Evidence, not vibes
Vera reads full Reddit threads, comment trees, and live X search — then quotes the exact people asking for your feature, with links you can click.
Vera is a Linear agent that pressure-tests your tickets against Reddit, X, and competitor changelogs — and posts a verdict with real evidence in about 90 seconds. Mention it. That's the whole workflow.
Roadmap · Q3 candidates
Marketing keeps asking for a way to tag hundreds of assets at once. Proposal: multi-select in the library view + “apply tags” bulk action. Do our users actually need this, or is it one loud customer?
@Vera validate this before we commit it to the sprint
Demand evidence
“Tagging 400 assets one by one is the reason we're shopping for a new DAM. Bulk actions or we walk.”
reddit · r/DigitalAssetMgmt · ▲ 212 · 47 comments
“every DAM demo: 'yes we have tags!' cool, can I apply them to 2,000 files at once? …silence”
x.com · 1.4k views · 38 reposts
Competitor coverage
Recommendation: Strong, repeated demand across both communities, and Air shipped it in March — the market has validated this for you. Build it, and lead with speed on large libraries.
reddit · r/DigitalAssetMgmt
“Bulk actions or we walk. Tagging 400 assets one by one is insane.”
▲ 212 · 47 comments
DAM-42 · comment
@Vera validate this before we commit it to the sprint
ack in <1s
bynder.com/roadmap
No change in 14 days
3 issues watching
DAM-73 · comment
@Vera is anyone actually asking for SSO on the free tier?
ack in <1s
DAM-42 · Bulk tagging
demand 8/10
x.com
“cool, can I apply tags to 2,000 files at once? …silence”
1.4k views · 38 reposts
reddit · r/ProductManagement
“We shipped it. Nobody used it. Nobody had ever asked for it.”
▲ 89 · 31 comments
x.com
“every DAM demo: 'yes we have tags!' — no one has bulk apply”
812 views · 12 reposts
air.inc/changelog
Shipped: bulk exports
matched DAM-51
DAM-67 · AI mood boards
demand 2/10
DAM-58 · Version diffs
demand 5/10
brandfolder.com/changelog
Shipped: duplicate detection
matched DAM-33
Vera turns hours of manual validation into a single @mention — deep research, a scored verdict, and standing competitor monitors, all inside Linear.
Vera reads full Reddit threads, comment trees, and live X search — then quotes the exact people asking for your feature, with links you can click.
Build, Investigate, or Skip — with a 0–10 demand score and a one-paragraph rationale. Weak tickets die before sprint planning, not after launch.
Zero organic mentions across Reddit and X in the last 12 months. No competitor lists it on a changelog or roadmap. The demand is internal, not market. Recommend skipping — this was six scoped weeks.
researched for 84s · 0 quotes found · 4 changelogs checked
Air shipped bulk exports this morning — the exact feature this issue proposes. They’ve validated it for you. Consider moving it up.
change detected → issue matched → commented in 2 min
The challenge
Manual research meant nobody did it. Vera makes the honest check the cheapest, fastest step in the workflow — so every ticket gets one before it costs you a sprint.
From @mention to a scored verdict
API spend per validation
Competitor pages re-checked, around the clock
Verdicts are just the start. Vera leaves standing monitors on competitor changelog and roadmap pages, matches every change against your open issues, and comments the moment the market makes a decision for you.
See the proactive loopHow it works
The whole pipeline runs where your team already lives — the only interface is a Linear comment thread.
Type @Vera on a Linear ticket. It acknowledges instantly and gets to work — no forms, no new tabs, no context switch.
linear → webhook → ack in <1s
Full Reddit threads with comment trees, live X search, and scraped competitor changelogs and roadmaps — three sources, simultaneously. One source failing never kills a run.
reddit ∥ x ∥ changelogs
Build, Investigate, or Skip — with a 0–10 demand score, linked evidence quotes, competitor coverage, and a one-paragraph recommendation. About 90 seconds, under a cent.
claude synthesis → verdict comment
Vera pins monitors to competitor pages and re-checks them every 10 minutes. When something ships that matches an open issue, it comments proactively — the market just validated it for you.
change detected → issue matched → comment
Everything you need to know about putting Vera to work on your backlog. Something missing? Ask away.
Vera is an AI agent that lives inside Linear. Mention @Vera on any issue and it researches real demand across Reddit, X, and competitor changelogs, then posts a Build / Investigate / Skip verdict with a 0–10 demand score and linked evidence — in about 90 seconds.
Put a verdict on every ticket before it costs you a sprint. One @mention, 90 seconds, real evidence.