Stanford Graduate School of Business · Case SI-193
Third Sphere:Impact in Transition
Stanford GSB published a case study on Third Sphere, the early-stage climate venture firm founded in 2013 by Shaun Abrahamson and Stonly Baptiste Blue. Written by lecturer Jaclyn Foroughi, it is the most thorough external account of how the firm works — its 13-year evolution from Urban Us, the rise of speedstrapping, its use of AI across investing and impact measurement, and the open question, raised by operating partner Miela Mayer, of how LPs evaluate climate impact in 2026.
Read the full case at Stanford GSB →
Explore the case ↓
Case author: Jaclyn Foroughi, CFA, CAIA · Published March 2026 · Copyright Stanford GSB
A companion to the case — not a copy of it.
We don’t host the case. Stanford owns it, and it available at the source. What follows is our own account of the five ideas the case is built around.
For well over a decade we approached climate investing by imagining a successful ten-year outcome first — how energy, transportation, or infrastructure might be reshaped — and then backing the startups capable of building it. We pursued the capital-intensive sectors most investors avoided primarily because we saw that most of that capital would not be on cap tables. That meant common concerns about dilution were overblown.
What is the “sci-fi version of impact”?
The most useful question in impact investing isn’t what is this company’s carbon footprint? or how much water does it use? It’s: if this company succeeds at scale, what does the world look like and how big is that delta? The first question is a snapshot in time and especially unuseful early on. The second measures whether the technology matters.
That framing led us to evaluate impact as a function of customer adoption and systems-level change, not internal ESG metrics. A startup building electric trucks has a modest direct footprint. The real impact is what happens when fleet operators replace diesel with their product and get to very high utilization rates of a much simpler drivetrain with fewer consumables (and therefore, less waste). We measure it the way you’d size a market — but the units are greenhouse gases avoided and people served.
What is speedstrapping — and why is it now the default?
Speedstrapping means reaching early revenue and securing non-dilutive capital — leases, credit facilities, project finance — before raising large venture equity. And it means heavy use of AI to accelerate everything from engineering to sales. Climate hardware creates tangible assets that can be financed against contracts and demand. But only if they are actually being paid for. The goal is operational breakeven around Series A, then a pivot to capital markets outside venture.
We used to think this applied to a subset of the portfolio, with growth equity as the main path. After the zombie unicorns of the Covid era, that thinking flipped. Then AI raised what small teams could ship; private credit expanded into categories that had no non-dilutive options before. The combination made speedstrapping the default and growth equity the exception. Nevoya, an electric-trucking company in our portfolio, secured 20 vehicle leases before raising its pre-seed. That’s the template now.
We built CreditDB.ai, the capital-stack compass, with students from the Haas School of Business — now a database of 300+ non-dilutive capital providers with a chat-based matching interface.
How is Third Sphere using AI to rewrite the VC operating model?
The case covers two examples. First, an internal scoring system — what we call our robots — trained on our archive of past investment memos. It already does a decent job of predicting what we’re likely to back. The bigger change isn’t speed; it’s who gets seen. A cold inbound that scores well now gets prioritized on its merits, not on who made the warm intro.
Second, company-specific impact baselines generated from that same memo archive. Instead of forcing every portfolio company into the same five metrics, we ask the specific questions that matter for that technology. Several founders have adopted our AI-generated impact reports as their own. We’ve also used these tools for systems research — vibe-coding a BloombergNEF-style simulation of how AI data-center energy demand might reshape renewable infrastructure, in an afternoon, with a four-person team.
The Earth Force discovery: solve wildfire, unlock low-carbon housing
Earth Force Technologies replaced spray-can, judgment-call tree marking with machine vision for wildfire vegetation management — automating both which material to remove and the verification that it was done. The first-order impact is real: federal timber removal for wildfire risk has run below 10% of quota for two decades, and this is the change that unlocks full capacity.
The second-order impact surfaced from the data, not the original memo: a guaranteed, low-cost supply of harvested timber is exactly the input needed to manufacture cross-laminated timber (CLT), a low-carbon substitute for concrete and steel in construction.
We wouldn’t have caught that connection without AI re-reading our archive against new portfolio data.
The open question: how are LPs diligencing climate impact in 2026?
The case ends on a question we’re genuinely sitting with — and we’re leaving it open on purpose.
The political backlash against ESG, SFDR’s tightening definitions in Europe, and AI’s rewriting of energy-demand assumptions all moved at once. Some LPs are doubling down on climate; others have gone quiet; most have shifted in ways they haven’t fully articulated. For a fund raising at scale, how others define impact is no longer background noise — it’s a fundraising constraint. So we’re asking, not answering: if you have a view, even a half-formed one, we’d like to hear it.
Where to go next
Two ways to keep going.
For LPs
The case is the snapshot. The conversation is the project.
If you’re evaluating climate venture in 2026 and have a view on how impact should be diligenced, we want to hear it. Request a copy of the case, then start a conversation.
Request a copy of the case →
Read the 2025 Portfolio Impact Report →
For Founders
Finance the hard part without raising too much, too early.
The speedstrapping sections are the most concise description of how we think about capital-stack design for early-stage climate companies. Start with the playbook and the capital-stack compass.
Explore the SpeedStrap Playbook →
Browse CreditDB.ai — 300+ capital providers →
Companion reading
The full record.
Read the case at the source.
The PDF is gated at Stanford — that gate is part of what makes the credential credible. Everything on this page is our own companion account. The case itself is the definitive version.
Third Sphere: Impact in Transition (SI-193) was prepared by Lecturer Jaclyn Foroughi, CFA, CAIA, and is published and copyrighted by the Board of Trustees of the Leland Stanford Junior University. This page is an independent companion guide produced by Third Sphere; it does not reproduce the case and links to Stanford GSB as the canonical source. With thanks to Jaclyn Foroughi and the team at Stanford GSB.