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Lenny's 🏦 Vault

Clear Explanations Unlock Iterative Breakthroughs

by Tomer Cohen on December 4, 2025

The Full Stack Builder Model: Reimagining Product Development for the AI Era

LinkedIn's approach to product development in the AI era centers on empowering individuals to build end-to-end regardless of their traditional role, creating more nimble and adaptive teams that can match the accelerating pace of change.

Why Traditional Product Development Needs Reimagining

  • The skills required for jobs will change by 70% by 2030
  • 70% of today's fastest-growing jobs weren't even on the list a year ago
  • The time constant of change now exceeds the time constant of response
    • Organizations must become more nimble to stay competitive

The Problem with Traditional Product Development

  • The basic builder process (research → spec → design → code → launch → iterate) has become unnecessarily complex
    • Each step expanded into numerous sub-steps (e.g., 10-15 sources of research information)
    • Multiple reviews (design, privacy, security) slow down progress
    • Valid reasons for each step, but collectively creates bloat
  • Process complexity led to organizational complexity
    • Micro-specialization across functions (PM, design, engineering)
    • Further specialization within functions (e.g., interaction design, animation design, content design)
  • Result: Building even small features requires multiple teams, codebases, and sprints

The Full Stack Builder Model

  • Core goal: Empower builders to take ideas to market regardless of role or team
  • Definition: A fluid interaction between human and machine where builders develop experiences end-to-end
  • Key human traits to preserve:
    • Vision: Creating compelling stances about the future
    • Empathy: Deep understanding of unmet needs
    • Communication: Aligning others around ideas
    • Creativity: Generating possibilities beyond the obvious
    • Judgment: Making high-quality decisions in complex, ambiguous situations
  • Everything else should be automated

Implementation Components

1. Platform

  • Re-architect core platforms so AI can reason over them
  • Build composable UI components with server-side support
  • Customize third-party tools to work with your stack
    • Off-the-shelf AI tools rarely work without customization

2. Tools & Agents

  • Build specialized agents for different aspects of product development:
    • Trust agent: Identifies vulnerabilities and harm vectors
    • Growth agent: Critiques ideas based on growth potential
    • Research agent: Trained on member personas and support tickets
    • Analyst agent: Queries data without SQL knowledge
    • Maintenance agent: Fixes failed builds (achieving ~50% automation)
  • Key learning: Don't just give agents access to all information
    • Curate "golden examples" and clean data for better results
    • Build connections between agents for orchestration

3. Culture

  • Performance evaluation: Include AI fluency in hiring and reviews
  • Pilot success stories: Create pods that demonstrate the model works
  • Associate Product Builder program: Replace APM program with cross-functional training
  • Celebrate wins: Highlight people using the tools successfully
  • Make tools accessible: Allow feedback and iteration

Organizational Structure Changes

  • Created a new career path with "Full Stack Builder" title and ladder
  • Shifted from large teams to small, cross-functional pods
    • Pods focus on missions rather than functional specialties
    • Teams assemble for specific problems, then reassemble for new challenges
  • Not everyone needs to be a full stack builder
    • Some will remain specialists, but fewer than before
    • Some will be system builders who empower full stack builders

Implementation Lessons

  • Top performers adopt AI tools first
    • They have an innate desire to improve their craft
  • Change management is critical
    • Not enough to just provide tools - must build incentives and motivation
    • Show examples of others being successful
  • Start with small teams but maintain visibility
    • Let the organization see progress to build interest
  • Be patient with the transformation
    • Invest upfront in platform and tools
    • Don't expect immediate 2x productivity gains
  • Don't wait for formal reorganization
    • Give permission to start building differently now

Results So Far

  • Teams saving hours of work per week
  • Higher quality insights and discussions
  • Designers and PMs picking up tasks directly from Jira
  • Increased ability to adapt to change

The model ultimately aims to create an organization that resembles Navy SEALs: cross-trained individuals who specialize in missions, operating in small, nimble pods that can be quickly assembled to tackle new challenges.

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