Stop paying for stale documentation
Built from your team's size, salaries, and AI adoption, with every multiplier backed by research from Atlassian, GitLab, and Stripe. Includes a PDF report you can share with your team
Common questions
It's an honest model, not a precise forecast. The multipliers (20% eng interpretation, 8h/week PM maintenance, 70%/90% recovery) come from Specsight's research with product teams plus published data from Atlassian, GitLab, and Stripe. Real teams sit in a 60–80% / 80–95% range on recovery; we use the midpoints here so the page shows a single dramatic figure. The full sourcing is on your report, under Where these numbers come from.
Documentation drift is a cross-functional cost. Engineering loses time interpreting unclear specs; PMs lose time maintaining the specs themselves. Specsight reduces both — we are the documentation, so PM maintenance time effectively goes away. We derive your PM count from a typical SaaS ratio (1 PM per 8 engineers) and show it openly in the breakdown so the math is transparent.
AI-coded changes ship faster than humans can update docs — more PRs per week, more behaviour changes, more drift volume. We model this as a 1.0× / 1.15× / 1.3× multiplier on the engineering interpretation cost. This is Specsight's hypothesis; we're honest that there's no cited public study yet backing the exact multipliers. If you have AI tools but disable them mid-flow, pick low.
Three pages: the receipt on the cover — what drift costs and what you'd get back — the full math with sources and what the cost means in human terms, and three drift-reduction tactics tailored to your team's AI adoption level. People who run our calculator forward the PDF to their CTO or board — it's formatted to make the budget case for you.
Stop paying the drift tax
Specsight reads the code and shows the whole company how the product behaves and how it changes, release by release