> My rule of thumb has been that with every order of magnitude of growth you should revisit your architecture, and determine whether it can still support the next order level of growth.

The last hyper growth startup I worked at grew 10x in scale every 2-3 quarters for nearly 3 years at meaningfully large scale (millions of monthly transacting users). In that time, the number of different business-lines/categories and amount of functional flows and their intersecting/overlapping complexity also grew multiple folds.

So, we were adding whole new things and throwing away old things and basically refactoring everything every 18-months. Without knowing consciously, the superpower we had was our ability to refactor large live systems so well.
In hindsight it became clear to me that our ability to do this hinged on a few different things:

1. A critical mass of engineers at both senior and junior levels understood the whole systems and flows end to end. A lot of engineers stayed with their own team developing strong functional-domain understanding. Similarly a good number of senior engineers rotated across teams.

2. The devops culture was extreme – every team (of 10-12 engineers) managed all aspects (dev-qa-ops-oncall etc) of building and operating their systems. This meant even very junior engineers were expected to know both functional and non-functional characteristics of their systems. Senior engineers (5-10 yr experience) were expected to evaluate new tech stacks and make choices for their team and live with the consequences.

3. Design proposals were openly shared and sought critical feedback. Technical peer reviews were rigorous. Engineers were genuinely curious to learn things, ask and understand things, challenge/debate things etc. Strong emphasis on first-principles thinking/reasoning and focusing on actual end-to-end problem-solving without being territorial or having dogmas was strongly encouraged and the opposite was strongly discouraged.

4. Doing live-migrations – we mastered the art of doing safe live migrations of services whose API schema or implementation was changing and of datastore whose schema or underlying tech was changing. We had a lot of different database tech migrations – from monolith SQL dbs, to NOSQL clusters to distributed SQL dbs and their equivalent in-memory dbs and caches.

Surprisingly, the things we didn't do so well but didn't really hurt our ability to refactor safely were:

1. Documentation – we had informal whiteboard diagrams photographed and stuck in wiki pages. We didn't have reams and reams of documentation.

2. Tests – we didn't have a formal and rigorous test coverage. We had end-to-end tests for load-testing and we had a small manual QA for doing end-to-end integration testing for critical flows. These came about a bit later – but trying to scale them effectively proved very challenging. But these were not seen as hurdles for doing refactors.

3. Formal architecture councils and formal approval processes – we didn't have these. Instead we had strong people to people connect and strong team level accountability – culturally people owned up their mistakes and do everything they could to fix things and do better next time. Humility was high.

Later, I worked at a large mature company with very large scale – and everything was exactly flipped on all the points above and any major refactors were a serious pain and migrations took forever and actually never completed. The contrast was very eye-opening and I realized in hindsight the above contributing factors.