EngineeringMap Methodology

A comprehensive guide to understanding and using our crowdsourced technology map for startup and scaleup decision-making

What is EngineeringMap?

EngineeringMap is a community-driven, opinionated guide to the technology landscape specifically curated for startups and scaleups building AI-powered products. It provides actionable insights on tools, techniques, platforms, and frameworks that can accelerate your AI engineering journey, powered by community votes, comments, and real-world experience.

Four Quadrants

  • • Techniques: Methods, practices, and approaches
  • • Tools: Software applications and utilities
  • • Platforms: Infrastructure and service platforms
  • • Languages & Frameworks: Programming languages and frameworks

Four Rings

  • • Adopt: Proven and recommended
  • • Trial: Worth pursuing with caution
  • • Assess: Worth exploring and understanding
  • • Hold: Proceed with caution or avoid
Scoring System for Startups & Scaleups
Our methodology considers the unique constraints and needs of growing companies

Adopt (Score: 80-100)

Criteria:

  • • Proven in production at scale
  • • Strong community support
  • • Excellent documentation
  • • Low learning curve
  • • Cost-effective for startups

For Startups:

  • • Safe default choices
  • • Reduces technical risk
  • • Faster time to market
  • • Easy to hire for

Trial (Score: 60-79)

Criteria:

  • • Emerging but promising
  • • Some production usage
  • • Active development
  • • Potential competitive advantage
  • • Manageable risk profile

For Startups:

  • • Use in non-critical paths
  • • Pilot projects and experiments
  • • Have fallback plans
  • • Monitor closely

Assess (Score: 40-59)

Criteria:

  • • Early stage or experimental
  • • Limited production usage
  • • Interesting potential
  • • Unclear long-term viability
  • • Requires investigation

For Startups:

  • • Research and prototyping only
  • • Allocate learning time
  • • Build internal expertise
  • • Wait for maturity

Hold (Score: 0-39)

Criteria:

  • • Significant issues or limitations
  • • Better alternatives available
  • • High risk or complexity
  • • Poor cost-benefit ratio
  • • Declining community support

For Startups:

  • • Avoid for new projects
  • • Plan migration if currently using
  • • Focus resources elsewhere
  • • Consider alternatives
Scoring Factors
Key criteria we evaluate when positioning technologies on the radar

TechnicalMaturity & Stability

  • • Production readiness (25 points)
  • • Performance and scalability (20 points)
  • • Security and compliance (15 points)
  • • API stability and versioning (10 points)

CommunityEcosystem Health

  • • Community size and activity (15 points)
  • • Documentation quality (10 points)
  • • Learning resources availability (5 points)

BusinessStartup Suitability

  • • Cost effectiveness (20 points)
  • • Time to value (15 points)
  • • Talent availability (10 points)
  • • Vendor lock-in risk (5 points)

InnovationFuture Potential

  • • Innovation and differentiation (10 points)
  • • Market adoption trends (5 points)
How to Use This Radar
1

Filter by Role

Use category filters to focus on tools relevant to your role: Product, Design, Development, QA, or DevOps.

2

Start with Adopt

Begin with technologies in the Adopt ring for safe, proven choices that reduce risk.

3

Plan Experiments

Use Trial and Assess technologies for competitive advantages, but with proper risk management.

Decision Framework for Startups

✅ When to Adopt Early

  • • Core infrastructure decisions
  • • Customer-facing features
  • • Security-critical components
  • • Areas where you lack expertise
  • • Time-sensitive deliverables

🧪 When to Experiment

  • • Internal tools and processes
  • • Non-critical feature development
  • • Areas of competitive differentiation
  • • When you have domain expertise
  • • Proof of concept projects

💡 Pro Tip for Startups

Focus on technologies that solve your immediate problems while keeping future scalability in mind. It's better to ship with proven tools than to get stuck perfecting the technology stack.