Build vs buy: the technical decisions that make or break startups

Every startup faces the same critical question: should we build this ourselves or buy an existing solution? Get it wrong, and you’ll either burn months building what you could have bought, or lock yourself into expensive vendor dependencies that limit your growth.

I’ve seen both scenarios destroy promising startups. The companies that thrive understand that build vs buy isn’t about finding the “right” answer - it’s about making decisions that align with your current constraints and future goals.

The hidden cost of getting it wrong

Most founders approach build vs buy decisions backward, starting with technology preferences instead of business outcomes. This leads to expensive mistakes that compound over time.

The “build everything” trap:

I worked with a fintech startup that spent eight months building a custom notification system instead of using SendGrid or similar. They wanted “full control” and “no vendor dependencies.”

The result? Their two best engineers spent most of Q2 and Q3 working on email delivery optimization instead of core financial features. Meanwhile, their competitor launched three major product updates and secured Series A funding.

The custom notification system worked, but the opportunity cost was enormous. They missed their market window because they built commodity functionality instead of focusing on their unique value proposition.

The “buy everything” trap:

On the flip side, I’ve seen startups become so vendor-dependent that they can’t control their own destiny. One e-commerce company I advised had 23 different SaaS subscriptions by month 12. Their monthly tool costs exceeded their engineering payroll.

Worse, when they needed to customize the checkout flow for their unique business model, they discovered their payment processor didn’t support it. Switching would have required rebuilding their entire order management system.

They had optimized for speed but sacrificed flexibility at a critical growth stage.

The decision framework that actually works

The key insight is that build vs buy decisions aren’t about technology - they’re about resource allocation and strategic positioning. Here’s the framework I’ve developed working with dozens of startups:

Start with business impact assessment

Before evaluating any technical options, answer these questions:

Strategic importance:

• Is this core to our competitive advantage?
• Will customers notice if we do this better than competitors?
• Does this directly impact our key business metrics?
• Could this become a differentiating feature later?

Timeline constraints:

• When do we need this functionality?
• What happens if we delay this by 3-6 months?
• Are there upcoming milestones that depend on this?
• Can we launch without this feature initially?

Resource availability:

• Do we have the right engineering talent for this?
• What other projects would this delay?
• How much ongoing maintenance will this require?
• Could we hire specialists if needed?

The build vs buy decision matrix

Use this matrix to evaluate each option systematically:

              | High Strategic Value | Low Strategic Value
High Complexity| Consider Build      | Strong Buy
Low Complexity | Lean Build          | Definite Buy

High strategic value + High complexity: This is where the decision gets nuanced. Consider building if you have the resources and timeline. Look for ways to start with a simple version or find vendors that offer customization.

High strategic value + Low complexity: Usually lean toward building, but set strict timelines. If it takes longer than estimated, reassess.

Low strategic value + High complexity: Strong buy signal. Focus your engineering resources on high-value problems.

Low strategic value + Low complexity: Definite buy. Don’t waste time on commodity functionality.

Case study: Authentication decisions

Let me walk through a real example of how this framework plays out. A B2B SaaS startup needed to implement user authentication and authorization.

Strategic assessment:

• Strategic importance: Medium - customers expect it but it’s not differentiating
• Timeline: Needed for MVP launch in 8 weeks
• Resources: Two full-stack engineers, both new to security best practices
• Complexity: High - proper security, password reset, role management, audit trails

Options evaluated:

Option 1: Build custom auth system

• Pros: Full control, no vendor dependencies, custom UI
• Cons: 6-8 weeks development time, ongoing security maintenance, compliance complexity
• Total cost year 1: $60k+ in engineering time, plus ongoing maintenance

Option 2: Use Auth0

• Pros: Battle-tested security, compliance handled, 2-week integration
• Cons: $2k/month at scale, vendor dependency, UI constraints
• Total cost year 1: $15k in service costs, $10k integration time

Option 3: Use open-source solution (Supabase Auth)

• Pros: Lower cost, good developer experience, some customization
• Cons: Self-hosting complexity, limited enterprise features
• Total cost year 1: $5k in hosting, $15k integration and maintenance

Decision: They chose Auth0 for MVP, with a plan to evaluate building custom auth after reaching 1000 paid users.

Outcome: Launched on time, Auth0 handled their growth to 5000 users seamlessly. When they did evaluate building custom auth 18 months later, they realized Auth0’s enterprise features would have taken another 6 months to replicate. They stayed with Auth0 and invested those engineering resources in core product features instead.

When to build: the competitive advantage test

Build when you can answer “yes” to most of these questions:

Competitive differentiation:

• Could this feature be a significant competitive advantage?
• Do existing solutions fall short of what your customers need?
• Could you potentially license this to other companies later?

Resource fit:

• Do you have engineers who are excited about this problem?
• Is this within your team’s core competencies?
• Can you commit to long-term maintenance and evolution?

Strategic control:

• Do you need complete control over the user experience?
• Are there regulatory or compliance requirements that vendors can’t meet?
• Could vendor limitations constrain your business model?

Economic viability:

• Is the total cost of ownership favorable over 3-5 years?
• Could you build significantly better functionality?
• Are vendor costs unsustainable at your target scale?

When to buy: the time and focus test

Buy when you can answer “yes” to most of these questions:

Time pressure:

• Do you need this functionality in less than 4-6 weeks?
• Are there market timing pressures that make speed critical?
• Would building this delay more important features?

Commodity functionality:

• Is this “table stakes” functionality that customers expect?
• Are there mature, reliable vendors in this space?
• Would customers not notice or care about customization?

Resource constraints:

• Do you lack the specific expertise needed?
• Would this require hiring specialists?
• Are your engineers already overcommitted?

Quality requirements:

• Do you need enterprise-grade reliability immediately?
• Are there security or compliance requirements beyond your expertise?
• Would the vendor solution be significantly more robust?

The total cost of ownership framework

Most startups dramatically underestimate the hidden costs of building. Use this framework to calculate true costs:

Build costs:

• Initial development time (multiply estimates by 1.5-2x)
• Ongoing maintenance and bug fixes (20-30% of development cost annually)
• Security updates and compliance work
• Documentation and knowledge transfer
• Opportunity cost of not working on core features

Buy costs:

• Subscription or licensing fees
• Integration and customization time
• Vendor management overhead
• Migration costs if you switch later
• Feature limitations and workarounds

Example calculation for a CRM integration:

Build option:

• Development: 12 weeks × $8k/week = $96k
• Annual maintenance: $20k
• Opportunity cost: 3 core features delayed = ~$200k in potential revenue
• Total year 1 cost: $316k

Buy option (HubSpot API):

• License: $100/month × 12 = $1.2k
• Integration: 3 weeks × $8k/week = $24k
• Customization: $5k
• Total year 1 cost: $30.2k

The buy option was 10x cheaper when including opportunity costs.

Industry-specific considerations

Different industries have different build vs buy patterns:

Fintech startups:

• Always buy: Core banking infrastructure, payment processing, fraud detection
• Consider building: Risk models, user analytics, custom financial workflows
• Regulatory complexity makes buying safer for compliance-heavy features

Healthcare startups:

• Always buy: HIPAA compliance tools, EHR integrations, medical device connectivity
• Consider building: Patient experience features, clinical decision support, custom workflows
• Compliance and certification costs favor buying

E-commerce startups:

• Always buy: Payment processing, tax calculation, shipping APIs
• Consider building: Recommendation engines, inventory management, customer analytics
• Focus building on features that improve conversion rates

B2B SaaS startups:

• Always buy: Authentication, email delivery, customer support tools
• Consider building: Core product features, data analytics, workflow automation
• Build what customers pay for, buy what they expect

Managing vendor relationships effectively

When you decide to buy, vendor relationship management becomes critical:

Vendor evaluation criteria:

• Financial stability and company trajectory
• API quality and documentation
• Customer support responsiveness
• Pricing model sustainability
• Integration complexity and maintenance

Contract negotiation:

• Negotiate volume discounts based on growth projections
• Include data export clauses
• Set clear SLA requirements
• Plan for price change notifications
• Secure integration support commitments

Vendor risk mitigation:

• Avoid single points of failure
• Maintain data export capabilities
• Document integration patterns
• Monitor vendor health regularly
• Have backup options identified

Common decision-making mistakes

Learn from these patterns I’ve seen repeatedly:

Engineering-driven decisions:

• Choosing to build because “it’s more interesting”
• Underestimating maintenance complexity
• Ignoring opportunity costs
• Not considering team skill gaps

Business-driven mistakes:

• Focusing only on initial costs, not total cost of ownership
• Not planning for scale requirements
• Ignoring integration complexity
• Making decisions under extreme time pressure

Strategic mistakes:

• Building non-differentiating features
• Not reassessing decisions as the company grows
• Ignoring vendor lock-in risks
• Not documenting decision rationale

The evolution of build vs buy

Your build vs buy criteria should evolve as your startup grows:

Pre-product-market fit (0-10 employees):

• Strong bias toward buying
• Focus entirely on customer validation
• Accept vendor dependencies for speed
• Build only core differentiating features

Product-market fit to scale (10-50 employees):

• More selective building
• Consider total cost of ownership
• Plan for vendor negotiations
• Build features that improve unit economics

Scale and beyond (50+ employees):

• Strategic building of competitive advantages
• Vendor consolidation and optimization
• Build vs buy vs partner decisions
• Consider building platforms, not just features

Making decisions under uncertainty

Build vs buy decisions often happen with incomplete information. Use these strategies:

Time-boxed experiments:

• Set 2-week spikes to evaluate build complexity
• Build minimal prototypes to test assumptions
• Run vendor pilots with real data
• Compare actual results, not estimates

Reversible decisions:

• Start with the faster option
• Plan migration paths if needed
• Use abstraction layers for vendor integrations
• Document assumptions for future reassessment

Decision deadlines:

• Set clear deadlines for build vs buy decisions
• Don’t let perfect be the enemy of good
• Assign decision ownership to specific people
• Review decisions quarterly as constraints change

Building your decision-making muscle

Great build vs buy decisions come from experience and systematic thinking. Here’s how to improve:

Create decision templates:

• Document your decision criteria
• Track outcomes of past decisions
• Build institutional knowledge
• Share frameworks across your team

Regular reassessment:

• Review build vs buy decisions quarterly
• Track vendor costs and satisfaction
• Measure engineering productivity impact
• Reassess as your business model evolves

Learn from others:

• Join CTO communities and forums
• Read vendor case studies critically
• Talk to customers about their experiences
• Study successful companies in your space

Remember, your competitive advantage isn’t in building everything yourself - it’s in knowing what you should never outsource and what you should buy as fast as possible. The most expensive technical decision is the one that prevents you from reaching your next funding milestone.

Focus your limited engineering resources on the features that differentiate your product and delight your customers. Buy everything else, and buy it fast.