They see what AI produced.
We see how you directed it.
Span's AI Effectiveness Suite traces agent interactions all the way to the pull request. That's useful — it tells you what AI produced and what it cost. But cost visibility and quality visibility compound differently. The question that tells you whether your org is getting better at AI is whether your engineers are learning to direct agents well. That's where Maestro looks.
Cost is a metric. Craft is a capability.
Span Ends at the PR.
Maestro Starts Inside the Work.
Span does something genuinely useful: it captures the trace from agent prompt to pull request. You can see token cost per PR, which code lines were AI-generated, where friction occurred. That's real observability into what AI produced.
But it's still artifact-first. Two engineers can ship identical PRs — one from a 12-turn session with careful problem scoping and edge case verification, one from a 90-turn sprawl where they accepted suggestions they didn't understand. The PR looks the same to Span. Maestro sees the difference — and more importantly, tells you which engineer is building the craft that compounds.
Agent Traces → PR vs. Inside the Work
Span gives you a system of record for developer-agent interactions: token cost per PR, AI code attribution at the line level, prompt-to-PR correlation. It's the observability layer for what AI produced.
Maestro gives you quality intelligence on how your engineers are directing AI tools. How they frame problems. Whether they verify outputs. Whether they're developing the craft that makes AI a force multiplier — or accepting suggestions in ways that create risk.
Two Philosophies
What Span Tracks
- Agent traces correlated to pull requests
- Token cost per PR and AI code attribution
- Workflow friction in developer-agent interactions
- What AI produced and what it cost
Useful for cost and output visibility. Stops at the artifact.
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 whether your engineers are getting better.
Read the full argument.
Eng metrics are dead. →See whether your engineers are getting better
Join engineering leaders who moved past measuring what AI produced and started measuring whether their engineers are learning to direct it well. See how Maestro surfaces intelligence across your org — who's upleveling, who needs coaching, and what your standards actually are.
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