One person covers 8 domains
Backend, AI/ML, systems, security, frontend, data, IoT, DevOps - where the legacy model needs 4-6 specialists. AI doesn't just make you faster at what you know; it makes adjacent domains reachable.
The legacy way bills you twice: a fortune to build it, then a meter that runs forever to host it. We already built the platform for five cents on the dollar, it runs on a box in your office, and you can unplug it the day after the election.
Go to a normal dev shop for one custom data app: discovery runs $15K-$40K before a screen ships, the build runs $50K-$150K+, agencies bill $100-$300/hour, then maintenance is 15-25% of the build every year after. Now price the whole platform the old way - a fully-loaded 9.5-person team, ~9 months - and you land at $855K to $1.71M, headline $1.28M.
actual build cost - $60K ops + $800 AI
one operator, AI as co-pilot
below the $1.28M legacy estimate - $1.22M saved
projects shipped / repositories, 15,700+ commits
That $1.28M of build cost is sunk, and it was never $1.28M. You don't pay to build a platform - you pay to compose a copy of one that already exists. Here's why that's structural, not magic:
Backend, AI/ML, systems, security, frontend, data, IoT, DevOps - where the legacy model needs 4-6 specialists. AI doesn't just make you faster at what you know; it makes adjacent domains reachable.
Versus ~35% for a legacy dev once you subtract meetings, standups, reviews, and context-switching. Every message is productive work - no ceremony between idea and production.
Legacy onboarding is 2-6 weeks per hire, with knowledge lost at every handoff. Here the whole codebase stays loaded - no re-explaining, no documentation lag.
The build is one-time. The cloud bill is forever - and you never own any of it: not the software, not the servers, not the right to look at your own data without paying for the privilege.
Hosting a real multi-service data app runs $18K-$60K a year - and the build was the one-time part. The cloud bill is the part that never stops.
Data leaving the cloud is billed by the gigabyte. For the price of moving 1 TB out of AWS, you could rent a whole server elsewhere for a month.
A hundred line items no one on staff can parse. A tool quietly reading your data every fifteen minutes turns a $4K month into a $9K month - and you find out after.
A tool you hammer in September-November still bills you every quiet month from December to August. You pay full freight to keep an idle machine warm.
The expensive part is already paid - for $61K, not $1.28M. So the economics flip on both bills.
A dashboard or tool is assembled on roads we already own - days, not months. The expensive part of software is the build, and that cost is already paid.
A box, or a few, in your office or a closet. No AWS account, no per-gigabyte tolls, no metered database.
50+ services on one local machine talk at no charge. In the cloud that same chatter is a billed line item - same richness, none of the network tax.
Election's over? Power it down. The bill drops to the cost of electricity, and a powered-off box has zero attack surface.
If it's trapped in a vendor's cloud today, we mirror it into your building - yours to query, for free, without asking permission.
A platform with millions of bursty, global users genuinely needs the cloud's elasticity. A team building eight separate enterprise products at once genuinely needs eight specialists. A regional or statewide political shop with a seasonal, known workload is neither- it's paying enterprise prices, on both bills, for problems it doesn't have.
Cloudless campaign tech. Free yourself from the meter.
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