Reversim Summit 2026 · Call for papers

Who submitted, from where, about what

519 sessions from 372 speakers: who submitted, where they work, which tracks they chose, where the program committee placed them, and what they wrote about.

Sessions submitted
519
after removing test entries and duplicates
Unique speakers
372
4% of sessions are co-presented
Organizations
170
not counting independents
Women
32%
of 372 speakers
Accepted
11%
56 sessions · 61 speakers
Mention AI
74%
385 sessions

Who submitted

Gender comes from speaker profiles. Where a profile left it blank, it was filled in from the speaker's bio, first name or photo.

Gender split

Unique speakers, then by conference track and format. Track and format rows count speaker slots, so co-presenters each count once per session.

FemaleMale
All speakers
Female 32%
Male 68%
32% ♀
Full session (30 min)
26% ♀
Lightning talk (5 min)
38% ♀
Ignites (128)
38% ♀
Craft (98)
15% ♀
Culture (72)
35% ♀
Backend (63)
25% ♀
Infrastructure (62)
24% ♀
AI/ML (57)
30% ♀
Frontend (46)
33% ♀
Keynote (2)
50% ♀
Unassigned (11)
27% ♀
The number on the right is the share of women.

Where they work

331 of 372 speakers named an employer. 171 organizations are represented. The top 10 account for 22% of speakers with a known company, and 118 organizations sent exactly one speaker.

Top companies

Unique speakers per company (hover for sessions)

Wix
12
Intuit
8
Microsoft
8
Teads
8
Cato Networks
7
groundcover
7
monday.com
7
HoneyBook
6
Reindeer AI
6
AT&T Israel
5
Island
5
Palo Alto Networks
5
Payoneer
5
Red Hat
5
Gong
4
Melio
4
Amazon / AWS
3
Baz
3
Booking.com
3
Elementor
3

The long tail

How many companies sent 1, 2, 3… speakers

1 speaker
118 orgs
2 speakers
29 orgs
3 speakers
8 orgs
4 speakers
2 orgs
5 speakers
5 orgs
6 speakers
2 orgs
7 speakers
3 orgs
8 speakers
3 orgs
12 speakers
1 org

Type of organization

Unique speakers

Industry
287 · 77%
Not specified
41 · 11%
Independent & consultants
29 · 8%
Academia & research
8 · 2%
Hospitals
5 · 1%
Public & non-profit
2 · 1%

What they submitted

Speakers choose a submitted track when they apply. The program committee then places every session in a conference track that fits the program.

Submitted tracks

As chosen by the submitter

Culture
67 · 13%
Machine Learning
56 · 11%
Software Architecture
41 · 8%
Software Craftsmanship
34 · 7%
Security
27 · 5%
Other
26 · 5%
Management
24 · 5%
Developer Experience (DX)
23 · 4%
Frontend
23 · 4%
Backend
19 · 4%
Data Engineering
19 · 4%
Infrastructure
17 · 3%
Emerging Technologies
15 · 3%
Product
15 · 3%
Monitoring
13 · 3%
DevOps
8 · 2%
Open Source
7 · 1%
Programming Languages
3 · 1%
FinOps
2 · 0%
No track chosen
80 · 15%

Conference tracks

As assigned by the committee

Ignites
125 · 24%
Craft
96 · 18%
Culture
69 · 13%
Backend
59 · 11%
Infrastructure
58 · 11%
AI/ML
55 · 11%
Frontend
44 · 8%
Keynote
2 · 0%
Unassigned
11 · 2%

Format

Sessions

Full session (30 min) · 394Lightning talk (5 min) · 125
All sessions
Full session 76%

Track funnel: submitted → conference

Where each submitted track ended up. Hover a ribbon or a track name to follow it.

IgnitesCraftCultureBackendInfrastructureAI/MLFrontendKeynoteUnassigned
Submitted trackConference track Culture 67 Machine Learning 56 Software Architecture 41 Software Craftsmanship 34 Security 27 Other 26 Management 24 Developer Experience (DX) 23 Frontend 23 Backend 19 Data Engineering 19 Infrastructure 17 Emerging Technologies 15 Product 15 Monitoring 13 DevOps 8 Open Source 7 Programming Languages 3 FinOps 2 No track chosen 80 Ignites 125 Craft 96 Culture 69 Backend 59 Infrastructure 58 AI/ML 55 Frontend 44 Keynote 2 Unassigned 11
Most predictable: 87% of Frontend went to Frontend. Most scattered: Emerging Technologies, where the largest destination (Craft) got only 27%. Ignites is effectively the lightning-talk track: all but 1 of its 125 sessions were submitted as lightning talks.

Does past participation help?

Acceptance rates for this year's call for papers, split by what the speaker did at earlier Reversim summits. People are matched across the yearly CFP exports by email, then by full name.

Acceptance rate by history

Share of speakers with at least one accepted session

Spoke at a past Reversim
40% · 24/60
Submitted before, never spoke
12% · 8/67
First time at Reversim
12% · 29/245
Overall, 16% of speakers and 11% of sessions were accepted. Speakers who have been on the stage before are 3.4× as likely as first-timers.

By years submitted before

Past years in which the speaker submitted at least one session

Never before
12% · 29/245
1 past year
16% · 10/64
2 past years
27% · 8/30
3+ past years
42% · 14/33
An association, not a cause: people who keep coming back may simply write proposals that fit the conference better.

Who is in the pool, and who gets in

The same speakers counted two ways: what this year's applicant pool is made of, and what the accepted list is made of. Hover any figure to see exactly what it counts.

Group Of all submitters Of accepted speakers
Spoke at a past Reversim16%6039%24
Submitted before, never spoke18%6713%8
First time at Reversim66%24548%29
Everyone 100%372 100%61
Past speakers are 16% of the people who submitted but 39% of the people who got in — the same pattern as the chart above, read from the other end.

What they talked about

"AI" shows up in 54% of all sessions. 74% mention AI-related terms, and no submitted track has fewer than a fifth of its sessions touching AI.

Tag cloud

The most common words in English titles and descriptions. Size shows how many sessions use the word. Hover for the count.

AIuserfailurelargejobhiddenmonthfailtechlanguagebehaviormetricsaydesignrequestgapstateinfrastructurereviewpatternMCPtoolcontextagenticbugdomainengineeringfeedbackcostperformanceaskmemorysometimerunningprocessqualitytellproblempipelinedesigningagentshipsecurityloopreadtestdeveloperevaluationarchitecturalchallengedatamachinesolutionskillfeaturefoundclaudeapiarchitecturebottleneckservicequietlymodelappbuildingfewproductioncodingscalecodedecisionassumptionchangepathplatformhumansmalllayerfixlatencyworkflowframeworkpromptknowledgeteamproductsoftwareflowriskfindexpensiveautonomouscontrolmapengineerfiledeterministicorganizationsystemtokentrustobservabilityintroducebreakstandardLLMstackhonestworkingconcrete

How much AI is in each track

Share of sessions whose title or description mentions AI, LLMs, agents, MCP, RAG, GenAI and similar terms

No track chosen
98%
Emerging Technologies
93%
Data Engineering
89%
Machine Learning
89%
Developer Experience (DX)
87%
Open Source
86%
Product
73%
Other
73%
Software Architecture
68%
Software Craftsmanship
68%
Security
67%
Culture
66%
DevOps
63%
Infrastructure
59%
Frontend
57%
Management
54%
Backend
47%
Monitoring
46%

Odds and ends

Patterns across all submissions

Hebrew titles
2%
11 sessions
Title with a colon
54%
"Catchy hook: the real topic"
Pitched in both formats
7 talks
same talk as a 30-min session and a lightning talk
Median description
129 words
longest: 479
“Agent” in the title
18%
93 sessions
Co-presented
4%
20 sessions with 2+ speakers

Submissions per speaker

Unique speakers by number of sessions they appear on

1 session
258 · 69%
2 sessions
64 · 17%
3 sessions
48 · 13%
4 sessions
1 · 0%
5+ sessions
1 · 0%