confidential data.

What changed for Finance

How to run “13F holdings-change interpretation”, step by step

The situation this prompt is built for: A manager's 13F dropped and you want the signal, with the well-known caveats front of mind. Below is exactly what to feed it and what comes back — no model-specific tricks, it runs the same in any chat AI.

What each placeholder does

Demo profile for the example fills: a equity research associate on a mid-cap sector coverage team, working in Excel, a chat AI model, and your firm's data terminal. Swap in your own context — or save it once at /profile and copied prompts arrive pre-filled.

• [MANAGER] — this is the input the whole output quality hangs on. Demo fill: your own manager — one or two concrete lines beats a paragraph of vague context. Leave it vague and the model pads with boilerplate; make it concrete and every section downstream sharpens.

What the model hands back

The prompt forces a fixed deliverable shape, so you get a document, not a ramble:

1. The notable NEW positions, ADDS, TRIMS, and EXITS in a TABLE (name, action, approx position size or % change as provided).
2. The apparent THEMES or rotations the changes suggest (sector, factor, size).
3. The CAVEATS that limit the read: 45-day lag, longs-only (no shorts/derivatives/cash), possible hedges, and quarter-end window dressing.
4. Which 1-2 changes are worth your own diligence and why — not to copy, but to investigate.

Why this structure works

13F reads are valuable only with the lag/longs-only caveats attached; separating the observable changes from unfounded intent-reading, and framing them as leads to investigate rather than signals to copy, is the honest use of the data.

On Pro, the manager set and the themes you care about are pre-filtered to your coverage and strategy, so the 13F read surfaces the rotations relevant to your book from your profile.

When to use it — and when not to

Reach for it when

• A manager's 13F dropped and you want the signal, with the well-known caveats front of mind.
• You can actually supply the inputs it asks for ([MANAGER]) — this prompt is an amplifier for real context, not a substitute for it.
• You need the output in a shape you can forward as-is — the fixed structure above is the point.

Skip it when

• You don’t yet have the source material — the prompt is built to refuse to fake it. Its own guardrail: “Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it.” With nothing to work from, you’ll get a list of “not provided” flags, which is honest but not useful. Collect the inputs first.
• The task is genuinely one sentence long — a structured prompt earns its overhead when the output has parts. For quick one-off questions, just ask.

Adapting today’s prompt for adjacent roles

“13F holdings-change interpretation” sits in the Investment Management lane of the finance pool. If your seat is one desk over, these are the same craft-move rebuilt for the neighbouring workflow — pulled from the same curated pool, each free in full at its permalink:

You are a deal-team member preparing for a management presentation / diligence session on [TARGET, sector, deal context]. Produce a QUESTION BANK organized by theme: 1.…

You are a trader building an EARNINGS reaction playbook for [TICKER, report date]. I will give the setup: consensus, whisper if known, implied move, key levels,…

You are an analyst assessing value creation for [COMPANY]. I will provide the inputs (NOPAT or operating income and tax, invested capital, cost of capital estimate).…

Common failure modes (and the fixes)

• Failure: letting the model drift past the prompt’s own guardrail — “Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it.” Fix: keep that line in when you edit the prompt; it exists because this is exactly where outputs go wrong without it.
• Failure: letting the model drift past the prompt’s own guardrail — “Mark every claim I should verify externally before relying on it.” Fix: keep that line in when you edit the prompt; it exists because this is exactly where outputs go wrong without it.
• Failure: letting the model drift past the prompt’s own guardrail — “Never use, infer, or request material non-public information (MNPI) or client-confidential data.” Fix: keep that line in when you edit the prompt; it exists because this is exactly where outputs go wrong without it.
• Failure: filling [MANAGER] with a vague summary. The output can only be as specific as this input — generic context in, generic deliverable out. Fix: paste raw specifics (real names, real numbers, real constraints), then trim the model’s output, not your input.
• Failure: accepting the first pass. Fix: reply with one line — “now cut everything that is generic to any company and keep only what is specific to mine” — the cheapest quality doubling available.

Where AI is landing for investment banking right now

Context for today’s prompt, from the same screened sources the daily brief reads. Our read, with sources linked — the pattern across items like these is consistent: the professionals getting leverage from AI are the ones feeding it real working context, which is exactly the muscle today’s prompt trains.

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• [Lenny's Podcast] The playbook for building high talent density teams | Adam Ward, Head of Talent at Cursor (podcast) — Adam Ward is the Head of Talent at Cursor, one of the fastest-growing developer tools in history. Before joining Cursor, he founded Growth by Design, an independent recruiting…

Quick answers

Is “13F holdings-change interpretation” free to use?

Yes — every weekday issue of the PromptSharp Finance publishes one full pool prompt free on the web, and it stays free in the archive. Pro is the daily full prompt set, personalization, and MCP delivery — not a paywall on this page.

Which AI model does this prompt work with?

Any of them. Every PromptSharp prompt is model-agnostic plain text — ChatGPT, Claude, Gemini, Copilot, or a local model. No plugins, no custom GPTs; paste and run.

How is the finance prompt of the day chosen?

Deterministic rotation over the curated finance pool — currently 75 prompts across 5 sections — the same single source the paid brief reads. Same date, same prompt: the archive never silently changes under you.

What goes in the [BRACKETED] placeholders?

Your context — the walkthrough above covers each one. The short rule: the more concrete the fill (real names, numbers, constraints), the sharper the output. Save your details once at /profile and web copies arrive pre-filled.

How do I get this in my inbox instead?

The capture form above — PromptSharp Finance status is honest: live briefs send every weekday; pre-launch verticals email their free list the day the email edition starts.

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