How can you measure AI's impact on your organization?
Despite AI's impact on how developers work, the core objectives remain the same: delivering working software that solves real problems
Laura Tacho
CTO
Research & Insights
Introducing the AI Measurement Framework
A research-based approach for measuring the impact of AI in your organization.
Laura Tacho
CTO
How Snowflake’s DevProd team operates
The communication channels, rhythms, and principles that made Snowflake’s DevProd team one of the most trusted teams in the company.
Kali Watkins
Product Marketing
AI acceptance rate: Easy to measure, easy to misuse
The question is no longer does AI work; it’s how well, and for whom, and where is the most value being created?
Laura Tacho
CTO
Applying the DORA metrics
DORA metrics can guide performance improvements, if you understand their context and limits.
Laura Tacho
CTO
How to communicate the reality of AI-assisted engineering in today’s hype cycle
Show real use cases, outline the cost of enablement, and tell a story with data.
Laura Tacho
CTO
Setting targets for developer productivity metrics
Principles for setting goals around developer productivity metrics while avoiding common pitfalls.
Laura Tacho
CTO
Findings from Microsoft’s 3-week study on Copilot use
After three weeks of using Copilot, developers felt more positive about the tool and AI overall, but they also emphasized the ongoing need to carefully validate AI-generated code.
Abi Noda
CEO
How Google is accelerating code migrations with AI
Google cuts code migration time in half by automating tasks with AI.
Abi Noda
CEO
Characterizing a high-functioning team
Developers on high-functioning teams are more productive, satisfied, and confident in their team’s ability to ship high-quality work quickly.
Abi Noda
CEO
Driving AI tool adoption — Lessons from Microsoft
SPACE co-author Brian Houck shares proven tactics for moving the needle on AI adoption.
Kali Watkins
Product Marketing
What we learned from Netflix, Pinterest, and Dropbox about measuring developer productivity
A behind-the-scenes look at how engineering leaders at Netflix, Indeed, Twilio, Pinterest, and Dropbox are redefining developer productivity.
Justin Reock
Deputy CTO
Can LLMs earn $1M from real freelance coding work?
A new benchmark tests AI’s ability to complete real-world software engineering tasks.
Abi Noda
CEO
5 interesting learnings from Revenue per Engineer data at 300+ companies
Top-performing companies see $1.5M+ Revenue per Engineer.
Abi Noda
CEO
The gap between developers’ ideal and actual workdays
How developers allocate their time and where AI can help.
Abi Noda
CEO
Three ways DevEx initiatives fail before they even get started
There are three consistent mistakes that undermine DevEx efforts, regardless of company size or technical stack.
Laura Tacho
CTO
AI-assisted development is the future—but productivity matters more than ever
AI-assisted development is reshaping software engineering, but mastering productivity measurement will determine who thrives and who falls behind.
Abi Noda
CEO
When leaders disagree with their developers
What should you do when leaders and developers see productivity differently? Start here.
Abi Noda
CEO
Operationalizing developer productivity metrics
How to integrate metrics into teams’ decision-making processes.
Laura Tacho
CTO
Backstage is dominating the developer portal market
Analysis of the IDP landscape.
Abi Noda
CEO