The Twenty Minute VCMonday.com CEO on Is SaaS Dead: Will Everything Be Vibe Coded | Eran Zinman
CHAPTERS
- 0:00 – 3:10
Public-market whiplash: fundamentals vs sentiment in the “SaaSpocalypse”
Eran describes the emotional and operational reality of running Monday.com amid a sharp market sentiment shift against software. He argues that day-to-day business performance can remain solid even as narratives and doomsday takes crush valuations.
- •Stock drawdowns feel disconnected from operational performance
- •Software sentiment has shifted aggressively in the last 6–18 months
- •Doomsday narratives spread quickly via social and media
- •Eran acknowledges there is some truth in concerns—but sentiment is overcorrecting
- 3:10 – 4:41
Mapping the three doomsday scenarios for SaaS platforms
Prompted by concerns that systems like Monday become “just databases,” Eran outlines three common threats he hears from investors. He proposes discussing each: vibe coding, foundation model companies owning the app layer, and agents abstracting away traditional UIs.
- •Scenario 1: companies vibe-code their own apps
- •Scenario 2: OpenAI/Anthropic/Gemini capture the application layer
- •Scenario 3: agents reduce platforms to systems of record
- •Eran frames these as familiar market fears worth unpacking
- 4:41 – 9:28
Threat #1 — Vibe coding: why building a UI isn’t building durable software
Eran explains why vibe coding demos are compelling but misleading, especially when equating quick UI generation with enterprise-grade, maintainable products. He argues maintenance, adoption, and organizational rollout are the true hard parts—and the economics favor buying over building.
- •Vibe coding excels at interfaces; real software depth is much harder
- •Long-term maintenance and change management are underestimated
- •Hiring people to build internal apps costs more than software licenses
- •Impact may be marginal; even VCs still fund startups despite vibe coding
- 9:28 – 12:39
Threat #2 — Will foundation model companies own the app layer? The AWS analogy
Eran compares today’s fears about OpenAI/Anthropic owning enterprise software to past fears that AWS would capture all value. He argues that infrastructure abundance usually creates more application innovation, and that selling enterprise workflows is a distinct, complex business.
- •Historical parallel: AWS made building easier and triggered a software boom
- •Enterprise apps require different product, sales motion, and handholding
- •LLM providers have massive incentive to focus on infrastructure leadership
- •Belief: no single company will “run everything” inside organizations
- 12:39 – 15:23
Threat #3 — Agents and the “database risk”: software must start doing the work
Eran agrees the agentic shift is the most real existential threat: traditional SaaS has largely been tracking work, not performing it. With AI, he expects the equation to flip so tools must do most of the work, not just store state—forcing a product transformation.
- •Core SaaS paradigm has been similar for ~25 years: DB + dashboards + workflows
- •Historically, 90% of work happened outside the system of record
- •AI enables software to perform 70–80% of work vs. 10–20% previously
- •Legacy tools that don’t deliver work outcomes will be abandoned
- 15:23 – 18:25
Why SaaS spend could explode: the ‘100x TAM’ argument
Eran claims the market is misreading the future: AI-driven productivity could shift budgets from headcount to software, expanding overall software TAM dramatically. He frames investor doubt as uncertainty about which incumbents can successfully change in time.
- •Public markets fear incumbents won’t adapt; they’re waiting for proof
- •Eran’s view: software becomes far more valuable as it replaces labor
- •Example: companies might gladly increase software spend to reduce hiring
- •Claim: software TAM could be 100x larger in an AI-driven economy
- 18:25 – 21:55
Headcount growth vs efficiency: why Monday won’t ‘slam the brakes’
Harry challenges Monday’s planned headcount increases amid industry cuts. Eran argues layoffs won’t fix the core market question; instead, investors want to see revenue acceleration that proves Monday is capturing AI demand during the transition.
- •Transition period requires responsible change management
- •Cutting headcount doesn’t address core concern: ability to reaccelerate revenue
- •Investor test: with ‘infinite AI demand,’ winners should show growth acceleration
- •Leadership focus: prove Monday can supply AI demand effectively
- 21:55 – 27:22
How Monday is using AI internally: SDR agents, AI support, and dev productivity
Eran shares concrete examples of AI-driven efficiency, especially in inbound qualification and customer support. He highlights dramatic response-time improvements and rising conversion metrics, plus engineering gains via tools like Cursor/Cloud Code.
- •Inbound SDR workflow replaced with AI; SDRs shifted to outbound
- •Response time improved from ~24 hours to ~3 minutes
- •Higher conversion, answer rates, and booking outcomes; multilingual 24/7
- •Support heavily AI-assisted; engineering output increasing with copilots
- 27:22 – 30:56
From ‘AI dust’ to a full pivot: pricing, product, and go-to-market redesign
Eran admits Monday initially “sprinkled AI dust” via features that didn’t change the core value. Now he describes a company-wide rethink—product, onboarding, marketing, and especially pricing—toward a world where agents are central and seat-based pricing erodes.
- •Early AI features (formulas/blocks/columns) didn’t transform core value
- •Now: biggest product pivot since 2013 across product + GTM + messaging
- •Seat pricing expected to transition to hybrid, then consumption-based
- •Boards/dashboards move back; agents move to the foreground
- 30:56 – 36:25
Monday’s AI platform bet: orchestrating humans + agents in one workspace
Eran positions Monday as the horizontal coordination layer where humans and agents collaborate, with enterprises needing guidance and structure beyond just buying an LLM license. He argues LLM chat products are personal tools, while cross-org work orchestration is a different category.
- •Goal: default workspace to build and run horizontal agents across a company
- •Agents produce artifacts (tables/docs/files) that humans review and extend
- •Enterprises need context, setup, governance, and collaboration patterns
- •LLM subscriptions ≠ workflow orchestration for teams and organizations
- 36:25 – 39:42
What no one sees about enterprise AI adoption: context is the bottleneck
Eran argues AI capability is advancing faster than organizational readiness because context inside companies is largely undocumented. He predicts a long transition where humans and agents co-work, especially across the broader non-software economy.
- •Tech speed ≠ org adoption speed; organizations change slowly
- •AI needs context; most company context isn’t written down anywhere
- •Expect multi-year transition with human-agent collaboration
- •Small, forward-leaning teams can move faster than established enterprises
- 39:42 – 41:33
Acquisition shock: Google AI answers cut a meaningful slice of new ARR
Monday’s customer acquisition machine takes a hit from Google’s AI mode reducing clicks on sponsored links. Eran quantifies the impact and explains how Monday reallocated budget to other channels with longer cycles, while most other acquisition sources stayed stable.
- •Google AI mode reduced sponsored link clicks and transactional intent capture
- •Impact: ~10% of acquisition/new ARR affected
- •Lost more SMB/transactional deals; shifted spend to longer-cycle channels
- •Diversified acquisition base: many other channels remained healthy
- 41:33 – 47:59
Capital allocation and morale: buybacks, insider behavior, and leading through drawdowns
Harry presses on share buybacks and personal purchases, then shifts to how to maintain morale when stock prices collapse. Eran details Monday’s buyback program, explains his trading constraints, and shares how he reframes extreme pessimism as fuel to execute and ‘go all in.’
- •Company buyback authorized; executed some and plans more over time
- •Eran on 10b5-1 constraints; leadership not selling; large retained ownership
- •Stock declines create real psychological strain; focus on controllables
- •‘If market says it’s worth zero, now we build’—offensive mindset
- 47:59 – 1:03:51
Public vs private, M&A restraint, and the ‘offensive bet’: agentic CRM + service
Eran argues being public can be an advantage by forcing urgency and clarity, and rejects taking Monday private. He explains why M&A is hard with private valuations and why winning depends on execution—then outlines the bold strategy: a horizontal agentic platform plus rebuilding CRM and service as fully agentic verticals.
- •Public markets deliver a harsh but clarifying signal; focus on offense
- •No desire to go private: strong cash position, FCF, retention, no need to raise
- •M&A constrained by private/public valuation mismatch; not a core win condition
- •Major bet: rebuild CRM + service from scratch as 100% agentic offerings
- 1:03:51 – 1:14:16
Quickfire: mindset shifts, leadership lessons, marriage advice, and optimism about AI’s future
In the closing rapid-fire, Eran cites AI as his biggest mindset change and acknowledges Monday must tell its story better. He shares personal leadership lessons about cycles, vulnerability and communication in relationships, and excitement about AI-driven quality-of-life improvements.
- •Biggest change: recognizing AI will fundamentally reshape software forever
- •Stinging truth: Monday can communicate strategy/story more effectively
- •Cycle lesson: don’t over-celebrate highs or internalize lows—execute over time
- •Marriage/leadership advice: communicate openly; vulnerability builds resilience
