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You don’t need a psychic dog to measure the impact of AI coding tools

Tim is a good boy. Tim is not a data source.
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‘Promising’ is not a metric

At some point in the last year, your engineering organization went all-in on AI coding tools. Probably more than one. The engineers seem to like them, and you’ve told the board the early signs are ‘promising’.

What you haven’t been able to tell them is exactly what those tools are doing to cycle time, throughput, or the quality of the work coming out the other side. You know adoption is up, sure. You know the team is positive about it. Beyond that, things get blurry.

It’s tempting to call it good enough. The problem is, “the engineers say it’s useful” gets harder to defend as the license costs compound and finance starts asking for specifics.

Luckily, there’s a way to measure AI impact without involving a labrador retriever with magical properties.

A detailed comparison

Here’s all you need to know when you’re deciding between acquiring a psychic pooch and investing in Swarmia, the engineering intelligence platform you can trust.

Change target:
The signal hound
The signal hound
Swarmia
Data source
One medium-sized dog.
GitHub, GitLab, Jira, Linear, and your AI tools.
Measurement methodology
Bark frequency mapped to trend lines by an eager colleague with a marker pen.
A full comparison of key engineering metrics before and after AI tool adoption. Also includes productivity metrics for agentic work.
Reproducibility
Low. Sneezing introduces noise. Tail-chasing renders data unusable.
Consistent, defensible, runs continuously in the background.
Breakdown by team
Woof.
Yes — by team, engineer, repository, and AI tool.
AI tool comparison
Not supported. The dog is not aware of the distinction between Copilot and Cursor.
Compare impact across different AI tools and agents.
Confidence interval
Wide. Especially during the spinning phase.
Narrow. Based on actual data.
Leadership-ready reporting
The bone-shaped graph has not been well received.
Yes.
Jimmy’s involvement
Essential.
Optional.
Engine
TrueLayer
Matillion
AdCellerant

250+

engineers at Engine get the data they need, without having to change the way they work

Read more→

“What I like about Swarmia is that all you have to do is connect it to your existing tools and then you get a whole bunch of information — without having to change your process or go through hours of consulting to make sure that the labels on the tickets are just right.”

Egan Royal, SVP Engineering at Engine

Egan Royal

SVP Engineering
Engine

Egan Royal, SVP Engineering at Engine

“What I like about Swarmia is that all you have to do is connect it to your existing tools and then you get a whole bunch of information — without having to change your process or go through hours of consulting to make sure that the labels on the tickets are just right.”

Egan Royal

SVP Engineering
Engine

Swarmia is a better way to measure the impact of AI coding tools and agents

Swarmia measures the actual impact of AI coding tools on your engineering org — so you can see what’s working, what isn’t, and what to do about it. Get before and after comparisons, team-level breakdowns, agent-specific metrics, and data you can put in front of leadership.
Measure AI impact with Swarmia→

Don’t be like John

He means well, but his methods range from slightly eccentric to seriously unhinged.
The magic 8 ball→
Believe it or not, there are better ways to decide which software initiatives should be capitalized.
The séance→
You could summon the spirits to let you know which initiatives are stuck. But maybe don’t?
Rock, paper, hotfix→
Because you really don’t need a made-up game to decide whose team will take on the next big project.

There’s a better way to run your engineering organization

It’s called Swarmia, and we’d love to show you around.

Get a demoSign up for free