Why Engineering Teams Lose Velocity After 50 People (And What Actually Fixes It)
The playbooks that got you to 50 engineers will break at 100. Here's what we've seen work—and what doesn't—across a dozen scaling teams.
We're an engineering consultancy for companies that need to build something real—not a proof of concept that dies in staging.
Things we've learned building software for companies across fintech, healthcare, and e-commerce.
The playbooks that got you to 50 engineers will break at 100. Here's what we've seen work—and what doesn't—across a dozen scaling teams.
Most AI projects fail in the last mile. After 14 production deployments, we've learned where the real problems are—and they're not where most teams look.
Platform teams are supposed to make everyone more productive. Instead, they often become bottlenecks. Here's the pattern we see and how to avoid it.
We've done 8 cloud migrations in the past 3 years. Here's what actually takes the time—and it's not what the vendors tell you.
Everyone says they want product engineers, not feature factory workers. But when you look at how teams actually operate, the distinction gets blurry.
A few things we've shipped recently. Names changed where clients prefer it.
Built an ML-powered routing system that reduced fleet fuel costs by 18%. Took longer than planned because integrating with their dispatch system was harder than scoped.
Migrated a legacy insurance platform to AWS. Zero customer-facing downtime, though we had three internal incidents during the parallel-running period.
Built a custom e-commerce platform for a beverage distributor cooperative. Revenue grew 8x in 14 months—slower than projected, partly due to shipping complexity we underestimated.
Added AI-powered candidate matching to an existing staffing platform. Cut time-to-match from 12 days to 5.4 days. The hard part was getting recruiters to trust the recommendations.
We're not the right fit for everyone. But if you need experienced engineers who can ship production software, let's talk.
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