Augment and Jellyfish partner to make AI impact measurable

Most engineering leaders we talk to ask some version of the same questions:

• “Our teams feel like they’re shipping faster with Augment, how can I prove it?”
• “How do I justify this AI spend to my CFO?”
• ​​“For every dollar we’re spending on AI tools, what are we getting back in throughput or quality?”

Augment brings agents to the entire SDLC–from IDE, CLI, Intent (our new multi-agent orchestration workspace), code review and more. With Jellyfish AI Impact, leaders can now see how that Augment usage translates into real gains in productivity and delivery.

Customer spotlight: Taskrabbit on measurable AI impact

The key metrics for leaders to prove AI results

With Augment telemetry surfaced in Jellyfish, leaders can move beyond “AI usage” and into AI impact. Here are a few of the views you can get.

1. Cycle time and PR flow

• Time from PR open to merge, broken down by:
  • PRs reviewed with Augment Code Review versus without
  • Teams that use Augment heavily versus lightly
• Reopen and rework rates for Augment-touched changes compared to baseline

This tells you whether Augment is actually unblocking reviews and speeding up delivery, not just leaving more comments.

2. Code quality and stability

• Defects per change set before and after Augment adoption
• Incidents or rollbacks tied to areas where Augment was (or was not) used
• Hotspots where AI-assisted refactors are reducing tech debt instead of creating churn

3. Developer focus and workflow health

Because Jellyfish already understands how work moves through your SDLC, you can divide up impact by:

• Team, repo, or project
• Type of work (features, maintenance, incidents, migrations)
• Stage in the lifecycle (new code, review, refactor, cleanup)

You can see where Augment is freeing up engineers to work on high‑value projects and where adoption is low enough that teams still feel stuck in “toil.”

4. ROI and vendor comparison

Jellyfish shows data across tools, so you can look at Augment alongside other AI investments and ask:

• For every dollar spent on AI tools, which ones are tied to:
  • Faster throughput
  • Fewer defects
  • More predictable delivery
• Where is Augment the primary driver of impact, and where are other tools overlapping?

This turns “we think AI is helping” into a story you can take to finance and the executive team.

Why this matters for Augment customers

If you’re already using Augment and Jellyfish, this partnership gives you a cleaner way to:

• Prove the impact of the practices you’re rolling out (code review, CLI automation, automated issue resolution)
• Spot teams that are finding new levels of productivity with Augment and model their habits elsewhere
• Catch pockets where AI is adding friction instead of removing it

If you’re evaluating Augment, Jellyfish gives you a neutral, system‑level view of whether it is working. You get the metrics without having to build your own reporting.

Get started

The Augment + Jellyfish integration is powered by our Analytics API, which makes your Augment usage data available to any analytics or engineering intelligence platform. Whether you use Jellyfish, build custom dashboards, or integrate with other providers, the same telemetry is available through our API.

If you’re already using Augment and want clearer visibility into its impact, or you’re evaluating AI tooling: Talk to our team about the Augment + Jellyfish AI Impact or learn more about what Augment can do across your SDLC here.