Pangram verdict · v3.3
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AI likelihood · overall
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HOW TEAMS BUILDAI usage patterns in software teamsEDITION 01 - TIM QI (2026)Tens of thousands of teams build software inside Linear every day. Over six years that’s given us a detailed picture of how product development happens, from before AI was widely adopted to now.Model companies and coding tools have published plenty on token usage and code volume, but that captures only one layer of the work. We’re unusually well placed to see the entire workflow behind building a product, from the first issue to the pull request that closes it. What we can’t see is AI usage that happens outside Linear, so this is a picture of adoption inside our own customer base, not the market at large.We look at three things across that transition. Who is using AI, how it reshapes where teams spend their time across Linear, and whether it changes how much they ship. Together they make a fixed point for where AI-assisted product development stands in 2026, and something to measure the next edition against.Adoption by functionAI adoption has spread to every functionBetween January and June 2026 the share of users active on AI features more than doubled in every function. Product climbed fastest, from 12% to 34%, and even go-to-market, the function furthest from the codebase, went from 5% to 18%.
We classify roles by normalizing job titles, which carries some error at the edges, but the pattern is too broad to be an artifact of labeling.Percentage of users active on Linear AI features (Last 30 days) by functionPercentage of users active on Linear AI features in the last 30 days, by functionSegmentJan 2026Jun 2026ChangeFounder14%30%+16 percentage pointsEngineering12%30%+18 percentage pointsProduct12%34%+22 percentage pointsDesign6%22%+16 percentage pointsGTM5%18%+13 percentage pointsJan 2026Jun 2026N = 127,000 paid users, active in both January and June 2026Adoption by executive teamAdoption goes all the way to the topExecutives are personally active on AI at rates that match or beat their teams.
CEOs at companies of 201 or more people went from 9% to 36% in six months, the largest jump of any cut in this report, suggesting the most senior leaders are learning the technology by using it rather than reading about it.
Company size comes from third-party enrichment, so this cut covers fewer workspaces than the rest of the report.Percentage of users active on Linear AI features (Last 30 days) by executive teamPercentage of users active on Linear AI features in the last 30 days, by executive teamSegmentJan 2026Jun 2026ChangeFounder, 201+10%26%+16 percentage pointsFounder, 51-20015%27%+12 percentage pointsFounder, 1-5015%31%+16 percentage pointsCEO, 201+9%36%+27 percentage pointsCEO, 51-20015%25%+11 percentage pointsCEO, 1-507%21%+14 percentage pointsCPO, 201+3%24%+21 percentage pointsCPO, 51-20010%26%+15 percentage pointsCPO, 1-5011%36%+25 percentage pointsCTO, 201+11%35%+24 percentage pointsCTO, 51-20012%28%+16 percentage pointsCTO, 1-5016%33%+17 percentage pointsJan 2026Jun 2026N = 13,300 executives, active in both January and June 2026Adoption by company sizeAdoption is consistent at every sizeAI adoption roughly tripled everywhere, from startups to enterprises.
Company size, usually a good predictor of how fast an organization moves on new technology, barely registers here.Percentage of users active on Linear AI features (Last 30 days) by company size (employees)Percentage of users active on Linear AI features in the last 30 days, by company size in full-time employeesSegmentJan 2026Jun 2026Change1001+ FTE8%25%+17 percentage points201-1000 FTE9%27%+19 percentage points51-200 FTE9%25%+16 percentage points1-50 FTE8%23%+14 percentage pointsJan 2026Jun 2026N = 199,000 paid users with a known company size, active in both January and June 2026Application - Create & organizeTeams are putting more into the systemBetween June 2025 and June 2026, time spent creating, triaging, and commenting rose in nearly every function, with engineering up roughly 17% on create and triage alone. Founders show much larger swings, up 17 minutes on creation and 26 on commenting, though they’re a smaller cohort and noisier for it.
More work seems to need more coordination, and that coordination increasingly sets the context agents act on.Average minutes per user per month, June 2025 vs June 2026Average minutes spent per user creating, triaging, assigning, updating, and commenting on issues, June 2025 versus June 2026, by functionSegmentJun 2025Jun 2026ChangeCreate & triage, Eng24m28m+5 minutesCreate & triage, Product38m37m-1 minutesCreate & triage, Design22m25m+3 minutesCreate & triage, GTM27m31m+4 minutesCreate & triage, Founder40m57m+17 minutesAssign & update, Eng16m19m+3 minutesAssign & update, Product26m26m0 minutesAssign & update, Design12m15m+3 minutesAssign & update, GTM12m15m+3 minutesAssign & update, Founder22m29m+7 minutesComment, Eng35m40m+5 minutesComment, Product48m49m+1 minutesComment, Design32m34m+2 minutesComment, GTM49m55m+6 minutesComment, Founder39m64m+26 minutesJun 2025Jun 2026N = 54,300 paid users (Jun 2025) → 89,000 (Jun 2026)Application - Issue creationAI authors nearly half of all issuesTwo years ago, fewer than one issue in a thousand was created by AI. Teams now use AI to write just under half of everything created in Linear, and at the current pace it will soon author more than people and integrations combined.Issues created per week (thousands) by sourceThousands of issues created per week by agents and MCP clients versus people and integrations, June 2024 to August 2026, excluding imported issuesWeek ofAgents & MCPPeople & integrationsJun 3, 20240605Jun 10, 20240599Jun 17, 20240582Jun 24, 20240689Jul 1, 20240602Jul 8, 20240628Jul 15, 20241621Jul 22, 20240627Jul 29, 20241650Aug 5, 20240654Aug 12, 20241624Aug 19, 20240660Aug 26, 20241650Sep 2, 20241670Sep 9, 20241690Sep 16, 20241692Sep 23, 20241725Sep 30, 20240696Oct 7, 20241726Oct 14, 20241724Oct 21, 20241741Oct 28, 20241721Nov 4, 20241760Nov 11, 20240760Nov 18, 20241795Nov 25, 20241677Dec 2, 20241765Dec 9, 20241800Dec 16, 20241770Dec 23, 20240373Dec 30, 20240460Jan 6, 20251825Jan 13, 20251878Jan 20, 20251869Jan 27, 20251920Feb 3, 20251930Feb 10, 20251924Feb 17, 20251890Feb 24, 20251934Mar 3, 20251942Mar 10, 20251974Mar 17, 20253971Mar 24, 20253984Mar 31, 20251985Apr 7, 20251999Apr 14, 20251974Apr 21, 20251994Apr 28, 202531029May 5, 202551037May 12, 202571063May 19, 202591042May 26, 202511992Jun 2, 2025181095Jun 9, 2025181074Jun 16, 2025281064Jun 23, 2025341148Jun 30, 2025351092Jul 7, 2025441166Jul 14, 2025401137Jul 21, 2025411164Jul 28, 2025451177Aug 4, 2025521171Aug 11, 2025501206Aug 18, 2025551177Aug 25, 2025471225Sep 1, 2025481200Sep 8, 2025461299Sep 15, 2025451272Sep 22, 2025451294Sep 29, 2025581338Oct 6, 2025621352Oct 13, 2025681350Oct 20, 2025651382Oct 27, 2025741414Nov 3, 2025851461Nov 10, 2025851457Nov 17, 2025911436Nov 24, 2025931299Dec 1, 20251221473Dec 8, 20251421487Dec 15, 20251471526Dec 22, 2025110795Dec 29, 2025139808Jan 5, 20262061601Jan 12, 20262731725Jan 19, 20262911721Jan 26, 20263231806Feb 2, 20264011897Feb 9, 20264511901Feb 16, 20265161875Feb 23, 20265992048Mar 2, 20267072123Mar 9, 20267942170Mar 16, 20268372106Mar 23, 20269162297Mar 30, 20269352104Apr 6, 202610382063Apr 13, 202611282297Apr 20, 202612092173Apr 27, 202612752185May 4, 202613822238May 11, 202615062278May 18, 202615972271May 25, 202614722132Jun 1, 202615422270Jun 8, 202617662371Jun 15, 202616522256Jun 22, 202617282372Jun 29, 202617992265Jul 6, 202620782532Jul 13, 202621432465Jul 20, 202621952396Jul 27, 202623482357Aug 3, 202624352481Agents & MCPPeople & integrationsIssues created per week, June 2024 to August 2026.
Excludes imported issuesApplication - PlanningPlanning time didn’t move inside LinearTime spent on customer requests, docs, and projects held steady in a year when nearly everything else in this report moved up. Planning practice varies widely from team to team, and plenty of it happens in conversation before it lands anywhere, so the average blends heavy planners with light ones.