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ENTRY_BACKBONE_LABS_PROGRAM

Founding and Leading Backbone's Labs Program

PUBLISHEDMARCH 1, 2024
STATUS
ARCHIVED
CHANNELPUBLIC_LOG
VERSION2026.01

The Problem

Backbone needed a way to validate new product ideas early without disrupting core product work. The company was growing fast, but experimentation was expensive and risky. Every new initiative required full product team commitment, making it hard to test concepts before committing significant resources.

The core issue: There was no dedicated space for upstream innovation. Product teams were focused on shipping core features, and internal tooling needs were deprioritized. This created friction—designers spent hours manually managing assets, staging environments were outdated, and new product ideas had no clear path to validation.

What I Built

I founded Backbone's Design Engineering program directly under the CEO to operate upstream of core product work. Starting solo and growing into a focused team over 1.5 years, the Labs program worked on early product initiatives including the Emulator, a China-specific app, and multiple AI pilots, while also owning shared infrastructure like Figma plugins, Retool tools, and staging environment modernization.

Key differentiator: The program reduced the cost and risk of experimentation while increasing overall team velocity. By operating independently from core product teams, we could validate ideas quickly, build internal tools that reduced friction, and hand off validated concepts when they were ready for full product commitment.

Backbone Labs Program

Technical Approach

Program Structure

The Labs program operated with three core principles:

  1. Upstream validation - Test ideas before they require full product team commitment
  2. Internal tooling - Build infrastructure that reduces friction for the entire organization
  3. Rapid iteration - Move fast on experiments, slower on infrastructure

Key Initiatives

Product Experiments:

  • Emulator - Retro gaming emulator that completed Backbone's aggregator mission
  • China-specific app - Regional product adaptation
  • AI pilots - Multiple early-stage AI product concepts

Internal Infrastructure:

  • Figma plugins - Connected designers directly to game assets database
  • Retool tools - Internal admin and data management interfaces
  • Staging environment modernization - Updated deployment and testing infrastructure

Key Design Decisions

Program placement under CEO

Operating directly under the CEO gave the Labs program autonomy to work on initiatives that didn't fit into existing product roadmaps. This structure allowed us to pursue ideas that were strategically important but not yet ready for full product team commitment.

Small, focused team

Starting solo and growing to a small team kept overhead low and decision-making fast. We could pivot quickly when experiments didn't pan out, and we could move fast on infrastructure improvements that had clear impact.

Infrastructure ownership

By owning shared infrastructure like Figma plugins and staging environments, the Labs program created immediate value while also building capabilities that enabled faster experimentation. Good tools don't eliminate effort; they concentrate it.

Home screen replica for rapid prototyping

What I Learned

Upstream innovation needs dedicated space

Product teams are optimized for shipping. They need clear requirements, defined scope, and predictable timelines. Innovation requires ambiguity, experimentation, and the freedom to fail. These two modes don't coexist well in the same team structure.

Internal tooling compounds

The Figma plugin that started as a Labs experiment became essential infrastructure for the design team. The staging environment improvements reduced deployment friction for everyone. Small investments in internal tools create outsized impact over time.

Validation reduces risk

By validating ideas early in Labs, we could test assumptions before committing full product resources. This reduced the cost of failure and increased confidence when concepts moved to full product development.

Labs hackathon

Results

Quantitative:

  • Reduced experimentation cost by operating independently
  • Increased team velocity through internal tooling improvements
  • Validated multiple product concepts before full commitment

Qualitative:

  • Created a clear path for upstream innovation
  • Built infrastructure that became essential for design and engineering teams
  • Established a model for rapid experimentation that influenced how the company approached new product ideas

The Labs program validated that dedicated space for upstream innovation pays dividends. By operating independently, we could move fast on experiments and infrastructure improvements that would have been deprioritized in core product teams. The program reduced the cost and risk of experimentation while increasing overall team velocity.

CERTIFICATION
"This entry represents a point-in-time reflection from the personal archives of BT Norris. The thoughts contained herein are subject to evolution and iteration."
IDENTIFIER
TH_BACKBONE_01

END_OF_DOCUMENT

Field Log

Issue 01 // 2026

WED, JAN 14, 2026Available now
Observations on the intersection of design engineering, human-computer interaction, and the building of tools.

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BT Norris // 2026