Head of Demand Generation
The bridges between segments, the demand programs feeding them, and the brand-vs-demand mix that's converting. Refreshed 6:00 AM PT daily.
Linear's funnel is product-led at the front (developers self-serve) and sales-assist at the back (enterprise contracts). The demand-gen role exists to architect the three bridges between the segments — making the implicit motion operable, instrumented, and improvable.
The developer signs up alone, brings in a teammate, then a third. The product-led conversion to a paying team plan happens around 5 active seats. That's where the bridge currently leaks — drop-off at the "5+ users" step is 49.7%.
Diagnosis (hypothesis, not yet validated): teams hit the seat-count gate during a sprint and the upgrade flow lands them on a generic billing screen rather than a team-plan-shaped one. Recommendation in Lifecycle Lead view.
This is the bridge under the "most significant quarter" headline. Workspaces hit the team-plan threshold organically; the demand-gen function's job is to identify the ones that look like enterprise, hand them to AEs with context, and shorten the time from team plan to enterprise contract.
Median time from team-plan threshold to closed-won enterprise: 187 days. Best-cohort (champion-led, single-team-rollout-first): 84 days. Closing that gap is the highest-leverage demand-gen play in the company.
Agents now take seats. Workspaces that adopt at least one agent show 3.4x the expansion rate of agent-free workspaces. The agent count is the cleanest expansion signal we've ever had — and it's also a brand asset (we got there first) that demand programs can lean on.
Agent seat ratio is 0.18 per human seat across paid workspaces. If we get to 0.5 by year-end (consistent with current adoption curve), that's $11–14M of additional ARR from existing customers without a single net-new logo.
The portfolio is brand-heavy on purpose. The honest question for the next $100M: can the brand keep doing this much of the work, or do we need a more balanced engine? See the attribution split below.
Brand is doing 62% of the converting work today. The strategic question for this seat: lean further into brand (it's working) or build a more balanced demand engine that can keep producing when the brand-led signal saturates? My take is "both, sequenced" — brand stays the front door, demand programs get rebuilt around the bridges above.
| Account | Segment | Stage | Seats | Agents | ARR target | Signal |
|---|---|---|---|---|---|---|
| Anthropic | Mid-market → Ent | AE-engaged | 340 | 62 | $420K | Champion · agent-heavy |
| Replicate | Team plan | ICP-flagged | 182 | 28 | $210K | Linear for Agents adoption |
| Modal Labs | Team plan | Opp opened | 128 | 14 | $148K | Champion identified |
| Plaid | Mid-market | AE-engaged | 412 | 8 | $520K | SSO + on-prem requested |
| Notion | Mid-market → Ent | Procurement | 280 | 42 | $340K | In legal · Q1 close path |
| Perplexity | Team plan | ICP-flagged | 160 | 31 | $180K | Linear for Agents adoption |
| Hex | Team plan | Opp opened | 112 | 9 | $128K | Champion identified |
| Retool | Mid-market | AE-engaged | 240 | 12 | $280K | Eval window · 14 days |
| Pinecone | Team plan | ICP-flagged | 104 | 22 | $112K | Linear for Agents adoption |
| Census | Team plan | AE-engaged | 128 | 6 | $140K | Method conf attendee |
Lifecycle Lead
Operational view of the funnel — daily signups, team rollouts, MQL-to-SQL pacing, enterprise pipeline movement, and Linear for Agents adoption. Refreshed hourly.
The threshold-to-paid soft step appears in the bridge (Head of Demand Gen view). Hypothesis: the seat-gate billing flow lands too generic. Worth a 2-week experiment with a team-plan-shaped upgrade screen.
| Stage | Volume QTD | Stage conv. | Avg time-in-stage | vs Q4 | Status |
|---|---|---|---|---|---|
| MQL | 1,840 | — | 8d | +22% | Healthy |
| SAL (sales-accepted) | 684 | 37.2% | 12d | +18% | Healthy |
| SQL (sales-qualified) | 412 | 60.2% | 21d | +14% | Healthy |
| Opportunity | 280 | 68.0% | 38d | +4% | Watch · cycle creep |
| Closed-won | 94 | 33.6% | 52d | +12% | Healthy |
| Buyer | # in pipe | Win rate | Median ACV | Median cycle | vs Q4 |
|---|---|---|---|---|---|
| Individual developer | 2,840 | 52% | $96 / mo | 2 days | +8% |
| Eng manager | 684 | 38% | $8.4K / yr | 14 days | +18% |
| Director of Eng | 142 | 31% | $48K / yr | 62 days | +22% |
| VP Engineering | 62 | 24% | $148K / yr | 112 days | +34% |
| CTO | 32 | 28% | $284K / yr | 147 days | +42% |
The CTO/VPE rows are where the up-market thesis sits. Win rates are lower (deeper procurement) but ACV climbs sharply. Q1's growth in the top two rows is the early shape of the "most significant quarter."
COO
Quarterly cadence. ARR by segment, the up-market thesis, brand-vs-demand investment, and the risk register. Built for the Cristina-shape of the question: where is the next $100M coming from?
Nine of the 23 enterprise wins displaced legacy issue-tracking incumbents (Jira, Asana, GitHub Projects). The pattern: a single team adopts Linear bottom-up, brings in adjacent teams, then Eng leadership consolidates. Median time from first paid seat to enterprise contract: 84 days for the champion-led path vs. 187 across all paths. The bridge can be 2x faster when we instrument it.
Agents take seats. The agent-to-human ratio (currently 0.18) is the cleanest expansion metric we've ever had — workspaces with agents expand 3.4x faster than agent-free workspaces. $2.1M in expansion ARR in Q1 alone. If the ratio reaches 0.5 by year-end (current curve supports it), that's $11–14M of additional ARR from existing customers — without a single net-new logo.
The shape of the next $100M is in this chart. Enterprise is the steepest curve and the largest absolute segment now — the up-market thesis is on. Mid-market is the segment with the biggest unfinished bridge (5+ users → paid is leaking 49.7%). Self-serve is the constant front door.
Brand investment under-indexed to its contribution — keep it close to flat. Demand programs over-indexed for what they're returning, but the diagnosis is "wrong programs, not wrong category" — the named-account ABM motion is the high-leverage demand spend that's still building. Sales spend should bias toward AE quality (named-account specialists) over SDR volume.
Median enterprise procurement cycle stretched to 41 days (vs. 32 in Q4). 22 opps currently in procurement — SOC2 + DPA workflows the longest individual steps. Risk: $14M+ slip from Q1 close to Q2.
Activation dipped to 70.8% (from 72.4%). Likely tied to ongoing onboarding A/B test rather than a structural shift. Watching Day-7 retention for the variant; will revert if not net-positive in two weeks.
Agents-as-seats pricing is converting in Q1 at small scale (3,420 workspaces). At 10x volume the friction may show — particularly for mid-market customers with budget cycles that don't match agent-seat growth. Risk: mid-cycle re-price.