Startups fail from premature scaling, not missing features—the first architecture should optimize for iteration speed, not theoretical load. Build for 100 users excellently before designing for 100,000.
●TypeScript + SaaS
TypeScript Developer
for SaaS
Strategic tech guidance without the equity. MVP in 8 weeks, scale to Series A. Saved founders $2M+ in avoided rewrites. Free strategy call.
●Key Insights
TypeScript isn't just about catching bugs—it's documentation that never goes stale. When your first engineer leaves, the types explain what they built. This compounds into onboarding speed as you grow.
The 'boring technology' principle applies doubly to startups: PostgreSQL, Redis, and S3 have known failure modes. Novel tech stacks have unknown failure modes that consume debugging time you don't have.
Feature flags should be infrastructure from day one, not an afterthought. They're not just for gradual rollouts—they're how you turn off the feature that's breaking at 2 AM without deploying code.
Your first ten customers will ask for features that only they need. The architecture must distinguish core product from customer-specific customization, or you'll drown in bespoke code.
●SaaS Regulations
Compliance requirements that shape technical architecture
●Common Challenges
Problems I solve for clients in this space
Choosing the right initial tech stack
Founders waste months debating technology choices when the answer is almost always 'it depends on what your team knows.' Wrong choices compound into technical debt.
Start with what your team is productive in, within reason. PostgreSQL, not MongoDB. React or Vue, not an obscure framework. Boring technology with known failure modes beats novel technology with unknown failure modes.
Building for scale too early
Microservices, Kubernetes, and event sourcing are premature optimization for a startup with 10 users. The complexity slows iteration when you need speed most.
Monolith first, with clear module boundaries. The monolith can be decomposed when you have traffic patterns that justify complexity. Most startups never need microservices.
Technical debt from MVP pace
Moving fast creates shortcuts that become landmines. But moving slow means running out of runway before finding product-market fit.
Strategic technical debt: document every shortcut, estimate remediation cost, and pay it down immediately once the feature proves valuable. Unknown debt is dangerous; known debt is a tool.
Hiring the first engineers
Non-technical founders struggle to evaluate engineering candidates. Bad early hires can sink the company; over-qualified hires get bored and leave.
Technical advisor involvement in hiring: defining the role, reviewing resumes, conducting technical screens, and calibrating compensation. The first three engineers set the culture.
Investor technical due diligence
Series A investors increasingly conduct code audits. Technical debt, security issues, and architectural red flags can tank deals or reduce valuations.
Proactive due diligence preparation: clean up the codebase before fundraising, document architectural decisions, address known security issues. I can conduct pre-diligence audits and coach you through investor technical questions.
●Recommended Stack
Optimal technology choices for TypeScript + SaaS
●Why TypeScript?
●My Approach
●Investment Guidance
Typical budget ranges for TypeScript saas projects
Factors affecting scope
- Founder technical capability (can you contribute code?)
- MVP scope and complexity
- Third-party integration requirements
- Timeline urgency
- Ongoing advisory vs project-based engagement