3,518 Intern Applications Checked In 4:54

You cannot from the post. No precision, recall, false-negative rate, or scoring rubric is published, and the author adds that the team is still manually checking applications and tweaking the process. He explicitly says this was the first run of the review system and not the final shortlist.

Unclear. The post reports 3,518 applications checked in 4 minutes 54 seconds with an estimated Jev cost of $0.4125, but it never breaks out parsing, document extraction, or queueing time. Read 4:54 as an end-to-end number for their in-house console, not a per-decision latency.

The post says only that the goal was finding evidence of real work at scale, and that every square in the console is a real SDE intern application. It does not list the inputs the harness reads or how a candidate is scored, so you would be rebuilding the pipeline from nothing.

A triage filter, by the author's own account. Twenty surfaced for human review out of more than 4,000 received, and he preempts the reading that this replaced recruiters by saying people are still doing the checking. No autonomous reject or ranking policy is described.

Shubh Srivastava, who describes himself as a founding member at tryAlanAI, where more than four thousand people applied for a single SDE internship. A co-post by Prasad Pilla frames the application flood, so the review console is an in-house tool at a startup rather than a service sold to recruiters.

A grid where every square is a real SDE intern application, per the post. The team says you can watch the shortlist change in real time as the run progresses, so the console is a live view of decisions landing rather than a static report generated afterward.

Nothing in the post suggests it is available. There is no repository, package name or deployment detail, and the author describes it as an in-house review console built for their own applicant flood. Reusing it would mean rebuilding the pipeline, including whatever parses and extracts from each application.