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Graph of Plan

Execution: One team, many products

We’re building four products with a small team. Spreading too thin could result in none of them reaching product-market fit.

The Risk

The portfolio thesis assumes we can execute on multiple products simultaneously:

  • Murphy: B2B SaaS for agencies
  • SmartBoxes: Developer platform with credit-based pricing
  • Nomos Cloud: Infrastructure with open-source SDK and enterprise sales
  • P4gent: Consumer product with viral growth mechanics

Each product has different:

  • Target customers
  • Go-to-market motions
  • Success metrics
  • Development requirements

A small team trying to do all four may do none well.

Specific Threats

  1. Context switching: Engineers moving between products lose productivity
  2. Support fragmentation: Customer issues compete for attention across products
  3. Marketing dilution: Brand and message get confused across different audiences
  4. Feature debt: Products ship MVPs but never mature
  5. Burnout: Team exhausted by breadth of demands

Mitigations

Product Strategy

  • Shared infrastructure: All products run on SmartBoxes + Nomos. Improvements to infrastructure benefit everything.
  • Sequential focus: Don’t launch all products simultaneously. Establish each before moving to the next.
  • Ruthless prioritisation: If a product isn’t finding fit within 3 months, cut or pause it.
  • Dogfooding: Our products help us build our products (Murphy for delivery control, SmartBoxes for automation).

Team Structure

  • Platform team: Core engineers focus on shared infrastructure
  • Product leads: Each product has one accountable owner
  • Clear roadmaps: No product gets worked on without a clear milestone

Measurement

  • Per-product metrics: Track acquisition, activation, retention separately for each product
  • Kill criteria: Define upfront what “not working” looks like for each product
  • Weekly reviews: Surface resource conflicts early

Residual Risk

Ambition exceeds capacity. The honest answer is: we’ll learn which products to focus on by trying them. The mitigation is being willing to cut products that don’t work rather than spreading thinner.

Probability: Medium (common startup failure mode) Impact: High (could prevent any product from succeeding) Mitigation effectiveness: Moderate (discipline helps, but pressure is real)