AI Coding Agents Made the Code Fast. The Bottleneck Moved: 91 Days, Measured
Quick answer: in 90 days of our own git history, the median time from a request to committed code was 5.4 minutes across 18 timed cases. The work that took days was blocked outside the code: client material, terms to sign, acceptance, checks on the live system. If you outsource software, the timeli
Posted on Oct 25 • Originally published at devaland.com
Quick answer: in 90 days of our own git history, the median time from a request to committed code was 5.4 minutes across 18 timed cases. The work that took days was blocked outside the code: client material, terms to sign, acceptance, checks on the live system. If you outsource software, the timeline is now set mostly by preparation and acceptance, not by programming.
This week a Romanian software company said, in an interview published by start-up.ro on 29 September 2026, that 25 to 40 senior engineers working with AI could take over the work of roughly 100 offshore developers. The article itself notes that this is an internal scenario, without the type of project or the method behind the number. We wanted a figure we could show, so we measured our own work.
Devaland is a one-person company that builds software with AI coding agents, often in several sessions in parallel. We read the history of all 56 git repositories active between 30 June and 28 September 2026. We excluded the 1,648 automated commits (backups, regenerated pages, automatic updates), merges and generated files. For request-to-code time we used only the cases where the time of the request is recorded, which covers the last month: 18 timed cases.
The items that took days were not stuck in programming. A piece of work for a publisher took about two days, and the course platform was ready six days after its sales page was already public. In both cases the waiting sat outside the code: material from the client, terms to sign, acceptance, verification on the real system.
We also found an error of our own. A piece of work estimated at "about two focused days" took 10 minutes of actual programming. Day-based estimates for the programming part were too high by a factor of tens.
1. Ask what you need to prepare, not only how long the programming takes: the data, the access, the documents, who signs acceptance. That is where the timeline comes from.
2. Ask for an early first version that runs on your own data. If programming takes minutes, there is no reason to wait weeks for a first result you can judge.
3. Prefer a fixed price for an outcome described in writing. When code is written quickly, paying by the hour rewards slowness; a fixed price protects you.
4. Keep a human on verification. An agent writes fast and can be wrong with the same confidence. Automated tests, checks on real data and one person accountable for the result make the difference.
5. Distance matters less, overlap still matters. Most of the calendar is now spent waiting for answers, so a supplier in your own time zone, inside the EU, invoicing under the normal EU VAT rules, keeps questions and answers inside the same working day.
If you want to see what a system built this way looks like, our document analysis platform, where every finding links to the page it came from, can be tried without an account at getdealos.tech/sandbox. The way we take on work, as fixed-price projects, is described on the AI development page.
Originally published on devaland.com: AI Coding Agents Made the Code Fast. The Bottleneck Moved: 91 Days, Measured