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HOW TEAMS BUILD

AI usage patterns in software teams

0000000000000000000000000000000000000000000000000111111111111111111111111111111111111111111111111122222222222222222222222222222222222222222222222223333333333333333333333333333333333333333333333444444444444444444444444444444444444444444444444555555555555555555555555555555555555555555555555566666666666666666666666666666666666666666666667777777777777777777777777777777777777777777777778888888888888888888888888888888888888888888888899999999999999999999999999999999999999999999999992026Linear Orbit Inc.

EDITION 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

01. By function

02. By executive team

03. By company size

Application

04. Create & organize

05. Planning

06. AI

Output

07. Non-engineer PRs

08. Total PRs

09. Coding agents

Adoption by function

AI adoption has spread to every function

Between 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 function

Founder

+16pp

Engineering

+18pp

Product

+22pp

Design

+16pp

GTM

+13pp

0%10%20%30%40%50%

Percentage of users active on Linear AI features in the last 30 days, by function

Segment

Jan 2026

Jun 2026

Change

Founder

14%

30%

+16 percentage points

Engineering

12%

30%

+18 percentage points

Product

12%

34%

+22 percentage points

Design

6%

22%

+16 percentage points

GTM

5%

18%

+13 percentage points

Jan 2026Jun 2026More infoN = 127,000 paid users, active in both January and June 2026

Adoption by executive team

Adoption goes all the way to the top

Executives 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 team

Founder201+

+16pp

51-200

+12pp

1-50

+16pp

CEO201+

+27pp

51-200

+11pp

1-50

+14pp

CPO201+

+21pp

51-200

+15pp

1-50

+25pp

CTO201+

+24pp

51-200

+16pp

1-50

+17pp

0%10%20%30%40%50%

Percentage of users active on Linear AI features in the last 30 days, by executive team

Segment

Jan 2026

Jun 2026

Change

Founder, 201+

10%

26%

+16 percentage points

Founder, 51-200

15%

27%

+12 percentage points

Founder, 1-50

15%

31%

+16 percentage points

CEO, 201+

9%

36%

+27 percentage points

CEO, 51-200

15%

25%

+11 percentage points

CEO, 1-50

7%

21%

+14 percentage points

CPO, 201+

3%

24%

+21 percentage points

CPO, 51-200

10%

26%

+15 percentage points

CPO, 1-50

11%

36%

+25 percentage points

CTO, 201+

11%

35%

+24 percentage points

CTO, 51-200

12%

28%

+16 percentage points

CTO, 1-50

16%

33%

+17 percentage points

Jan 2026Jun 2026More infoN = 13,300 executives, active in both January and June 2026

Adoption by company size

Adoption is consistent at every size

AI 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)

1001+ FTE

+17pp

201-1000 FTE

+19pp

51-200 FTE

+16pp

1-50 FTE

+14pp

0%10%20%30%40%50%

Percentage of users active on Linear AI features in the last 30 days, by company size in full-time employees

Segment

Jan 2026

Jun 2026

Change

1001+ FTE

8%

25%

+17 percentage points

201-1000 FTE

9%

27%

+19 percentage points

51-200 FTE

9%

25%

+16 percentage points

1-50 FTE

8%

23%

+14 percentage points

Jan 2026Jun 2026More infoN = 199,000 paid users with a known company size, active in both January and June 2026

Application - Create & organize

Teams are putting more into the system

Between 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 2026

Create & triageEng

+5m

Product

-1m

Design

+3m

GTM

+4m

Founder

+17m

Assign & updateEng

+3m

Product

0m

Design

+3m

GTM

+3m

Founder

+7m

CommentEng

+5m

Product

+1m

Design

+2m

GTM

+6m

Founder

+26m

0m15m30m45m60m75m

Average minutes spent per user creating, triaging, assigning, updating, and commenting on issues, June 2025 versus June 2026, by function

Segment

Jun 2025

Jun 2026

Change

Create & triage, Eng

24m

28m

+5 minutes

Create & triage, Product

38m

37m

-1 minutes

Create & triage, Design

22m

25m

+3 minutes

Create & triage, GTM

27m

31m

+4 minutes

Create & triage, Founder

40m

57m

+17 minutes

Assign & update, Eng

16m

19m

+3 minutes

Assign & update, Product

26m

26m

0 minutes

Assign & update, Design

12m

15m

+3 minutes

Assign & update, GTM

12m

15m

+3 minutes

Assign & update, Founder

22m

29m

+7 minutes

Comment, Eng

35m

40m

+5 minutes

Comment, Product

48m

49m

+1 minutes

Comment, Design

32m

34m

+2 minutes

Comment, GTM

49m

55m

+6 minutes

Comment, Founder

39m

64m

+26 minutes

Jun 2025Jun 2026More infoN = 54,300 paid users (Jun 2025) → 89,000 (Jun 2026)

Application - Issue creation

AI authors nearly half of all issues

Two 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 source

300025002000150010005000

Jul 2024Jan 2025Jul 2025Jan 2026Jul 2026

Thousands of issues created per week by agents and MCP clients versus people and integrations, June 2024 to August 2026, excluding imported issues

Week of

Agents & MCP

People & integrations

Jun 3, 2024

0

605

Jun 10, 2024

0

599

Jun 17, 2024

0

582

Jun 24, 2024

0

689

Jul 1, 2024

0

602

Jul 8, 2024

0

628

Jul 15, 2024

1

621

Jul 22, 2024

0

627

Jul 29, 2024

1

650

Aug 5, 2024

0

654

Aug 12, 2024

1

624

Aug 19, 2024

0

660

Aug 26, 2024

1

650

Sep 2, 2024

1

670

Sep 9, 2024

1

690

Sep 16, 2024

1

692

Sep 23, 2024

1

725

Sep 30, 2024

0

696

Oct 7, 2024

1

726

Oct 14, 2024

1

724

Oct 21, 2024

1

741

Oct 28, 2024

1

721

Nov 4, 2024

1

760

Nov 11, 2024

0

760

Nov 18, 2024

1

795

Nov 25, 2024

1

677

Dec 2, 2024

1

765

Dec 9, 2024

1

800

Dec 16, 2024

1

770

Dec 23, 2024

0

373

Dec 30, 2024

0

460

Jan 6, 2025

1

825

Jan 13, 2025

1

878

Jan 20, 2025

1

869

Jan 27, 2025

1

920

Feb 3, 2025

1

930

Feb 10, 2025

1

924

Feb 17, 2025

1

890

Feb 24, 2025

1

934

Mar 3, 2025

1

942

Mar 10, 2025

1

974

Mar 17, 2025

3

971

Mar 24, 2025

3

984

Mar 31, 2025

1

985

Apr 7, 2025

1

999

Apr 14, 2025

1

974

Apr 21, 2025

1

994

Apr 28, 2025

3

1029

May 5, 2025

5

1037

May 12, 2025

7

1063

May 19, 2025

9

1042

May 26, 2025

11

992

Jun 2, 2025

18

1095

Jun 9, 2025

18

1074

Jun 16, 2025

28

1064

Jun 23, 2025

34

1148

Jun 30, 2025

35

1092

Jul 7, 2025

44

1166

Jul 14, 2025

40

1137

Jul 21, 2025

41

1164

Jul 28, 2025

45

1177

Aug 4, 2025

52

1171

Aug 11, 2025

50

1206

Aug 18, 2025

55

1177

Aug 25, 2025

47

1225

Sep 1, 2025

48

1200

Sep 8, 2025

46

1299

Sep 15, 2025

45

1272

Sep 22, 2025

45

1294

Sep 29, 2025

58

1338

Oct 6, 2025

62

1352

Oct 13, 2025

68

1350

Oct 20, 2025

65

1382

Oct 27, 2025

74

1414

Nov 3, 2025

85

1461

Nov 10, 2025

85

1457

Nov 17, 2025

91

1436

Nov 24, 2025

93

1299

Dec 1, 2025

122

1473

Dec 8, 2025

142

1487

Dec 15, 2025

147

1526

Dec 22, 2025

110

795

Dec 29, 2025

139

808

Jan 5, 2026

206

1601

Jan 12, 2026

273

1725

Jan 19, 2026

291

1721

Jan 26, 2026

323

1806

Feb 2, 2026

401

1897

Feb 9, 2026

451

1901

Feb 16, 2026

516

1875

Feb 23, 2026

599

2048

Mar 2, 2026

707

2123

Mar 9, 2026

794

2170

Mar 16, 2026

837

2106

Mar 23, 2026

916

2297

Mar 30, 2026

935

2104

Apr 6, 2026

1038

2063

Apr 13, 2026

1128

2297

Apr 20, 2026

1209

2173

Apr 27, 2026

1275

2185

May 4, 2026

1382

2238

May 11, 2026

1506

2278

May 18, 2026

1597

2271

May 25, 2026

1472

2132

Jun 1, 2026

1542

2270

Jun 8, 2026

1766

2371

Jun 15, 2026

1652

2256

Jun 22, 2026

1728

2372

Jun 29, 2026

1799

2265

Jul 6, 2026

2078

2532

Jul 13, 2026

2143

2465

Jul 20, 2026

2195

2396

Jul 27, 2026

2348

2357

Aug 3, 2026

2435

2481

Agents & MCPPeople & integrationsMore infoIssues created per week, June 2024 to August 2026. Excludes imported issues

Application - Planning

Planning time didn’t move inside Linear

Time 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. What the steadiness suggests is that AI has so far changed how teams execute far more than how they decide what to build.

Average minutes per user per month, June 2025 vs June 2026

Customer requestsEng

0m

Product

0m

Design

0m

GTM

+1m

Founder

+1m

Docs & projectsEng

+1m

Product

+1m

Design

+1m

GTM

+1m

Founder

0m

0m5m10m15m20m25m

Average minutes spent per user on customer requests, docs, and projects, June 2025 versus June 2026, by function

Segment

Jun 2025

Jun 2026

Change

Customer requests, Eng

1m

1m

0 minutes

Customer requests, Product

3m

4m

0 minutes

Customer requests, Design

1m

1m

0 minutes

Customer requests, GTM

4m

4m

+1 minutes

Customer requests, Founder

2m

3m

+1 minutes

Docs & projects, Eng

3m

3m

+1 minutes

Docs & projects, Product

13m

14m

+1 minutes

Docs & projects, Design

4m

5m

+1 minutes

Docs & projects, GTM

3m

3m

+1 minutes

Docs & projects, Founder

7m

8m

0 minutes

Jun 2025Jun 2026More infoN = 54,300 paid users (Jun 2025) → 89,000 (Jun 2026)

Application - AI

A new layer of work appeared

Chatting with AI and delegating issues to agents are categories of work that didn’t exist a year ago, and they now show up in every function’s week, with product leaning in hardest. Nothing else shrank to make room, which suggests AI has landed on top of existing work rather than replacing any of it, at least so far.

Average minutes per user per month, June 2025 vs June 2026

Agent issuesEng

+1m

Product

+1m

Design

0m

GTM

0m

Founder

+2m

Chat with AIEng

+2m

Product

+5m

Design

+3m

GTM

+3m

Founder

+4m

0m2m4m6m8m10m

Average minutes spent per user on agent issues and AI chat, June 2025 versus June 2026, by function

Segment

Jun 2025

Jun 2026

Change

Agent issues, Eng

0m

1m

+1 minutes

Agent issues, Product

0m

1m

+1 minutes

Agent issues, Design

0m

0m

0 minutes

Agent issues, GTM

0m

0m

0 minutes

Agent issues, Founder

0m

2m

+2 minutes

Chat with AI, Eng

0m

2m

+2 minutes

Chat with AI, Product

0m

5m

+5 minutes

Chat with AI, Design

0m

3m

+3 minutes

Chat with AI, GTM

0m

3m

+3 minutes

Chat with AI, Founder

0m

4m

+4 minutes

Jun 2025Jun 2026More infoN = 54,300 paid users (Jun 2025) → 89,000 (Jun 2026)

Output - PR creation

Non-engineers are shipping more code

The share of product managers attaching pull requests rose from 3% to 10% in two years, and designers from 1% to 8%. We only count pull requests in repositories connected to Linear, so anyone shipping outside that loop is invisible here, which makes these numbers floors rather than ceilings. The people who used to describe a change increasingly ship it themselves.

Percentage of users who attached a pull request (Last 30 days)

Founder

+12pp

Engineering

+14pp

Product

+7pp

Design

+7pp

GTM

+2pp

0%10%20%30%40%50%

Percentage of users who attached a pull request in the last 30 days, June 2024 to June 2026, by function

Segment

Jun 2024

Jun 2025

Jun 2026

Change

Founder

11%

12%

23%

+12 percentage points

Engineering

20%

22%

34%

+14 percentage points

Product

3%

3%

10%

+7 percentage points

Design

1%

2%

8%

+7 percentage points

GTM

1%

1%

3%

+2 percentage points

Jun 2024Jun 2025Jun 2026More infoN = 166,000 paid users (June 2026)

Output - PR volume

Pull requests are up 111% in two years

Pull requests opened per workspace are up 111% on a June 2024 baseline. Output held roughly level for the first year, then bent upward through 2026 as model quality and adoption climbed together. We count PRs opened rather than merged, and an opened PR says nothing about the value of the change, but the inflection is hard to miss.

Percentage change in pull requests per team per week since June 2024 - All paid workspaces

+125%+100%+75%+50%+25%0%-25%-50%-75%

Jul 2024Jan 2025Jul 2025Jan 2026Jul 2026

Weekly change in pull requests opened per paid workspace, against the June 2024 baseline

Week of

Change

Jun 2, 2024

0%

Jun 9, 2024

+9%

Jun 16, 2024

+10%

Jun 23, 2024

+3%

Jun 30, 2024

+8%

Jul 7, 2024

-4%

Jul 14, 2024

+8%

Jul 21, 2024

+7%

Jul 28, 2024

+8%

Aug 4, 2024

+7%

Aug 11, 2024

+6%

Aug 18, 2024

+3%

Aug 25, 2024

+10%

Sep 1, 2024

+10%

Sep 8, 2024

+5%

Sep 15, 2024

+12%

Sep 22, 2024

+10%

Sep 29, 2024

+14%

Oct 6, 2024

+8%

Oct 13, 2024

+11%

Oct 20, 2024

+9%

Oct 27, 2024

+18%

Nov 3, 2024

+8%

Nov 10, 2024

+15%

Nov 17, 2024

+11%

Nov 24, 2024

+17%

Dec 1, 2024

0%

Dec 8, 2024

+16%

Dec 15, 2024

+17%

Dec 22, 2024

+10%

Dec 29, 2024

-58%

Jan 5, 2025

-50%

Jan 12, 2025

+6%

Jan 19, 2025

+15%

Jan 26, 2025

+13%

Feb 2, 2025

+15%

Feb 9, 2025

+19%

Feb 16, 2025

+21%

Feb 23, 2025

+17%

Mar 2, 2025

+21%

Mar 9, 2025

+19%

Mar 16, 2025

+26%

Mar 23, 2025

+26%

Mar 30, 2025

+23%

Apr 6, 2025

+17%

Apr 13, 2025

+24%

Apr 20, 2025

+11%

Apr 27, 2025

+10%

May 4, 2025

+7%

May 11, 2025

+14%

May 18, 2025

+21%

May 25, 2025

+22%

Jun 1, 2025

+9%

Jun 8, 2025

+22%

Jun 15, 2025

+16%

Jun 22, 2025

+12%

Jun 29, 2025

+22%

Jul 6, 2025

+8%

Jul 13, 2025

+16%

Jul 20, 2025

+16%

Jul 27, 2025

+16%

Aug 3, 2025

+13%

Aug 10, 2025

+9%

Aug 17, 2025

+5%

Aug 24, 2025

+10%

Aug 31, 2025

+8%

Sep 7, 2025

+4%

Sep 14, 2025

+11%

Sep 21, 2025

+10%

Sep 28, 2025

+8%

Oct 5, 2025

+9%

Oct 12, 2025

+9%

Oct 19, 2025

+9%

Oct 26, 2025

+9%

Nov 2, 2025

+14%

Nov 9, 2025

+15%

Nov 16, 2025

+13%

Nov 23, 2025

+16%

Nov 30, 2025

+1%

Dec 7, 2025

+17%

Dec 14, 2025

+17%

Dec 21, 2025

+14%

Dec 28, 2025

-48%

Jan 4, 2026

-54%

Jan 11, 2026

+10%

Jan 18, 2026

+22%

Jan 25, 2026

+22%

Feb 1, 2026

+27%

Feb 8, 2026

+32%

Feb 15, 2026

+36%

Feb 22, 2026

+33%

Mar 1, 2026

+50%

Mar 8, 2026

+49%

Mar 15, 2026

+54%

Mar 22, 2026

+55%

Mar 29, 2026

+58%

Apr 5, 2026

+41%

Apr 12, 2026

+46%

Apr 19, 2026

+60%

Apr 26, 2026

+66%

May 3, 2026

+67%

May 10, 2026

+80%

May 17, 2026

+91%

May 24, 2026

+95%

May 31, 2026

+85%

Jun 7, 2026

+106%

Jun 14, 2026

+113%

Jun 21, 2026

+111%

More infoN = 47,900 paid workspaces (June 2026)

Output - Coding agents

Coding agents account for most of the acceleration

Teams that connected a coding agent roughly tripled their weekly pull requests over two years, from 21 to 65, while teams without one went from 8 to 10. These teams were already higher-output before coding agents existed, so the levels aren’t directly comparable, but each cohort against its own baseline tells a clean story, and nearly all the growth sits on the agent side.

Pull requests per team per week - Fixed cohort (paid workspaces)

706050403020100

Jul 2024Jan 2025Jul 2025Jan 2026Jul 2026

Average pull requests opened per workspace per week, coding-agent teams versus traditional teams, June 2024 to June 2026

Week of

Coding-agent teams

Traditional teams

Jun 2, 2024

21

8

Jun 9, 2024

24

8

Jun 16, 2024

24

9

Jun 23, 2024

22

8

Jun 30, 2024

24

9

Jul 7, 2024

21

8

Jul 14, 2024

24

8

Jul 21, 2024

24

8

Jul 28, 2024

24

9

Aug 4, 2024

24

8

Aug 11, 2024

24

8

Aug 18, 2024

23

8

Aug 25, 2024

25

8

Sep 1, 2024

24

8

Sep 8, 2024

24

8

Sep 15, 2024

25

9

Sep 22, 2024

25

8

Sep 29, 2024

26

9

Oct 6, 2024

25

9

Oct 13, 2024

26

8

Oct 20, 2024

25

8

Oct 27, 2024

26

9

Nov 3, 2024

25

8

Nov 10, 2024

27

9

Nov 17, 2024

26

8

Nov 24, 2024

28

9

Dec 1, 2024

23

8

Dec 8, 2024

27

9

Dec 15, 2024

28

9

Dec 22, 2024

26

8

Dec 29, 2024

10

3

Jan 5, 2025

11

4

Jan 12, 2025

25

8

Jan 19, 2025

27

9

Jan 26, 2025

27

8

Feb 2, 2025

28

8

Feb 9, 2025

29

9

Feb 16, 2025

30

9

Feb 23, 2025

29

9

Mar 2, 2025

30

9

Mar 9, 2025

30

9

Mar 16, 2025

30

9

Mar 23, 2025

31

9

Mar 30, 2025

31

9

Apr 6, 2025

30

8

Apr 13, 2025

32

9

Apr 20, 2025

28

8

Apr 27, 2025

28

8

May 4, 2025

28

8

May 11, 2025

29

8

May 18, 2025

32

9

May 25, 2025

31

9

Jun 1, 2025

28

8

Jun 8, 2025

31

8

Jun 15, 2025

31

8

Jun 22, 2025

30

8

Jun 29, 2025

32

8

Jul 6, 2025

29

8

Jul 13, 2025

32

8

Jul 20, 2025

31

8

Jul 27, 2025

32

8

Aug 3, 2025

32

8

Aug 10, 2025

32

8

Aug 17, 2025

31

7

Aug 24, 2025

33

8

Aug 31, 2025

32

8

Sep 7, 2025

31

8

Sep 14, 2025

34

8

Sep 21, 2025

34

8

Sep 28, 2025

34

8

Oct 5, 2025

35

8

Oct 12, 2025

34

8

Oct 19, 2025

34

8

Oct 26, 2025

34

8

Nov 2, 2025

36

8

Nov 9, 2025

36

8

Nov 16, 2025

35

8

Nov 23, 2025

37

8

Nov 30, 2025

31

7

Dec 7, 2025

37

8

Dec 14, 2025

38

8

Dec 21, 2025

37

8

Dec 28, 2025

16

3

Jan 4, 2026

13

3

Jan 11, 2026

35

7

Jan 18, 2026

40

8

Jan 25, 2026

39

8

Feb 1, 2026

42

8

Feb 8, 2026

44

8

Feb 15, 2026

46

9

Feb 22, 2026

44

8

Mar 1, 2026

49

9

Mar 8, 2026

50

9

Mar 15, 2026

51

9

Mar 22, 2026

50

9

Mar 29, 2026

52

9

Apr 5, 2026

48

9

Apr 12, 2026

49

9

Apr 19, 2026

54

9

Apr 26, 2026

55

9

May 3, 2026

55

8

May 10, 2026

57

9

May 17, 2026

60

10

May 24, 2026

62

10

May 31, 2026

57

9

Jun 7, 2026

65

10

Jun 14, 2026

63

9

Jun 21, 2026

65

10

Coding-agent teamsTraditional teamsMore infoN = 6,887 paid teams (4,280 with coding agents, 2,607 without)

A CLOSING NOTE

The clearest indication of AI’s influence on product development is the dramatic output gains experienced by teams using coding agents over the last two years. We have no way of knowing whether this increased output led to positive business outcomes, but it shows a very clear correlation between AI adoption and acceleration.

Perhaps more intriguing is the makeup of that adoption, and how it appears to be blurring roles. Senior leaders are doing more of the hands-on IC work, adopting AI aggressively to help them do it, and non-engineers are committing code. The suggestion that everyone in an organization is becoming a “builder” seems to be directionally true.

Those gains haven’t shown up as time saved, though. Time spent on existing tasks in Linear held while AI usage appeared as a new layer of work, meaning the overall time spent on product development is going up rather than down. As far as we can observe, teams are working more, not less, suggesting AI has a Jevons paradox quality beyond token consumption.

Many will rightfully argue that looking at pull requests indicates motion rather than value, which is certainly true, but it’s still a step forward from measuring tokens. A mechanical refactor might burn lots of tokens while a meaningful bug fix or code review doesn’t, so token spend and value don’t line up at all, and using one as a proxy for the other will be remembered as a relic of AI’s early days.

In future reports we intend to go deeper on the full lifecycle of work, from token spend all the way to outcomes, something we can newly observe now that code and code review run through Linear as well.

TIM QI - Head of data

Appendix

Methodology

This report uses aggregated product data from Linear. The data includes AI conversations, agent sessions, issue activity, comments, and pull requests. It covers only paid workspaces and the users in them. We report all metrics in aggregate to show broad patterns in how teams use AI to build software, not individual behavior. We measure each metric in a fixed time window. A window is one calendar month or the last 30 days. The year‑over‑year charts use June 2025 and June 2026. Adoption metrics use a trailing 30‑day window, and time‑series charts aggregate to weekly points. Both steps reduce short‑term noise. Some charts keep only the users who are active in both windows.

Definitions

AI-active. A user with at least one AI interaction, an in-app or Slack conversation or an agent session, in a 28-day window.

Agent team. A workspace with a coding agent connected.

Pull request. A code change opened against a repository connected to Linear. We count pull requests opened, not merged.

Paid workspace. A workspace on a paid plan, active during the relevant period.

Agent issue. This includes delegating an issue to an agent or starting a session.

Company size. Full-time employees at the company, from third-party enrichment.

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