19 posts tagged with "data"

Every engineering leader asks the same question: how much time do developers actually spend writing code?

Microsoft Research found that developers spend only 30-40% of their time writing code. A 2019 study by Haystack Analytics suggested closer to 2 hours. Our own IDE heartbeat data across B2B engineering teams confirms a median of 78 minutes per day.

Here's what the data actually shows and why it matters.

The "10x developer" is one of the most persistent myths in our industry — and one of the most damaging. Fred Brooks observed in The Mythical Man-Month (1975) that individual programmer productivity varies widely, but he also warned against the conclusion that hiring solves systemic problems. The SPACE framework (Forsgren et al., 2021) goes further: measuring individual developer "productivity" with a single metric is not just inaccurate, it's counterproductive.

We have data from B2B engineering teams and thousands of hours of tracked coding time. Here's what it actually says about developer performance variance — and why the answer matters less than you think.

According to McKinsey's research on developer productivity, software engineers spend only 25-30% of their time actually writing code. So where developers work should matter far less than how their time is structured. Yet the remote vs. office debate has been running for six years, with CEOs citing "collaboration" and developers citing "focus" — both arguing from conviction, not evidence.

We have thousands of hours of tracked IDE activity across 100+ B2B companies. The data tells a more nuanced story than either side wants to hear.

Every "top programming languages" list you've seen is based on GitHub stars, Stack Overflow surveys, or job postings. None of them measure what developers actually spend their time writing.

We do. Here's the ranking based on thousands of hours of real IDE coding time across 200+ programming languages, tracked from active B2B developers at 100+ B2B companies.

Some developers swear by 6 AM starts with coffee and silence. Others don't open their IDE until 10 PM. Managers debate whether to enforce "core hours" or let people work whenever they want.

We looked at extensive activity data from developers across 100+ B2B companies to find out when developers actually code — and whether timing matters.

Every engineering manager has a gut feeling about their team's weekly rhythm. Monday feels slow. Friday feels like a wind-down. But what does the data actually show?

We analyzed thousands of coding hours from developers across 100+ B2B companies to map developer productivity across the work week — and the results challenge some common assumptions.

The IDE debate is eternal. VS Code fans say it's fast and extensible. JetBrains loyalists swear by deep language support. And now Cursor is the new challenger, riding the AI wave. The Stack Overflow Developer Survey consistently ranks VS Code as the most popular editor, while the JetBrains Developer Ecosystem Survey shows strong loyalty among its users. But surveys measure sentiment, not reality.

What do developers actually use when they sit down to work? Not what they tweet about. Not what they starred on GitHub. What they code in, hour after hour, day after day.

We have the data. thousands of hours of tracked coding time across 100+ B2B companies, broken down by IDE.

"Adding manpower to a late software project makes it later." Fred Brooks wrote that in 1975. Fifty years later, engineering leaders still debate whether it's true.

We looked at real coding data from 100+ B2B companies on PanDev Metrics to understand how team size relates to individual developer productivity. The answer is more nuanced than Brooks suggested — but his core insight still holds.

AI coding assistants went from novelty to necessity in under three years. GitHub Copilot, Cursor, Cody, and dozens of alternatives now sit inside developers' editors, suggesting code, answering questions, and writing boilerplate. A Deloitte report on AI adoption in software development estimates that ~70% of enterprise development teams now use some form of AI coding assistance.

But are they actually making developers more productive? Or just more reliant on autocomplete?

We looked at real IDE usage data from 100+ B2B companies to find out what AI-assisted coding looks like in practice.