They count PRs.
We measure the work.
Jellyfish tracks what your engineers shipped — PR counts, commit velocity, DORA metrics. That was enough before AI. It isn't now. When agents are writing the code, the PR is a lagging indicator. The work happened earlier, in the conversation between engineer and agent where quality was made or broken.
A PR is not a unit of work. It's a unit of output.
Jellyfish Counts Output.
Maestro Measures the Work.
Jellyfish was built when pull requests were the atomic unit of engineering work. Count enough PRs, measure enough cycle time, track enough DORA metrics, and you had a picture of your team. That picture was always incomplete — it stopped at the artifact.
AI made the gap impossible to ignore. Your engineers now direct agents in tools like Claude Code, Cursor, and Copilot. That conversation — the session — is where they scope problems, evaluate proposals, verify outputs, and decide what to accept. Two engineers can ship identical PRs: one from a 12-turn session with careful verification, one from a 90-turn sprawl where nothing was checked. Jellyfish sees the same PR. Maestro sees the difference.
The PR Boundary vs. Inside the Work
Jellyfish sees the PR boundary: when it opened, how long it took to merge, how many commits, how many comments. It's accurate. It's just not where the quality decisions happened.
Maestro sees inside the work: how your engineers are using AI tools, whether they're prompting with discipline or accepting suggestions blindly, who is developing craft and who is stuck in copy-paste loops.
Two Philosophies
What Jellyfish Tracks
- PRs merged, cycle time, commit frequency
- DORA metrics: deployment frequency, lead time, MTTR
- Throughput dashboards and velocity trends
- Who shipped what, and when
Useful. But it stops at the PR boundary.
What Maestro Measures
- How your engineers use AI tools — quality, not just volume
- Who is developing AI craft vs. stuck in copy-paste loops
- Whether your team's skills are improving or plateauing
- What your best engineers do — made visible and teachable
Maestro sees what's inside the work.
Read the full argument.
Eng metrics are dead. →See inside the work
Join engineering leaders who moved past counting output and started measuring craft. See how Maestro surfaces intelligence across your org — who's using AI well, who needs coaching, and what your standards actually are.
Trusted by engineering leaders at Runway, AimLabs, and more