Thesis Evolution Log
Chronological record of how the Project TBD thesis has shifted, with Signal quotes as evidence. Each entry documents the before/after state, the evidence that drove the shift, and why it matters.
2026-01-15 — Buyer psychology established
Before: Unclear who would pay for supply chain resilience. After: Tier 1 suppliers (downstream customers) pay for resilience because it helps them win downstream contracts — e.g., a supplier to Toyota benefits if they can demonstrate resilience to Toyota. Evidence: > “company that supplies brakes to Toyota helps to get the Toyota contract if they can demonstrate to Toyota an increased resilience of their own supply chain” Significance: First articulation of a real paying buyer — shifts the model from speculative to grounded.
2026-01-21 — AI becomes a core lens, not background hype
Before: Both founders were “very contrarian and very averse to all the hype around AI.” After: Explicit decision to lean into AI — both as a mission bridge (best commercial AI for national interest, à la Palantir) and as a business model differentiator (AI-native companies will outcompete legacy software). Evidence: > “we’re living through a once-in-a-generation type of technological moment, and we should be thinking about how to lean in” Significance: Establishes AI-native design as a core product principle, not just a feature.
2026-02-08 — Data flywheel articulated as core business logic
Before: Compliance as a revenue source. After: Compliance intelligence → customer data accumulation → insurance product spinoff. “BPT in action.” The data asset is the compounding advantage. Evidence: > “Provide firms supply chain intelligence to incentivize sharing their own data → increase ability to sell the same product to other customers → use all customer data to spin off insurance product” Significance: Shifts from product thinking to platform thinking. The compliance product is the data acquisition mechanism, not the end goal.
2026-02-15 — Three-step progression crystallized
Before: Loose framing of compliance as a wedge with financial upside. After: compliance → intelligence → finance is the clearest, most compelling narrative arc. This becomes the canonical description of the business model. Evidence: > “the most compelling and exciting vision is compliance to intelligence to finance” Significance: Canonical thesis statement established for all external pitches and internal planning.
2026-02-17 — Industry pivot toward batteries (later reversed)
Before: Semiconductors as the target vertical.
After: Cross-industry oil-analog analysis (13-page deep research report) concluded batteries were the highest-conviction Day-1 wedge — driven by EU Battery Passport regulatory deadline (Feb 2027) and stronger oil-analog prerequisites (recurring shocks, volatility, benchmark infrastructure).
Evidence: Oil-analog scan report: memory/media/2026-02-17-oil-analog-scan-batteries-winner.pdf
Significance: Temporary thesis pivot. Later reversed (see Mar 18 below). Reveals that they hadn’t yet done deep enough work on semiconductors to confidently commit — and that disciplined research changed their mind in both directions.
2026-02-27 — “Data exhaust” adopted as core terminology
Before: “Data generated by compliance” — vague framing. After: “Data exhaust” from the compliance platform becomes the formal term. Sourced from Joe Malchow meeting. Exhaust language positions the data as a byproduct the company uniquely captures and monetizes. Evidence: > “Key term used by Joe yesterday which I think we should start adopting… we’re triangulating towards the compliance wedge as our area of initial and actionable focus, and using the data exhaust from that platform to structure risk products and/or hedging instruments” Significance: Terminological clarity is strategic. “Data exhaust” frames the value clearly for investors and partners.
2026-03-02 — Clearest thesis statement to date
Before: Iterative fragments of compliance + data + finance. After: “I feel like we have pretty solid understanding of our potential model and its progression from compliance → data intelligence asset → financial derivatives/risk transfer/insurance. Now it’s time to do the legwork to prepare to test this externally.” Evidence: Bliss’s message Mar 2. Significance: First time either founder declared the thesis “solid.” Marks transition from ideation to validation mode.
2026-03-09 — Weakness reframed as strength
Before: “We designed a business model without any unique customer insight” — acknowledged as a fundamental weakness. After: The compliance wedge strategy converts this weakness: use the product to get inside customer organizations, then discover real problems and build the digital twin on top. Evidence: > “We designed a business model without any unique customer insight. That’s always been our weakness. This strategy allows our weakness to become a strength.” (Dustin, post-Eyck meeting) Significance: Major strategic reframe. Changes the go-to-market logic from push to pull.
2026-03-18 — Return to semiconductors; batteries pivot shelved
Before: Post-Feb-17, some residual consideration of batteries as primary vertical. After: Null hypothesis locked on semiconductors. Don’t pivot without evidence. Evidence: > “our null hypothesis/framing right now is semis so let’s stick with that unless we are shown evidence otherwise to pivot” Significance: Brings closure to the Feb battery pivot. Existing synthesis docs (compliance-wedge-takeaways.md) already recommend semis as the strongest vertical — decision now formally aligned.
2026-03-18 — Buyer persona updated: cost engineers, not compliance teams
Before: Assumed compliance teams or supply chain teams are the primary buyers. After: Cost engineers hold the budget and decision-making authority in semiconductor firms. They’re motivated by probabilistic cost scenario modeling, not compliance certifications. Evidence: > “Cost engineers — these are the people in the company with a lot of power/value… It’s not a certification that there is no China; it’s a probabilistic dynamic model that can help figure out the scenarios and probability of different cost outcomes.” (Joe Malchow / Ali Keshavarzi meeting) Significance: Changes the go-to-market target — product messaging and sales approach need to speak to cost engineers.
2026-04-06 — Trojan horse as the core differentiator
Before: Compliance as “wedge” — somewhat generic framing. After: The compliance product is specifically a trojan horse: solving unavoidable regulated workflows to acquire proprietary data that powers the digital twin. The edge is not the compliance product itself but the data acquisition mechanism. Evidence: > “Our approach is focused on creating a trojan horse style [thing] that gets our foot in the door and unlocks primary insight” (vs. the RDI primer’s focus on industry analysis) Significance: Sharper language for investor conversations and RDI articulation.
2026-04-10 — Ontology building becomes the tactical priority
Before: Research/validation mode; building the external thesis. After: Building the ontology (on public data) is now the most important immediate task — it frames the edges of the problem, reveals data gaps, and creates credibility for external conversations. Evidence: > “My strong sense is that the most important thing for us to do right now, and quickly, is build this ontology using currently available data.” Significance: Marks the shift from research phase to prototype phase. The ontology is the first tangible artifact.