Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
An enterprise service management platform building a workforce of customizable AI agents to take the ticket load off human service reps across IT, HR, and Legal departments.
Autonomous AI agents with multi-step reasoning chains have a cascading failure problem: a minor prompt tweak or tool-call variation can cascade into...
“Many teams treat evaluation as a last-mile check, but we made it a Day 0 requirement.”
Cloud-based work management platform for team collaboration and project tracking.
Framework and developer platform for building LLM-powered applications.
monday.com's Agent evaluation is part of this use case:
Related implementations across industries and use cases
Agent failures at 1M ops/day meant engineers stitching logs, traces, and code to diagnose. Now every decision links to a commit in one view.
Prompt iterations rubber-banded: each engineer's fix overcorrected the last. Evals are now a merge requirement—no eval, no commit.
Scattered spreadsheets couldn't catch AI hallucinations. Now, automated LLM judges evaluate every prompt change to block regressions.
Agent failures at 1M ops/day meant engineers stitching logs, traces, and code to diagnose. Now every decision links to a commit in one view.
Prompt iterations rubber-banded: each engineer's fix overcorrected the last. Evals are now a merge requirement—no eval, no commit.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Reaching a new market meant standing up another dubbing team. One API now dubs into 30+ languages; creators edit tracks before it goes live.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
An enterprise service management platform building a workforce of customizable AI agents to take the ticket load off human service reps across IT, HR, and Legal departments.
Autonomous AI agents with multi-step reasoning chains have a cascading failure problem: a minor prompt tweak or tool-call variation can cascade into...
“Many teams treat evaluation as a last-mile check, but we made it a Day 0 requirement.”
Cloud-based work management platform for team collaboration and project tracking.
Framework and developer platform for building LLM-powered applications.
monday.com's Agent evaluation is part of this use case:
Related implementations across industries and use cases
Agent failures at 1M ops/day meant engineers stitching logs, traces, and code to diagnose. Now every decision links to a commit in one view.
Prompt iterations rubber-banded: each engineer's fix overcorrected the last. Evals are now a merge requirement—no eval, no commit.
Scattered spreadsheets couldn't catch AI hallucinations. Now, automated LLM judges evaluate every prompt change to block regressions.
Agent failures at 1M ops/day meant engineers stitching logs, traces, and code to diagnose. Now every decision links to a commit in one view.
Prompt iterations rubber-banded: each engineer's fix overcorrected the last. Evals are now a merge requirement—no eval, no commit.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Reaching a new market meant standing up another dubbing team. One API now dubs into 30+ languages; creators edit tracks before it goes live.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.