Putting the Voice of the Developer First: Lessons from Amazon
Leah Melvoin, creator of Amazon's Voice of the Developer Initiative, shares her insights on what truly drives engineering effectiveness.
What Is Developer Productivity in the AI Era?
Code generation has exploded. Here's what developer productivity actually means now — and why your metrics may not be showing the full picture.
![Top Engineering Intelligence Platforms [2026]](https://uplevelteam.com/hubfs/top-engineering-intelligence%20(1).png)
Top Engineering Intelligence Platforms [2026]
Boards want a number on AI ROI, but most platforms only show what happened last week. Compare the top engineering intelligence platforms for 2026.
Token Spend Is the Wrong Way to Measure AI ROI
Token spend tells you what AI costs — not what it's producing. Here's how engineering leaders can define, measure, and defend AI ROI before someone asks them to.
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Tokenomics for the Deeply Skeptical
AI budgets are under scrutiny. Ed Quick joins Uplevel for a practical conversation on how to manage token spend, drive value, and promote experimentation.
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What Makes Engineering Transformation Stick
Most engineering transformations stall because they skip stages. Here's the five-stage framework for building AI capability that compounds.
AI Capabilities Maturity: What to Measure Beyond Adoption
A lot of AI metrics track usage, not impact. Here's the framework engineering leaders need to assess AI maturity well.
Top Engineering Intelligence Platforms [2026]
Boards want a number on AI ROI, but most platforms only show what happened last week. Compare the top engineering intelligence platforms for 2026.
How to Choose an Engineering Transformation Consultant
Roadmaps aren't enough. Effective software engineering transformation consultants combine measurement, qualitative research, and team capability building.
Tokenomics for the Deeply Skeptical
AI budgets are under scrutiny. Ed Quick joins Uplevel for a practical conversation on how to manage token spend, drive value, and promote experimentation.
What Makes Engineering Transformation Stick
Most engineering transformations stall because they skip stages. Here's the five-stage framework for building AI capability that compounds.
AI Capabilities Maturity: What to Measure Beyond Adoption
A lot of AI metrics track usage, not impact. Here's the framework engineering leaders need to assess AI maturity well.
Enterprise AI Capability Building: How to Do It Right
Enterprise AI capability building requires six organizational surfaces. Most strategies address one or two. Here's how to assess where yours stands.
The WAVE Framework for Engineering Effectiveness
Uplevel's WAVE Framework guides our approach to organizational change in engineering. Learn about our key indicators for engineering capability.
The AI Measurement Crisis
Here's what the research from a study of 100+ engineering leaders at large orgs reveals about AI measurement.
AI Won’t Solve Your Developer Productivity Problems for You
AI tools aren't the magic fix for developer productivity. Learn how to maximize impact with fundamentals.
We just raised $20M in funding. We’ll use it to expand innovation around developer team health, effectiveness.
Have you heard the good news? We just received $20 million in new funding. [Pause for applause.] With the industry facing tough economic times, it’s not lost ...
How Uplevel Measures the Impact of Chat Interruptions
Learn about Uplevel's Chat Interruptions feature and how you can use it to support your organization from data scientist Anne Sallaska.
Deep Work Is a Multiplier for Engineering Organizations
Deep work time is critical for software engineering teams. Here's how leaders can measure it to help their teams deliver on high-value projects.
Time Allocation Strategies for Engineering Leaders
With greater visibility into how your engineering teams allocate their time, you can create a culture of accountability across your entire organization.
KTLO in Software Development: Best Practices for Leaders
KTLO (keeping the lights on) is the maintenance work that keeps systems running — and AI is making it harder to do. Here's what leaders should know.
DORA Metrics Are a Start. Here's What Comes Next.
DORA metrics are lagging indicators of delivery performance because they don't explain context. Here's why engineering leaders need a better view.
Balancing Engineering Alignment with Autonomy
Learn how Francisco Trindade, VP of Engineering at Braze, approaches engineering leadership to help his team be effective and align with business goals.
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Developer Productivity Metrics That Matter for AI
Measuring developer productivity is hard within large engineering organizations. Here's why that is, and why a holistic approach is necessary.