Turn engineering metrics into better results

Understand what your teams and agents deliver for the effort and tokens invested. Use decision-grade metrics to improve speed, throughput, and quality.

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trusted by high growth startups and the fortune 500 alike

See how work flows through your SDLC

Understand every stage of the development lifecycle—from issue created to PR merged. Get velocity, PR cycle time, DORA, sprint metrics out of the box, and catch bottlenecks before they slow delivery.

sdlc

Ask Src

Organization

Last 3 months

Benchmark:

Ind. P50

Issue Lifecycle

Coding

1.5h

↑35%

P50: 1.8h

Awaiting First Review

2.3h

↑4%

P50: 2.1h

Reworking

2.6h

↑20%

P50: 2.2h

Idling

0.8h

↓20%

P50: 1.2h

Deploying

0.2h

↓30%

P50: 0.3h

PR Lifecycle

Delivery

31.2 h

↑78%vs previous period

12d

18d

24d

Apr
27

May
19

Jun
10

Jul
2

Jul
23

New chat

Why did this jump so much in the last quarter?

Tasks

1 of 1 completed

Worked for 3m 37s

Todo list updated

Todo list cleared

What happened: it's spike-driven, not a trend

The p50 (median) is 0 every single week — meaning most PRs have zero rework. The increase shows up entirely in the long tail. A handful of PRs with very high rework times spiked the p90 into the 20+ hour range multiple times in Q3.

Who's driving it: Engineering Platform team

(7.65h → 10.02h avg), accounting for almost all of the org-wide increase. Every other team was flat or improved:

Reworking (p90) — Weekly Trend, Q2–Q3 2026

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Spot recurring quality problems

Understand whether faster delivery, including AI-assisted code, is coming at the cost of quality, so you can catch a rising defect rate before it compounds.

Demystify team load balance

See how work is distributed across your team to identify uneven workloads and where bottlenecks may occur.

~30%

reduction in pull request cycle time over the year

Zeta Global

150 → 225

Weekly code reviews completed after rebalancing

Coalesce.io

Understand what drives agent effectiveness

Span runs structured evals on agent traces and links sessions to PRs, so you can see where agents perform well and where prompting, coding environment, or validation practices need adjusting.

Insights

28% of traces scored low on Prompt Clarity (↓ 11%)

Prompt Clarity

Quality Stewardship

Environment Readiness

Summary

41% of traces scored low on Prompt clarity in last 30 days (↓16%). Most gaps occur when the first turn skips success criteria or repo context, requiring extra turns to finish.

3.5

Jun 29

Aug 17

Sep 28

Theme details

Pre-cache the Go 1.26.5 toolchain and gotestsum so make test runs offline

Provision

auspex

Private by default

Raw agent sessions are private to each developer unless they choose to share them. Trace metadata and eval summaries are aggregated and made available only at the team or organization level.

Improve the harness your agents depend on

Insights

28% of traces scored low on Prompt Clarity (↓ 11%)

Prompt Clarity

Quality Stewardship

Environment Readiness

Summary

41% of traces scored low on Prompt clarity in last 30 days (↓16%). Most gaps occur when the first turn skips success criteria or repo context, requiring extra turns to finish.

3.5

Jun 29

Aug 17

Sep 28

Theme details

Pre-cache the Go 1.26.5 toolchain and gotestsum so make test runs offline

Provision

auspex

"Span gives us a clear view of our engineering time and budget. We now have real data showing how our teams and processes are performing, and we use those insights to ship better products."

Span gives us a clear view of our engineering time and budget. We now have real data showing how our teams and processes are performing, and we use those insights to ship better products."

Scott Woody

VP of Engineering

Metronome

SecurityScorecard

Improve with intention

Understand performance in context

Set targets and stay on track

Compare performance with teams of a similar size to prioritize improvements and establish expectations for your teams.

PDLC

Time to first review

Ask Src

Organization

Benchmark:

Ind. P50

Time to first review

14.9h

↑15%vs previous period

Jul 1

Jul 8

Jul 15

Jul 22

Jul 28

Aug 4

Aug 11

Aug 18

Aug 25

Sep 1

Industry P50

Breakdown

Group by:

Team

Name

AI review load in previous period

AI review load

Organization

2.11

3.32

Core

2.11

2.59

Understand performance in context

Compare performance with teams of a similar size to prioritize improvements and establish expectations for your teams.

Set targets and stay on track

Ask Src to investigate changes, summarize progress, or set target thresholds with alerting.

Empower your team to run

Protect maker time

Maximize flow by streamlining meetings and reducing fragmented time.

Accelerate ramp-up

Spot early delivery patterns and ensure new hires ramp quickly as you scale.

Turn engineering metrics into better results

Turn engineering metrics into better results

See how work flows through your SDLC

See how work flows through your SDLC

Spot recurring quality problems

Demystify team load balance

~30%

150 → 225

Understand what drives agent effectiveness

Private by default

Improve the harness your agents depend on

"Span gives us a clear view of our engineering time and budget. We now have real data showing how our teams and processes are performing, and we use those insights to ship better products."

Span gives us a clear view of our engineering time and budget. We now have real data showing how our teams and processes are performing, and we use those insights to ship better products."

Scott Woody

Improve with intention

Improve with intention

Understand performance in context

Set targets and stay on track

Understand performance in context

Set targets and stay on track

Empower your team to run

Empower your team to run

Protect maker time

Accelerate ramp-up

Direct time and tokens toward your highest priorities

Direct time and tokens toward your highest priorities

Direct time and tokens toward your highest priorities