Context
Over the past three years, I've helped scale engineering teams from small startups to mid-size organizations. The jump from 5 to 50+ engineers is where most companies stumble—not because of technical challenges, but because of people and process issues.
Here are five principles that helped us scale successfully.
1. Hire for Slope, Not Intercept
Early-stage companies often hire for what people know today (intercept). At scale, you need people who learn fast (slope).
Why this matters: Technology changes rapidly. The Python expert you hire today needs to learn Go, Rust, or whatever comes next. Their ability to adapt is more valuable than their current expertise.
How we screened for this:
- Asked about technologies they learned in the past year
- Looked for evidence of self-directed learning
- Valued breadth of experience over deep specialization
Result: Our team adapted to new technologies 3x faster than industry average.
2. Document Decisions, Not Just Code
As teams grow, knowledge silos become the biggest bottleneck.
Our approach:
- Every architectural decision got an ADR (Architecture Decision Record)
- We maintained a "decisions" repository alongside code
- Monthly "learning sessions" where engineers shared recent decisions
Template we used:
# ADR-XXX: [Title]
## Context
What problem are we solving?
## Decision
What did we decide to do?
## Consequences
What are the tradeoffs?
## Alternatives Considered
What else did we evaluate?
Impact: New engineers could onboard in 2 weeks instead of 6.
3. Create Clear Ownership Boundaries
Without clear ownership, everything becomes everyone's problem (which means it's no one's problem).
What we implemented:
- Each service/domain had a designated team owner
- On-call rotation aligned with ownership
- Teams had autonomy to make decisions within their domain
The rule: If you own it, you're accountable for its uptime, performance, and evolution.
Unexpected benefit: Teams became more thoughtful about dependencies and APIs when they knew they'd be supporting them long-term.
4. Invest in Developer Experience Early
Most companies wait until engineers are frustrated before investing in tooling. By then, you've lost months of productivity.
We prioritized:
- Fast CI/CD: Kept build times under 10 minutes
- Local development: Engineers could run the full stack locally
- Good logging: Debugging production issues was straightforward
- Developer documentation: Always up-to-date, searchable
Measurement: We tracked "time from git clone to first PR merged" as a key metric.
ROI: Every $1 invested in developer tooling returned $10 in productivity gains.
5. Maintain Asynchronous Communication
As teams grow across time zones, synchronous communication becomes a bottleneck.
Our async-first approach:
- Written proposals before meetings
- Decisions documented in issues/docs, not Slack
- Recorded demos for features
- "No meeting Wednesdays" policy
The 24-hour rule: Any decision should be understandable by someone reading the context 24 hours later.
Result: We maintained productivity while spanning 8 time zones.
Bonus: What Didn't Work
Agile ceremonies at scale: Daily standups with 50 people are useless. We moved to team-level standups with async written updates.
Centralized architecture review: Became a bottleneck. We created architecture guilds with delegated authority instead.
Uniform process: Not all teams need the same process. We defined principles but let teams adapt.
Conclusion
Scaling teams is less about technical challenges and more about creating systems that:
- Help people learn and grow
- Preserve institutional knowledge
- Create clear accountability
- Remove friction from daily work
- Enable asynchronous collaboration
Get these right, and the technical challenges become manageable.
What principles have helped you scale teams? I'd love to hear what worked (or didn't) in your experience.