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Jonathan Chemouny is GTM at ElevenLabs, where he scaled outbound from 5% to 46% of pipeline in one year with a small distributed SDR team. He previously built and led SDR teams at Intercom and Lattice. His team operates with no job titles, no standups, and no activity metrics , running on async Slack communication and trust-based autonomy.

We discuss:

- Why an AI-native company at 95% inbound decided to build a human SDR team instead of automating everything

- How ElevenLabs defines outbound (pure cold + PLG-assisted) and why the distinction matters for pipeline math

- Why candidates from finance and VC outperform career SDRs -- and the hiring process that screens for it

- The operating system: no standups, no pipeline reviews, no job titles, async Slack ("Slack militaire")

- How SDRs run demos, travel to meet prospects in person, and attend events solo -- one rep skipped President's Club for CCW Berlin and came back with 60+ SQOs

- The AI SDR handling inbound qualification in multiple languages with 78% decisions requiring no human intervention

- WhatsApp as a prospecting channel in Europe and why LinkedIn outperforms email

Referenced:

- Carles Reina on 20VC (20x Base-to-quota model)

- Jonathan Chemouny on LinkedIn: linkedin.com/in/chemouny/

- ElevenLabs: elevenlabs.io

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Chapters:

(00:00) Welcome and Setup(00:25) Why Hire SDRs in AI(01:45) Inbound to Outbound Shift(02:33) Defining Outbound and Pipeline(04:02) Talent Profile and Culture(06:21) No Titles and Global Hiring(07:42) Fast Interview Process(11:32) Testing AI Fluency(13:43) Roleplay and Sequence Review(15:19) Career Paths and SDR Role(18:52) Enabling Non Sales Hires(19:47) Productivity and Outbound Mix(24:42) Full Cycle AE Debate(26:05) Culture Intensity and Remote(28:05) Cutting Meetings with Slack(28:57) Slack Notes Automation(29:27) Coaching On The Road(30:47) Incentives And Outbound Shift(31:42) Modern Qualification And Handoffs(33:50) Pipeline Metrics Dashboard(34:40) SDRs In The Field(38:03) SDRs Running Demos(41:02) AI Outreach Demos(41:22) AI Tools And Inbound Agent(44:44) Iteration And Focus Lessons(46:24) Cold Calling And WhatsApp(49:49) KPIs And Agent SDR Debate

Want the prompt I used for this test? And my AI Prompt Library with 30+ outbound prompts?

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I tested seven AI models on the same account research prompt, 12 specific instructions, one target company (Replit), one buyer lens (TrackRec). This is my March 2026 benchmark.

The models: Perplexity Sonar, GPT 5.2 Thinking, Grok 4.2 Beta, Grok 4, Claude Opus 4.6, Claygent (Argon), and Gemini 3 Pro. I scored every model on six weighted criteria, tracked which instructions each model actually completed, classified why they missed what they missed, and manually verified every disputed claim.

Agenda:

- Why I expanded from 3 scoring criteria to 6 — and how adding Business Relevance changed the rankings

- What instruction completion reveals that scores alone don't (Perplexity: 10/12, Gemini: 1/12)

- The difference between hallucinations and false claims — and why it matters for automation at scale

- Why four models found September funding and stopped looking (the persistence failure pattern)

- The $400M funding round that may or may not be real — REPORTED vs VERIFIED as a new verification category

- Which model to use for high-value accounts vs volume enrichment in Clay

- Web app vs API vs Clay: why your results will be different and what I'm testing in the next benchmark

Referenced:

- TrackRec: https://www.trackrec.co

- Replit: https://replit.com

- Perplexity: https://www.perplexity.ai

- Clay: https://www.clay.com

- RepVue: https://www.repvue.com

- The account research prompt: Available for Outbound Kitchen paid members

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Who I am? Elric Legloire, founder of Outbound Kitchen.

When you're ready

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Chapters:(0:00) - Why I keep benchmarking AI models
(1:45) - The test setup: TrackRec researching Replit
(3:00) - What changed from the last test(6 criteria, instruction tracking)
(3:30) - The new rankings
(4:05) - Perplexity: VP of SDR, podcast, RepVue miss
(5:00) - GPT 5.2: zero false claims, Glassdoor depth
(5:30) - The $400M funding round — is it real?
(7:00) - Grok 4.2: 56 seconds, best RepVue data
(8:00) - Bottom four models (quick summary)
(8:55) - Verification: hallucinations vs false claims
(10:05) - Which models I recommend
(10:45) - Web app vs Clay availability
(11:30) - What's next

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Ask: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Submit your questions here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ (anonymous)

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Troy Johnson is the SDR Enablement Program Manager at JumpCloud, where he runs the SDR Enablement program for the Americas. He has over eight years in sales development, including six years managing SDR teams. This is his second appearance on the show, Part 1 covered SDR enablement foundations, and Part 2 dives into practical AI role-play implementation.

We discuss:

- How JumpCloud uses AI role-play to certify SDRs during onboarding -- 100+ practice scenarios before going live

- Running a March Madness-style qualification competition to drive AI adoption and peer coaching

- The monthly rhythm for rolling out updated talk tracks with live practice and manager demos

- Using Gong's theme spotter to identify the most common objections and build targeted AI drills

- Building an SDR-to-AE progression program with AI scenarios aligned to AE managers

- Why managers should practice AI role-play themselves to lead by example

- Tools used: Hyperbound, Orum, Gong, and ChatGPT Voice Mode as a free alternative

Referenced:

- Hyperbound: hyperbound.ai

- Orum: orum.com

- Troy Johnson on LinkedIn

- Gong

- ChatGPT

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When you're ready

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠👨‍🍳 Want to work with me? Send me a DM⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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Connect with me

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Chapters:

(00:00) Intro

(00:44) Framework: Building a World-Class Outbound Team (Talent, Productivity, Enablement)

(02:18) Why JumpCloud Went All-In on AI Role Play (Phone-Heavy Motion)

(03:56) Scenario #1: Onboarding Certification with AI Call Practice

(06:31) How Call Academy Works + Certification Criteria & Rubric Scoring

(09:17) Results & Benefits: 10x Reps, Faster First Meeting, Multilingual Coaching

(11:46) Scenario #2: Qualification Competition (Gamified Tournament for Adoption)

(14:39) How the Tournament Runs: Schedule, Scoring, Tools (Orum vs Hyperbound)

(18:50) Scenario #3: Talk Track Adoption—Rolling Out Updates with Live AI Practice

(22:05) Measuring Adoption + Handling Common Objections (Setup for Next Scenario)

(24:15) Test Talk Tracks with Top Performers + AI Role Play Before Rollout

(25:51) Scenario #4: Weekly Objection-Handling Drills That Build Confidence Fast

(28:15) Pick the Right Objections: Use Gong Theme Spotter + Manager Alignment

(30:07) Talk Tracks for “Not a Priority” + “Already Have a Solution” (Battlecards)

(32:02) Competitor Tracking, Game Tape Reviews, and Managers Practicing Too

(34:40) Scenario #5: Upskilling SDRs for the Next Role (SDR → AE and Beyond)

(37:34) Designing the Progression Program: Mentorship, Shadowing, Practice, Certs

(42:59) Data-Driven Enablement: Scorecards, “Beat the Bot,” and Individual Coaching

(46:41) Tool Stack: Hyperbound, Orum, ChatGPT Voice Mode + How Gong Supports It

(49:44) Wrap-Up: Start with One Scenario, Lead by Example, and Keep Iterating