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Who we sat down with
AI is rewriting go-to-market and most firms are nonetheless working with a “Frankenstein stack.”
On this episode of GTMnow, we sit down with David Zhu, co-founder & CEO of Reevo, to unpack how AI-native firms will substitute legacy GTM programs, why the way forward for gross sales groups seems to be radically completely different, and the way AI brokers have gotten the brand new working layer for income groups.
David shares why Reevo stayed in stealth whereas constructing a vertically built-in AI income working system, the issue of institutional data loss in gross sales organizations, and why the outdated playbook for SaaS and GTM is breaking in 2026.
Mentioned on this episode
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AI-native go-to-market technique
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The demise of the legacy SaaS tech stack
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Income working programs defined
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AI brokers for gross sales, advertising, and buyer success
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How founders ought to take into consideration AI adoption
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Constructing startups within the age of AI
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Why “failure is the cornerstone of innovation”
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AI-driven gross sales productiveness and income effectivity
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Founder-led gross sales in 2026
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The way forward for CROs, CMOs, and RevOps
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AI copilots, Jarvis-style workflows, and GTM automation
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Scaling groups with out scaling headcount
Episode highlights
1:20 – Why Reevo inbuilt stealth
4:50 – Why AI can lastly disrupt GTM tech stacks
9:20 – What Reevo truly does
11:10 – AI outcomes vs headcount development
15:00 – How AI adjustments management & innovation
19:00 – Why legacy GTM groups are weak
23:00 – The way forward for AI-native GTM organizations
29:00 – Working an AI-native firm internally
34:00 – David’s favourite AI workflows & instruments
37:40 – Recommendation for introverted founders & leaders
Key takeaways
1. AI will substitute fragmented GTM tech stacks:
Reevo is betting that firms gained’t maintain stitching collectively dozens of gross sales, advertising, and assist instruments. As a substitute, AI-native “income working programs” will unify GTM workflows and protect institutional data throughout groups.
2. Institutional data is the largest hidden drawback in gross sales:
Prime-performing reps typically maintain crucial data of their heads. After they depart, firms lose playbooks, deal intelligence, and buyer context. David argues AI brokers can turn into the everlasting reminiscence layer for go-to-market groups.
3. The way forward for GTM is outcomes, not headcount:
Conventional scaling meant hiring extra SDRs, AEs, and assist reps to develop income. AI adjustments that equation. Smaller groups geared up with AI copilots and brokers can doubtlessly generate the output of a lot bigger organizations.
4. AI-native firms want a totally completely different working mannequin:
Outdated administration buildings and workflows have gotten out of date. David explains why firms ought to empower builders with extra possession, scale back silos, and optimize for experimentation, quick studying, and adaptableness as an alternative of inflexible course of.
5. The businesses that undertake AI early will compound benefits over time:
AI programs enhance as they ingest extra context, choices, and buyer interactions. Leaders who begin adopting AI-native workflows now might construct long-term aggressive benefits by means of gathered organizational intelligence and sooner execution.
Comply with David Zhu
Comply with Sophie Buonassisi (Host)
Comply with GTMnow
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