Startups vs Big Tech for Web Developers

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Show Notes

Introduction

• One of the theories I have is with the rise of AI, it will democratize creating POCs and therefore creating startups
• Therefore there might be more opportunities for developers to get into startups in the future vs big tech
• What is big tech? 
  
  • FAANG (or MAANG)
  • Fortune 500 corps
  • Large enterprises
• What is a startup?
  
  • Usually less than 100 employees
  • Funding is often from investors or bootstrapped
• My experience
  
  • Worked in a larger startup that transitioned to a mid size company
  • Have friends and family that work in big tech (Amazon, Instacart, Facebook, Apple)
  • Working currently at a 30-40 person startup

1. Scope and Breadth of Responsibilities

• Startup
  
  • Broad scope: Developers wear multiple hats, often handling frontend, backend, DevOps, and even customer support.
  • High autonomy: Opportunity to influence product direction.
  • Potential downside: Risk of burnout or lack of specialization.
    
    
• Evidence: According to Stack Overflow's Developer Survey (2023), startup developers often report higher job diversity but also higher stress.
  
  
• Big Tech
  
  • Clearly defined roles: Developers usually specialize in a specific area (frontend, backend, infrastructure, etc.).
  • Deep expertise: Opportunity to master specialized skill sets.
  • Potential downside: Reduced visibility into overall product direction and slower personal impact.
    
    
• Evidence: FAANG companies frequently hire specialists in niche technologies (e.g., React core teams, backend-only roles at Google).
  

2. Development Pace and Workflows

• Startup
  
  • Faster iteration cycles: Quick prototyping and MVP approach.
  • Agile in practice, less rigid adherence to formal processes.
  • Potential downside: Technical debt accrues faster due to speed.
    
    
• Evidence: Lean Startup methodology popularized by Eric Ries emphasizes fast cycles of "build-measure-learn."
  
  
• Big Tech
  
  • More structured release cycles: Greater emphasis on code review, testing, QA processes, and gradual rollout.
  • Emphasis on reliability, scalability, and maintainability.
  • Potential downside: Slower pace of innovation due to bureaucracy.
    
    
• Evidence: Google's development practices emphasize rigorous code reviews and automated testing frameworks for scalability (Google’s SRE Handbook).
  

3. Impact and Ownership

• Startup
  
  • High impact per developer: Individual contributions directly influence company survival.
  • Sense of ownership: Close connection to users, seeing immediate results of work.
  • Potential downside: Higher pressure and responsibility can lead to stress.
    
    
• Evidence: Harvard Business Review (2022) highlights higher engagement and job satisfaction among startup employees due to perceived personal impact.
  
  
• Big Tech
  
  • Impact at scale: Changes made by a developer potentially affect millions of users.
  • Shared ownership: Contributions are part of larger initiatives and teams.
  • Potential downside: Individual impact can feel diluted.
    
    
• Evidence: Netflix’s engineering culture emphasizes shared responsibility, allowing broad autonomy within clearly defined parameters.
  

4. Career Growth and Mentorship

• Startup
  
  • Accelerated learning: Exposure to multiple technologies and rapid problem-solving.
  • Potential downside: Less structured mentorship or formalized training.
    
    
• Evidence: TechCrunch (2023) notes developers at startups tend to self-teach more frequently due to fewer internal resources.
  
  
• Big Tech
  
  • Structured career paths: Clearly defined levels (junior, mid, senior, staff engineer).
    Strong mentorship and training programs.
  • Potential downside: Progression can be slower due to rigid promotion cycles and bureaucracy.
    
    
• Evidence: Big tech companies like Amazon and Microsoft frequently provide formal mentorship programs and career mapping (Glassdoor, 2023).
  

5. Job Security and Stability

• Startup
  
  • Higher risk: Employment stability closely tied to funding rounds, product-market fit, and growth trajectory.
  • Higher reward potential: Equity opportunities can provide financial upside if the startup succeeds.
    
    
• Evidence: Forbes reports (2022) that 70% of startups fail within the first five years, highlighting employment risk.
  
  
• Big Tech
  
  • Greater stability: Established companies offer consistent employment, stable income, and extensive employee benefits.
  • Predictable career trajectory with established compensation packages.
  • Potential downside: Lower potential financial upside (aside from steady incremental raises or bonuses).
    
    
• Evidence: LinkedIn Workforce Report (2023) shows big tech employees have longer average tenure compared to startup employees.
• https://www.investopedia.com/articles/personal-finance/040915/how-many-startups-fail-and-why.asp#:~:text=Despite%20their%20promise%2C%20as%20many,first%20five%20to%20ten%20years.
  
  

6. Culture and Work Environment

• Startup
  
  • Informal culture: Generally flexible hours, casual dress code, emphasis on camaraderie.
  • Greater influence on culture: Early employees shape organizational values.
  • Potential downside: Sometimes chaotic or unclear structure.
    
    
• Evidence: Surveys by AngelList consistently rate startup flexibility and culture as key attractions for tech workers.
  
  
• Big Tech
  
  • Structured, professional environment: Clear policies, formal processes, extensive HR frameworks.
  • Extensive perks: Often include comprehensive healthcare, parental leave, wellness programs, catered meals, and more.
  • Potential downside: Possible feeling of being just another employee in a large organization.
    
    
• Evidence: Employee reviews on Glassdoor commonly highlight extensive benefits and stability in big tech, but also occasional lack of personalized attention or care.
  

7. Tech Stack and Innovation

• Startup
  
  • Greater freedom in choosing technologies: Typically quick adoption of cutting-edge or experimental frameworks.
  • Potential downside: Less mature tooling and potential compatibility issues or frequent rewrites.
    
    
• Evidence: Developer happiness surveys (Stack Overflow 2023) indicate developers value the ability to experiment, common at startups.
  
  
• Big Tech
  
  • Well-established stacks: Battle-tested technologies, large-scale deployments, and internal tooling.
  • Potential downside: Slow adoption of new technologies due to scale and operational constraints.
    

• ‍Evidence: Facebook's slow adoption and careful rollouts of React 18 demonstrate caution in big tech’s approach to innovation (Facebook Engineering Blog, 2022).