AI-First Transformation

How much is not going AI-first costing you?

Your team, your timeline, your numbers: what the old way costs, and what the same outcome shipped in weeks is worth. Every constant cited. All figures USD.

Value of going AI-first

—

Old-way build cost

AI-first build cost

Cost of the delay

Shipped earlier by

0 mo

1 · Your current plan

Team size

devs

Planned timeline

months

Cost / dev / month

fully loaded: salary + employer costs + overhead. Default = US median dev salary + ~33% employer costs (BLS)

AI-first delivery

months

same team, same scope, agents do the labor. Pre-filled at a conservative 10× faster (measured cases run 100×+)

Advanced: smaller team on the AI-first build

Team on the AI-first build

devs

default: your full team. Our measured case ran on 1 engineer instead of 3. The freed people ship your next product.

2 · What each month of delay costs (McKinsey)

McKinsey: a product that ships 6 months late earns ~33% less profit over five years, which works out to ≈5.5% of its profit lost per month of delay. So the price of a delayed month comes from what your product is expected to earn:

Your 5-year profit forecast

unsure? keep the default (2× build cost, a deliberate floor)

Cost of one month of delay

$/mo

= 5.5% × your forecast, or type your own

Include delay cost (recommended). Uncheck to count build cost only.

Grounded, not invented: just two cited constants, McKinsey's 5.5% per month and the 2× profit floor. Full math and sources below; change any input and everything recomputes.

The full math, step by step, from your inputs

Where these numbers come from

Grounded in a real delivery, then deliberately discounted. Here's the case: a system that took a 3-developer team 1.5 years was rebuilt better in 2 weeks. One engineer. Non-technical teammates shipping alongside, agents doing the labor. That's 100×+ less human dev time. The defaults here assume a tenth of that, 10×, to stay on the skeptical side.
How the pre-filled delay cost is computed. McKinsey's model prices one month of delay at ≈5.5% of a product's five-year profit (33% ÷ 6 months). That's a share of what the product will earn, not a markup on what it costs. Since earnings need an estimate, the forecast field defaults to a floor of 2× build cost (below that, the build wouldn't be approved), so replace it with your real forecast. If anything the result understates the truth: months gained at launch are peak market-window months. They compound adoption, strengthen a funding round, and free the team for the next product.
Time beats budget, by an order of magnitude. McKinsey's product-development model: a product shipping 6 months late earns ~33% less profit over five years; shipping on time but 50% over budget costs only ~4%. McKinsey, via TCGen
Cost of delay is measurable, and large. Maersk Line measured $200K+ per week of delay cost on a single queued feature (roughly $8M while it waited in line). Black Swan Farming
Intuition misses this by 50 to 1. Reinertsen's research: gut estimates of delay cost inside one team spread 50:1. That's why this page asks for your numbers instead of asserting ours. Cost of delay · PMI
Early delivery pays twice: the share premium is permanent. Across 129 brands in 36 categories, the second entrant into a market averages only ~71% of the earlier entrant's share, and the sixth ~45%. Months of earliness buy market share that later entrants never claw back. In software specifically, DORA's research finds teams with elite delivery speed are ~2× more likely to meet profitability and time-to-market goals. Order-of-entry research (Urban et al.) · DORA
Speed decides who leads the market. Across ~500 brands in 50 categories, 47% of first movers failed. The lasting winners were early leaders: fast entrants who reached scale first, taking ~3× the pioneers' share. Months of delay is how that seat is lost. Golder & Tellis

Built by Igor, the engineer behind the numbers