Span.app is the AI-native developer intelligence platform that makes big engineering teams feel small. Get a complete picture of engineering impact and health.
Which teams are using AI most effectively? Why did defect rates increase this month?
Engineering leaders currently spend hours digging through a dozen dashboards to answer those questions. They shouldn't have to.
Src, Span's AI agent, makes your entire engineering system
Tl;dr: We deleted our product homepage.
At a previous org, we had a KPI to increase key actions, so we threw a bunch of stuff onto the product homepage to drive it. It technically worked, and the number went up enough to call it a win.
At @Span_App, I didn't want to chase an
Quick demo of @Span_App's new product, Src! Customers are already using Src to:
- Understand ROI of AI tokens on projects and types of work
- Run scenario and capacity planning
- Kick off cost capitalization cycles
- ... and more!
Different parts of a product, and different kinds of companies, are meant to move at different paces.
@TownAI co-founder and CEO @jgreze stopped by our Stack Trace podcast to discuss how to match shipping velocity with what you're building.
Stop talking about tokens and come waste some the old-fashioned way.
Span is hosting Tokenmaxxing Arcade Night on July 1st at Thriller Social Club in SF, just 10 minutes away from @aiDotEngineer World's Fair.
From 6-9pm, spend tokens all you want. We won't tell your CFO.
What happens when you tell a crew of senior engineers to stop writing code by hand for a month?
Jeffrey Wescott, VP of Eng at @ExpelSecurity, ran the experiment. For the verdict, you'll have to hear him on Episode 1 of Stack Trace, our new podcast launching today.
AI doesn't write buggier code. It writes bigger PRs.
When we controlled for PR size across 248,099 pull requests, AI's effect on defect rate disappeared. What survived: AI-assisted PRs run roughly double the size of mostly human-written ones.
The arrow runs AI → bigger PRs →
3 weeks to 3 days.
That's how much @intercom cut their quarterly software capitalization workflow after partnering with Span.
Building alignment between engineering, finance, and ops teams can be this easy.
Previously every quarter, @intercom spent close to three weeks collecting and attributing work for software capitalization. With Span, this now takes three days.
Span’s AI-assisted mapping automatically categorized engineering work, replacing manual data entry and verification
Today, @linear is partnering with @Span_App.
Linear is where teams plan and build. Span shows what actually happens after. What shipped, how long it took, and where the effort went.
Putting the two together gives teams a clearer picture of real work. If your team already runs
We’re partnering with @linear to connect planning to execution.
See how work moves from idea to shipped code, grounded in real signals from engineering activity, including how AI-assisted work shapes outcomes in practice.
If you run on Linear, explore the integration:
