--- title: AI-Assisted Software Development: Team Profiles and... description: DORA's 2025 research on AI-assisted software development identifies seven team profiles and seven key capabilities that help teams extract more value from AI... canonical: https://daily.dev/posts/ai-assisted-software-development-team-profiles-and-capabilities-for-putting-research-into-action-2wrtt7sbw twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: AI-Assisted Software Development: Team Profiles and Capabilities for Putting Research into Action | daily.dev og:description: DORA's 2025 research on AI-assisted software development identifies seven team profiles and seven key capabilities that help teams extract more value from AI... og:url: https://daily.dev/posts/ai-assisted-software-development-team-profiles-and-capabilities-for-putting-research-into-action-2wrtt7sbw og:image: https://api.daily.dev/og/posts/2WrTt7SBw.png og:image:alt: AI-Assisted Software Development: Team Profiles and Capabilities for Putting Research into Action og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # AI-Assisted Software Development: Team Profiles and Capabilities for Putting Research into Action **[InfoQ](https://daily.dev/sources/infoq)** · 5 min read · 0 upvotes · 0 comments ## Summary DORA's 2025 research on AI-assisted software development identifies seven team profiles and seven key capabilities that help teams extract more value from AI adoption. Nathen Harvey, presenting at QCon London, argues AI acts as an amplifier — its greatest returns come from improving the underlying organizational system, not just individual tooling. The research found that while AI adoption increased perceived individual effectiveness and code quality, it also raised software delivery instability, suggesting misaligned incentives. Key capabilities for AI success include clear AI stance, healthy data ecosystems, strong version control, working in small batches, and quality internal platforms. Harvey recommends teams use DORA findings as hypotheses, contextualized to their own environment, and pursue continuous improvement. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### Does AI adoption increase software delivery instability according to DORA's research? Yes, DORA's 2025 research found that as AI adoption increased, software delivery instability also increased, meaning deployments were more likely to be rolled back or require hot fixes. This occurred even though self-reported individual effectiveness and perceived code quality both improved, suggesting a contradiction possibly caused by misaligned incentives or poor visibility into how changes affect production. _Teams weighing AI's tradeoffs against delivery stability can track findings like this on daily.dev._ ### What capabilities help software teams get the most value out of AI adoption? DORA identified seven capabilities: a clear and communicated AI stance, healthy data ecosystems, AI-accessible internal data, strong version control practices, working in small batches, a user-centric focus, and quality internal platforms. Combined with AI adoption, these capabilities correlate with better team and product outcomes, according to Nathen Harvey's presentation of DORA's 2025 research. _Engineering leaders shaping an AI adoption strategy can follow research like this via daily.dev._ ### Why does AI adoption put pressure on the practice of working in small batches? AI models can suggest large change sets or pull requests, which are harder to review, harder to assess for fitness of purpose, and carry more risk than small changes. DORA's long-standing data shows smaller batches lead to better software delivery performance, so teams need to collaborate with AI assistants to break large suggested changes into smaller, independently deployable units. _Developers tuning how they review AI-generated pull requests can find this kind of guidance on daily.dev._ ## Similar posts on daily.dev - [From adoption to impact: Putting the DORA AI Capabilities Model to work](https://daily.dev/posts/from-adoption-to-impact-putting-the-dora-ai-capabilities-model-to-work-efixyb4mu) · Google Cloud · 0 upvotes · 0 comments - [Measuring for AI success and quality improvement](https://daily.dev/posts/measuring-for-ai-success-and-quality-improvement-vo2t7mcwf) · Agile Testing · 0 upvotes · 0 comments - [DORA’s 2025 research on the impact of AI](https://daily.dev/posts/dora-s-2025-research-on-the-impact-of-ai-rxssp8auu) · Software Engineering Research · 0 upvotes · 0 comments --- Tags: [#ai](https://daily.dev/tags/ai), [#productivity](https://daily.dev/tags/productivity), [#company-culture](https://daily.dev/tags/company-culture), [#dora](https://daily.dev/tags/dora) [View this post on daily.dev](https://daily.dev/posts/ai-assisted-software-development-team-profiles-and-capabilities-for-putting-research-into-action-2wrtt7sbw) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"AI-Assisted Software Development: Team Profiles and Capabilities for Putting Research into Action","url":"https://daily.dev/posts/ai-assisted-software-development-team-profiles-and-capabilities-for-putting-research-into-action-2wrtt7sbw","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/ai-assisted-software-development-team-profiles-and-capabilities-for-putting-research-into-action-2wrtt7sbw"},"datePublished":"2026-07-30T11:42:42.583Z","dateModified":"2026-09-14T06:40:40.572Z","description":"DORA's 2025 research on AI-assisted software development identifies seven team profiles and seven key capabilities that help teams extract more value from AI...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/527f62d5eaa78ba4c70825d606eaaf20?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/527f62d5eaa78ba4c70825d606eaaf20?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"InfoQ","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"InfoQ","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/afc3bced3e1e4b188dd9127017a60e0c","url":"https://daily.dev/sources/infoq"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/ai-assisted-software-development-team-profiles-and-capabilities-for-putting-research-into-action-2wrtt7sbw","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"ai,productivity,company-culture,dora","timeRequired":"PT5M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"InfoQ","item":"https://daily.dev/sources/infoq"},{"@type":"ListItem","position":3,"name":"AI-Assisted Software Development: Team Profiles and Capabilities for Putting Research into Action"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/ai-assisted-software-development-team-profiles-and-capabilities-for-putting-research-into-action-2wrtt7sbw#faq","mainEntity":[{"@type":"Question","name":"Does AI adoption increase software delivery instability according to DORA's research?","acceptedAnswer":{"@type":"Answer","text":"Yes, DORA's 2025 research found that as AI adoption increased, software delivery instability also increased, meaning deployments were more likely to be rolled back or require hot fixes. This occurred even though self-reported individual effectiveness and perceived code quality both improved, suggesting a contradiction possibly caused by misaligned incentives or poor visibility into how changes affect production. Teams weighing AI's tradeoffs against delivery stability can track findings like this on daily.dev."}},{"@type":"Question","name":"What capabilities help software teams get the most value out of AI adoption?","acceptedAnswer":{"@type":"Answer","text":"DORA identified seven capabilities: a clear and communicated AI stance, healthy data ecosystems, AI-accessible internal data, strong version control practices, working in small batches, a user-centric focus, and quality internal platforms. Combined with AI adoption, these capabilities correlate with better team and product outcomes, according to Nathen Harvey's presentation of DORA's 2025 research. Engineering leaders shaping an AI adoption strategy can follow research like this via daily.dev."}},{"@type":"Question","name":"Why does AI adoption put pressure on the practice of working in small batches?","acceptedAnswer":{"@type":"Answer","text":"AI models can suggest large change sets or pull requests, which are harder to review, harder to assess for fitness of purpose, and carry more risk than small changes. DORA's long-standing data shows smaller batches lead to better software delivery performance, so teams need to collaborate with AI assistants to break large suggested changes into smaller, independently deployable units. Developers tuning how they review AI-generated pull requests can find this kind of guidance on daily.dev."}}]} ```