Time to first ship, year-one cost, hiring risk, and the case for the hybrid path: YATE Web ships first, you hire after. Numbers based on US/EU senior salaries.
By YATE Web editorial · Senior engineering team · Updated
TL;DR
Building an in-house AI team takes 4 to 9 months to first ship: 3 months hiring (tech recruiter $25K plus sourcing), 4 to 8 weeks onboarding, 6 to 12 weeks first sprint. Total year one: $850K to $1.4M for a team of four. YATE Web ships first MVP in 6 to 10 weeks at $18K to $50K, with full methodology transfer if you decide to hire later. Build in-house when AI is your moat. Use YATE Web when AI is a vehicle for a non-AI product, or when you want to start in-house with proven patterns.
Side by side
Eight dimensions where 'build vs buy' decisions actually diverge. The cost line alone usually decides; everything else is whether you have the runway and the leadership to make that cost worth it.
| Dimension | In-house team | YATE Web |
|---|---|---|
| Time to first ship | 4 to 9 months | 6 to 10 weeks |
| Year-one cost (team of 4) | $850K to $1.4M | $140K to $300K |
| Hiring risk | High in AI engineer market | None |
| Methodology development | 6 to 18 months internal | Day 1, 94 templates included |
| Knowledge concentration | Team-internal, fragile | Documented, transferable |
| Replacement risk on key hire | Critical | Distributed across senior pool |
| AI vendor strategy | DIY | Vendor parity by default |
| Ramping cost | Real (40-60% productivity in month 1-3) | None |
When to choose in-house AI engineering team
Build in-house when AI is the company, not the feature.
When to choose YATE Web
YATE Web is the right call when speed and proven patterns matter more than ownership.
12-month TCO
Year-one cost for a team of four senior AI engineers (US/EU). Hiring fees, onboarding loss of productivity, infrastructure, salaries, stock, benefits, and a recruiter retainer.
| Stage | In-house team | YATE Web |
|---|---|---|
| Recruiter fees (4 hires) | $80K to $120K | $0 |
| Onboarding loss (3 months) | $120K productivity hit | $0 |
| Salaries (4 engineers) | $640K to $880K | $0 |
| Stock, benefits, payroll tax | $160K to $240K | $0 |
| Infrastructure + tools | $30K to $60K | Included |
| YATE Web MVP + retainer | $0 | $140K to $300K |
| Year-1 total | $850K to $1.4M | $140K to $300K |
The hidden cost is the time-to-ship gap. Six months without revenue or product feedback is itself worth $200K to $1M depending on your market.
In practice
The most common engagement shape we run is build-then-transfer. YATE Web ships the first product on the methodology library, documents the architecture and prompt patterns, then runs an onboarding programme for your first internal hires. By month 6, the team is yours; by month 12, the methodology has been adapted to your domain and YATE Web is on retainer for review only. Total year-one cost is roughly half of pure in-house with no time-to-ship gap.
Code is easy to inherit; methodology is hard. An in-house team that inherits a working product but no documented prompt-engineering process spends 3 to 6 months recreating decisions that were already made. Transfer of the library, the cost model templates, and the eval suite is what compresses that recreation cost. We have run this transfer four times; the average internal team reaches feature-parity productivity in 8 to 10 weeks.
FAQ
We do not sell engineer placements directly, but we partner with a small number of clients on right-of-first-refusal agreements after 12 months. Specifics depend on the engineer and the engagement.
30-day post-launch guarantee covers critical fixes at no charge. Beyond 30 days, the standard Quarterly Sprint engagement covers continued work at sprint-fixed pricing.
Both. Methodology Library transfer is included in MVP Sprint engagements and above. The library transfers under your account with naming, tagging, and references intact.
Build phase is sprint-fixed (typical $80K to $180K depending on scope). Transfer programme is a flat $35K covering documentation, paired sessions for the first 2 internal hires, and a 4-week shadow period.
Same languages, same frameworks, same quality bar. The difference is documentation density: YATE Web code arrives with architectural decision records, an eval suite, and a prompt-engineering guide. Most in-house code arrives with whatever the original engineer remembered to write down.
Free, 48-hour SLA, no sales call
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