Personal Hypotheses and Beliefs

This document captures your core beliefs about what will drive Apps adoption success. Each hypothesis should be testable and backed by data.

Hypothesis Framework

flowchart LR
    subgraph Framework["HYPOTHESIS → DATA → ACTION"]
        H["HYPOTHESIS<br/>What you believe"]
        D["DATA<br/>Evidence needed"]
        A["ACTION<br/>What you'd do"]
    end
    
    H --> D --> A
    A --> |"Validate & Learn"| H

Hypothesis 1: Apps as Tip of the Spear

Belief

Apps can serve as the entry point to land workloads across ETL, DW, ML, AI Agents, and Operational use cases—driving influenced revenue that exceeds direct Apps revenue.

Why You Believe This

• Apps position closer to business value than infrastructure
• Apps are visible to business users, unlocking new budget sources
• Apps act as a “container” for multiple workloads

Data Needed to Validate

Risks If Wrong

• Apps becomes a distraction from core revenue
• Field loses trust in “influenced revenue” narrative
• Investment in Apps GTM doesn’t pay off

Cross-References

Hypothesis 2: Ecosystem Synergy Is the Moat

Belief

The combination of Lakebase + Governance + AI creates a defensible moat that accelerates adoption—customers who use all three have higher retention and expansion.

Why You Believe This

• Synergies reduce integration complexity
• Unified governance is an executive priority
• Co-located AI is a developer preference

Data Needed to Validate

Risks If Wrong

• Customers may prefer best-of-breed over integrated
• Feature gaps in individual products undermine synergy story
• Moat is theoretical, not experienced by customers

Cross-References

Hypothesis 3: Full-Funnel GTM Gap (Refined)

Belief

FE faces a FULL-FUNNEL gap: they don’t identify Apps opportunities, can’t qualify use cases, AND lack architecture conversation skills. The blocker starts earlier than architecture—at opportunity identification and qualification.

The Full Funnel Problem

flowchart TB
    ID["STAGE 1: IDENTIFY<br/>❌ FE doesn't see Apps opportunity"]
    QU["STAGE 2: QUALIFY<br/>❌ No qualification framework"]
    PO["STAGE 3: POSITION<br/>❌ Architecture uncertainty"]
    CL["STAGE 4: CLOSE<br/>⚠️ Product gaps block some deals"]
    
    ID --> QU --> PO --> CL

Why You Believe This

• FE is strong on Data/ML, weak on app patterns
• Apps Cookbook is insufficient
• FE doesn’t recognize Apps opportunity even when present
• Industry GTM leads not aligned on Apps use cases by vertical
• Marketing events don’t feature Apps demos prominently
• EBCs don’t include Apps positioning for executives

Data Needed to Validate

Resolution Path

Cross-References

Hypothesis 4: Three App Archetypes Drive 80% of Adoption

Belief

The majority of successful Apps adoption falls into three patterns: Business Cockpits, Deeply Vertical Apps, and Horizontal Platform Apps—and we should build playbooks for each.

Why You Believe This

• Pattern recognition from existing wins
• Each archetype has distinct buyer and value prop
• Focused playbooks > generic enablement

Data Needed to Validate

Cross-References

Hypothesis 5: SI Partnerships Can Counter Palantir’s FDE Motion

Belief

By partnering with App-first SIs, we can achieve Palantir-like solution delivery at scale without building an internal FDE army—and at lower cost to customers.

Why You Believe This

• SIs have delivery capacity we don’t have
• App-first SIs already have relevant skills
• Palantir’s model is expensive and not scalable for all segments

Data Needed to Validate

Cross-References

Hypothesis 6: Influenced Revenue Metrics Will Align BU Leaders

Belief

If we can define and track Apps attach rates and influenced revenue, BU leaders will invest in Apps GTM because they’ll see the downstream impact on their core products.

Why You Believe This

• BU leaders are rational—they follow the money
• Current problem is lack of visibility, not lack of impact
• Other platform companies use influenced revenue successfully

Data Needed to Validate

Cross-References

Hypothesis 7: Net-New Apps (Not Migration) Is the Right Focus

Belief

We should focus on net-new application development, not legacy app migration—because our platform is optimized for this and trying to migrate Java/.NET apps will fail.

Why You Believe This

• Product limitations (legacy framework support coming FY27)
• Competitive positioning is weaker for migration
• Net-new lets us lead with AI/Lakebase differentiation

Data Needed to Validate

Cross-References

Hypothesis 8: Quality vs Quantity Determines Adoption Success

Belief

Deep implementations with few apps (Quality motion) drive retention and stickiness for business outcome-oriented customers, while many lightweight apps (Quantity motion) drive coverage for developer-centric customers. Mismatching motion to customer profile leads to low retention.

Why You Believe This

• Current retention is low—suggests motion-customer mismatch
• Active users per app follows power law—few apps drive most value
• Business outcome customers need depth and PS support
• Digital Native customers value dev experience and IDE integration

The Two Motions

Data Needed to Validate

Cross-References

Hypothesis Prioritization

Hypothesis Status Summary

Update this table as hypotheses are validated or invalidated.

Last Updated: January 2026