Original data on AI-native software delivery
Surveys, telemetry studies, and benchmarks from Stride and the broader software-delivery community. Methodology is always published; sample sizes are disclosed; raw datasets are linked when public. Cite freely.
Engineering Burnout & Process Debt 2026
May 18, 2026Engineering burnout has risen across the 2019–2024 window (39%→62%→53% in the Yerbo cycle; 41% Stack Overflow 2024). Almost no engineering survey uses the validated MBI. The literature points strongly at autonomy and process fit; process debt is rarely measured. Volume 0 reads the clinical literature; Volume 1 (Q3 2026) lands the 600-engineer study.
ReadDORA Metrics in Practice 2026
May 18, 2026Seven years of DORA Accelerate data converge on four metrics that predict org performance, and one repeated misinterpretation of what they prove. DORA explicitly does NOT claim causation; the popular reading routinely ignores that. Volume 0 reads the literature; Volume 1 (Q4 2026) lands the AI-era segmented refresh.
ReadSprint Estimation Reality 2026
May 18, 2026Software estimates have been ~30% optimistic on average for 43 years (Halkjelsvik & Jørgensen 2012). The 2026 question isn't whether AI fixes that. It's whether AI hides it. Volume 0 synthesises the literature and pre-registers Stride's 500-person calibration study; Volume 1 lands at this URL in Q4 2026.
ReadState of AI Software Delivery 2026
May 17, 2026AI adoption in software delivery is universal (~76–95% across DORA, Stack Overflow, McKinsey). Productivity findings disagree wildly: Microsoft/GitHub measured +55% on standardised tasks; METR measured −19% on real OSS work, with the same developers feeling +20% faster. The Stride 2026 study (n≥1,500, pre-registered) closes the measurement gap. Headline findings: July 2026.
Read
Methodology & press materials
- Engineering Burnout & Process Debt 2026:MethodologyPress kit
- DORA Metrics in Practice 2026:MethodologyPress kit
- Sprint Estimation Reality 2026:MethodologyPress kit
- State of AI Software Delivery 2026:MethodologyPress kit
About Stride Research
- What is Stride Research?
- A program of original surveys, telemetry studies, and landscape syntheses on AI-native software delivery. Reports are published with full methodology disclosure (sample sizes, recruitment, statistical methods) so journalists, peer reviewers, and engineering leaders can assess the rigor before citing.
- Can I cite Stride Research in my publication?
- Yes. Reports are licensed CC BY 4.0. Attribute with the report title and a link to the source URL. Where datasets are released (look for the "Download raw data" link), reproducibility notebooks are linked from each report's methodology page.
- How does Stride collect research data?
- Three sources: pre-registered surveys (recruited via Prolific Academic, weighted to engineering-leader population), telemetry from Stride beta-customer workspaces (anonymised, opt-in), and synthesis of existing public studies (DORA, METR, Octoverse, Maslach Burnout Inventory). Every numeric claim in our reports is attributable to one of these.
- Are the surveys peer-reviewed?
- Surveys are pre-registered via OSF before fielding (the methodology page links the registration). They are not formally peer-reviewed in the academic sense, but the pre-registration plus full instrument disclosure plus dataset release makes them auditable in a way most industry research is not.
- When will the next report ship?
- Volume 0 (landscape synthesis) of each report is live now. Volume 1 (primary findings from the pre-registered surveys) ships on a rolling basis through 2026: DORA refresh Q4 2026, Sprint Estimation Q4 2026, Engineering Burnout Q3 2026, State of AI Software Delivery July 2026. Each Volume 1 replaces the synthesis sections of Volume 0 at the same URL.