For any technology pre-launch startup, a key initial goal is to ship a reliable MVP fast, learn quickly, and preserve future flexibility. There are fundamental software engineering principles and practices that should be followed in order to achieve this goal:
Engineering Principles (The “Why”)
1. Build for Learning First
Principle: Early engineering exists to validate assumptions, not to be perfect.
• Optimise for fast feedback over completeness
• Prefer experiments over big builds
• Treat assumptions as hypotheses
2. Simplicity Over Cleverness
Principle: Simple systems are easier to change.
• Avoid over-engineering
• Use proven tools and frameworks
• Prefer explicit, readable code
3. Bias Toward Shipping
Principle: Working software beats perfect plans.
• Small, frequent releases
• Feature flags over long branches
• MVP > v1.0 fantasies
4. Ownership & Accountability
Principle: Every system has a clear owner.
• One person accountable per service/module
• Ownership includes reliability and documentation
5. Design for Change, Not Scale
Principle: Change is more certain than growth.
• Modular architecture
• Clear interfaces
• Delay optimisation until data demands it
6. Quality is Built In, Not Added Later
Principle: Bugs cost more the later they’re found.
• Automated tests over manual testing
• Code reviews as default
• Guardrails instead of heroics
7. Security and Privacy by Default
Principle: Trust is a core feature.
• Least-privilege access
• Secure defaults
• Compliance awareness even pre-launch
Core Engineering Practices (The “How”)
A. Architecture & Technology Choices
Practices
• Monolith first (modular internally)
• Clear separation of concerns
• Cloud-native but not cloud-locked
• Infrastructure as code (lightweight)
Guidelines
• Avoid micro-services pre-launch
• Choose boring, well-documented tech
• Prefer managed services over custom builds
B. Development Workflow
Practices
• Trunk-based development
• Short-lived feature branches
• Daily commits to main
• Feature flags for incomplete work
Definition of Done
• Code reviewed
• Tests passing
• Deployed to staging (or prod)
• Observability in place (logs/errors)
C. Code Quality & Reviews
Practices
• Mandatory peer review
• Small pull requests (<300 lines)
• Focus on clarity, not style nitpicks
• Shared coding standards
Review Checklist
• Does this solve the user problem?
• Is it understandable in 3 months?
• Does it introduce hidden complexity?
• Are failure cases handled?
D. Testing Strategy
Pre-Launch Testing Pyramid
1. Unit tests (core logic)
2. Integration tests (critical paths)
3. Minimal end-to-end tests
Practices
• Test business logic first
• Avoid over-mocking
• Automate regression tests
• QA focuses on exploratory testing
E. Deployment & Release
Practices
• Continuous deployment where possible
• One-click rollback
• Blue-green or canary releases (if needed)
• No manual production changes
Release Philosophy
• Release small, often
• Measure impact of every release
• Roll back fast if needed
F. Observability & Reliability
Practices
• Centralised logging
• Error tracking from day one
• Basic performance metrics
• Simple uptime monitoring
Principle
If you can’t see it, you can’t fix it.
G. Documentation & Knowledge Sharing
Practices
• README for every repo
• Architecture decision records (ADRs)
• Setup instructions always up-to-date
• Document “why”, not just “what”
Rule
• If it isn’t documented, it doesn’t exist.
H. Security Practices
Practices
• Secure authentication & authorisation
• Secrets management (no hard-coded keys)
• Dependency vulnerability scanning
• Regular access reviews
Pre-Launch Minimum Bar
• HTTPS everywhere
• Data encryption at rest
• Privacy policy alignment
Engineering Culture & Team Norms
Collaboration
• Async-first communication
• Written decisions over meetings
• Clear escalation paths
Feedback
• Blameless postmortems
• Continuous improvement mindset
• Psychological safety
Time Management
• Protect maker time
• Minimise meetings
• Engineering leads set priorities, not chaos
What NOT to Do Pre-Launch
• Premature scaling
• Over-custom infrastructure
• “Rewrite it later” mentality
• Hero-based development
• Ignoring tech debt completely
Engineering at Pre-Launch is about:
• Speed with discipline
• Learning over perfection
• Simple systems with strong foundations
• Ownership, quality, and security from day one
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