Post-Series A: The 5 Engineering Decisions That Make or Break Scale

Pre-seed and seed stage is about survival: ship fast, find PMF, don't run out of money. Post-Series A is different. You've proven the product works. Now you need to scale it — the product, the team, and the infrastructure — without the wheels falling off.

We've helped 15+ startups navigate this transition. Here are the 5 decisions that matter most.

Your instinct is to hire 5 more developers. Don't. Hire a VP of Engineering (or a strong Engineering Manager) first. Why?

Going from 4 to 9 developers without management structure creates chaos. No code review standards, no sprint planning, no architecture decisions, no hiring process. You'll hire fast, ship slow, and accumulate debt that takes years to pay off.

The right sequence: VP Eng (month 1) → establish processes (months 2-3) → hire developers with a proper pipeline (months 3-6). The VP Eng pays for themselves by preventing $500K+ in bad hires and rework.

If your deployment process involves SSH-ing into a server and running git pull, fix this immediately. Every manual deployment is a risk: wrong branch, missing migration, forgotten environment variable, no rollback.

Target state: Merge to main → automated tests run → builds automatically → deploys to staging → one-click production deploy with automatic rollback. This should take a senior developer 2-3 days to set up. It saves hundreds of hours over the next year.

The #1 scaling bottleneck for growing startups is the database. Your dashboard queries (reads) and your transaction processing (writes) compete for the same resources. At 10K+ concurrent users, this becomes a real problem.

The fix is simple and cheap: Add a read replica. Route dashboard/reporting/search queries to the replica. Keep writes on the primary. Most cloud databases offer this as a checkbox. The cost: $50-200/month extra. The benefit: 2-3x more headroom before you need to re-architect.

If you learn about outages from customer support tickets, you're already behind. You need three things:

Uptime monitoring: External service that hits your health endpoint every 60 seconds. Alerts via Slack/PagerDuty when it fails. Cost: free (UptimeRobot) to $20/month.

Error tracking: Sentry (or similar) catches every unhandled exception in production, with stack traces, user context, and frequency. Cost: free tier handles most startups.

Business metrics dashboard: Real-time view of signups, orders, revenue, and active users. When a deploy causes signups to drop 50%, you want to know in minutes, not days. Cost: build it yourself or use Grafana ($0).

In 6 months, you'll have 3 new engineers who weren't there when you chose PostgreSQL over MongoDB, or decided to use server-side rendering, or picked Stripe over Razorpay. Without documentation, they'll either ask the same questions repeatedly or make conflicting decisions.

Architecture Decision Records (ADRs) are short documents that capture: what was decided, why, what alternatives were considered, and what trade-offs were accepted. They take 15 minutes to write and save hours of onboarding and debate.