Spendassay Research
What the evidence actually says.
Spendassay publishes the research its method rests on, including the findings that cut against us. Every study is linked to its primary source and reported with its effect size, so you can check the claim rather than take ours.
What Spendassay Research publishes
Evidence reviews
Vendor-neutral reads of the published research, effect sizes included, and the findings that argue against us reported alongside the ones that do not.
Benchmarks
Citable reference tables. The load-bearing column is the basis for each row, because a benchmark without a population behind it is an anecdote with a number on it.
The AI tool price index
Published prices for every tool in the catalog, each stamped with the date it was last read against the vendor's own page. Where no price is published, we say so.
Methodology
How every number is built, layer by layer, and how sure each one is. The standard the rest of this work is held to.
The byline is the company, not a persona — how that work is produced, and who runs it.
Reviews
Does AI actually make developers faster?
The published evidence, linked and dated, with effect sizes and a comparison table. Includes the results that cut against the case for AI tooling, because a review that only cites the favourable studies is marketing.
The sources we cite
8 published studies underpin the method. Each is listed with its finding on the methodology page, and compared side by side in the review above.
| Source | Year | Measures |
|---|---|---|
| METR | 2025 | Task completion time, with and without AI tools |
| Faros AI | 2026 | Delivery quality against AI-accelerated throughput |
| GitClear | 2025 | Code churn and duplication over time |
| DORA | 2025 | DORA delivery and stability metrics under AI adoption |
| CACM · Ziegler et al. | 2024 | Perceived productivity vs. acceptance rate |
| LinearB · APEX | 2026 | Adoption curve and payback window |
| Microsoft · Viva | 2026 | Minimum group size for reporting |
| DX (now part of Atlassian) | 2026 | Longitudinal engineering velocity across dimensions |
Measure your own numbers, not an industry average.
The research says the effect varies by team. That is the argument for measuring yours.