Why are teams only aligned during a crisis? | CircleCI & MongoDB
How metrics keep everyone on the same page.
This week, Ben and Andrew dive into the (surprisingly?) complex world of calculator apps, analyze how AI is revolutionizing the technical interview, and dissect the emerging “two-tier” economy around AI. What side of the curve does your org fall on?
Then, the conversation goes on site to San Francisco, where host Dan Lines hosts Rob Zuber (CTO of CircleCI) and Tara Hernandez (VP of Dev Productivity at MongoDB) for a discussion of LinearB's 2025 Software Engineering Benchmarks Report.
We unpack the report's surprising findings on the PR lifecycle, project management hygiene, DORA metrics, code quality, and predictability, with key takeaways for optimizing your engineering team's performance.
Be sure to grab your copy of the report to follow along with Dan, Rob, and Tara.
"You need as much process as helps you. If it's getting in your way, get rid of it." — Tara Hernandez, VP of Developer Productivity @ MongoDB
The Download
The Download flips the switch from busy to productive. 💡
1. Building a simple calculator is harder than it looks 🧮
Even seemingly simple apps, like a calculator, can hide complex challenges. In a recent article, Chad Nauseam highlights the unexpected difficulties in creating a truly accurate calculator app, reminding us that solving for precision and usability often requires tackling hidden technical complexity.
Read: "A calculator app? Anyone could make that."
2. Startups are outpacing corporations in AI adoption 🚀
A “two-tier” AI economy is emerging, with startups rapidly integrating AI into their core operations while larger corporations lag behind. Startups are leveraging AI to build new products and business models, whereas many enterprises remain in the experimental phase. This disparity could lead to significant competitive advantages for agile startups.
3. AI is changing how we hire by changing how we learn 🤖📚
AI is forcing a rethink of hiring and learning across the tech industry. AI is making traditional tech interviews obsolete, as skills like algorithm memorization no longer predict success. Even more, AI can now sit between developers and their code at nearly every stage of the creation process that’s typically screened in a tech interview.
Meanwhile, AI is supercharging how we can learn, helping engineers quickly gain new abilities. However, what happens when the traditional struggles of learning are missing from that experience?
The common thread tells us that AI’s rise means focusing less on static knowledge and more on adaptability, problem-solving, and curiosity.
Read: AI Killed The Tech Interview. Now What?
Read: New Junior Developers Can’t Actually Code
4. Get your guide to go beyond DORA 📈
Are your metrics driving real results, or just ticking boxes? A new LinearB guide shares insights from engineering communities (like Dev Interrupted and Refactoring) on how to go beyond DORA metrics to measure what really matters:
🛶 Flow efficiency
🤩 Developer satisfaction
💥 Measurable business impact
Want to learn how top teams are driving results with this approach?
