Fish Where the Whales Are — Pitch Narrative (Internal)

Concentrate development effort on the few funders who can write the biggest aligned checks, and design each ask to their pattern at maximum plausible size.

Beat 1 — The hook

“Most fundraising is done fishing with a wide net in a whale ocean.” Fundraising effort is spread widely. Money isn’t. Funding obeys a power law, and the biggest checks come from a few hundred hands.

Beat 2 — The shape of the money (the numbers slide)

“$617 billion a year, concentrated in a tenth of a percent of hands — with a $124 trillion wave behind it.”

• The pool is at a record. U.S. charitable giving hit $617.2B in 2025 — crossing $600B for the first time (+5.7% current dollars, +3.0% after inflation). ¹
• The concentration is radical. Of 120,000 U.S. foundations, grantmakers giving $50M+ are just 0.1% of funders — yet they supply 40% of all grant dollars; ² the largest 1,000 (1% of funders) account for roughly half to 60% of tracked foundation giving. ³ The Gates Foundation — the largest U.S. private foundation — alone paid out $8.0B in 2024; ⁴ marquee grantmakers like Mellon ($540M in 2024 grants) ⁵ and Robert Wood Johnson ($550M/yr) ⁶ each move over half a billion annually.
• The wave got bigger. Cerulli now projects $124T changing hands through 2048 in the Great Wealth Transfer — with ~$18T destined for charity. ⁷
• The whales are multiplying. 556,850 ultra-high-net-worth individuals ($30M+) held $63.8T globally in 2025, and the U.S. is home to ~37% of them — roughly 206,000 people; ⁸ global HNWI wealth reached a record $98.3T (Capgemini). ⁹ World figures — labeled as such on the slide.

All figures verified against primary sources 2026-07-28. Corrections from verification: the June draft’s Mellon $302M / RWJ $293M were ~2015-era numbers on an undated aggregator page — the single most dangerous figures in the deck for a foundation-literate audience; Giving USA, Cerulli, and Altrata all had newer editions than the draft cited; and the $98.3T belongs to Capgemini’s investable-assets series, not Altrata’s net-worth counts (the two must never be mixed).

(seek chart: the power-law curve — foundations ranked by annual grantmaking, log scale, with “where effort goes today” vs “where dollars are” annotated)

Beat 3 — The method (the doctrine slide)

“The 990 tells you what they funded. The call tells you why. The pattern tells you what to ask for — and how big.”

1. Study the public footprint — 990s for actual grantmaking history, ¹⁰ Candid/press/principals’ statements for strategy and values. ¹¹
2. Get the intro call — learn the thesis behind the checks.
3. Pattern-recognize — the cause, geography, stage, and outcome they keep paying for.
4. Align to the sweet spot — design the ask to the largest amount that still fits their pattern. Start from what they want to give; shape the program to match.

Beat 4 — It already worked (the receipts slide)

“The campaign’s anchors are reverse-engineering receipts: Carnegie’s pattern said Delta, so the ask said Delta — and $2M landed.”

Carnegie Corporation’s $2M anchors the Delta expansion; Schusterman’s $1M followed; $6M of $25M is committed with ~$3M more in motion and an August 2026 founding-cohort close. ^{12 13} Each landed where the funder’s existing pattern and Reach’s work overlap — not from a generic application.

Beat 5 — The whale map is already drawn (OVERWHELM: the target slide)

“The mega-gifts research is a reverse-engineered map: 84 verified gifts, every funder’s revealed pattern, sized and dated.”

What the map shows, by tier:

• Pattern-proven, in-market now: Ballmer Group (largest private funder of alternative teacher prep; $40M residency renewal) ¹⁴ · Ascendium ($172M/yr, rural learner success named) ¹⁵ · Bloomberg ($570M cumulative CTE, now granting directly to colleges) ^{16 17} · Walton (Strategy 2030 aimed at the Delta) ¹⁸ · Arnold Ventures (largest-ever Maricopa completion grant) ¹⁷ · Lumina (Goal 2040 metric = Reach’s outcomes). ¹⁹
• Dated windows: Humanity AI $10M open call (summer 2026); ²⁰ OpenAI $50M unrestricted (July 2026); ²¹ BlackRock’s $25M RFP via JFF. ²²
• Unsolicitable but screen-matched: MacKenzie Scott — $7.2B year, ²³ $1.1B+ to access institutions exactly like Reach ²⁴ — the play is public legibility and clean outcomes data, not an application.
• The whale thesis in one line: billion-dollar debt-free-degree checks exist (Gottesman, ²⁵ Bloomberg/Hopkins ²⁶) — but only in medicine. The pattern-matched mega-ask for undergraduate working adults has never been made. Someone will make it first.

(seek chart: capacity × alignment scatter — every scanned funder plotted, top-right quadrant labeled “spend the hours here”)

Beat 6 — The engine (the operationalization slide)

“Reverse-engineering is the strategy. The corpus + agents are the engine.”

The reach-edu funder corpus (500+ documents across 57 funders, now with per-strategy funding datasets and a 150-source citation registry) plus the [[agent-workflow-maxxing]] doctrine make studying many funders’ footprints tractable for a small team. The mega-gifts scan — 84 verified gifts in an afternoon — is the throughput proof.

Beat 7 — The ask (internal decision)

“Rank every prospect by capacity × alignment. Spend the team’s hours on the top ten. Size every ask to the pattern’s maximum.”

Concretely: adopt the tiered map from Beat 5 as the working pipeline; assign the intro-call push to the pattern-proven tier before the August cohort close; ¹² submit into every dated window that clears the alignment bar; and draft the first pattern-matched mega-ask (the medicine-precedent, debt-free-degree framing) for the one funder whose pattern it fits best.

Beat 8 — Close

“A few precise asks beat a hundred generic ones. The map is drawn — now fish where the whales are.”

Citations