Description

In this episode, Dave "CAC" Kellogg and Ray "Growth" Rike go point-counterpoint on two high-profile articles making waves across Wall Street and Silicon Valley: Citrini's provocative February 2025 report, The 2028 Global Intelligence Crisis, and Citadel's rebuttal, The 2026 Global Intelligence Crisis.

Dave and Ray unpack whether AI is truly triggering an unprecedented economic collapse or whether Citrini's dark simulation is, as one economist put it, just "a scary bedtime story." They dig into the SaaS private credit contagion theory, the historic parallels of labor displacement, the role of government regulation, and why this particular AI scare hits closer to home than any previous tech disruption. As always, the brothers bring the receipts, including nearly 20 sources and 20 hours of research - so you don't have to.

Full Episode Summary:

Dave Kellogg and Ray Rike open by framing the episode as a tale of two AI futures: Citrini's alarming speculative simulation versus Citadel's data-driven rebuttal.

The Citrini Case (Bear Case): Published February 22nd, Citrini's report simulates a scenario in which rapid AI agent adoption triggers a global intelligence crisis by mid-2028 featuring 10.2% unemployment and a 38% drop in the S&P 500. The report argues AI is categorically different from prior technology waves because it displaces cognitive workers, who represent roughly 75% of U.S. labor income.

Citrini further warns that SaaS, already accounting for 23% - 25% of the $3 trillion U.S. private credit market could become the chip in the windshield that cracks the broader financial system, with ripple effects into insurance and the broader economy. Dave and Ray note that Citrini's word choices ran 3.4-to-1 negative, and flag that the firm may hold short positions — characterizing the piece as well-crafted "bear porn."

The Citadel Rebuttal (Bull Case): Two days later, Citadel, a $65B AUM asset manager with 35 years of credibility responded with a data-driven defense. Software engineering jobs are up since January 2024, AI CapEx is 2% of GDP and AI-adjacent commodity pricing is up 65%. Citadel argues AI follows historical S-curve adoption patterns, that "recursive capability doesn't equal recursive adoption," and that technology has always complemented rather than replaced labor - pointing to Microsoft Office as a historical analogue.

Dave and Ray's Take: Both hosts find Citadel more credible, but acknowledge real displacement risks ahead. Their key insight: the reason this particular AI scare is generating 10x more fear than past labor disruptions (auto workers, telephone operators, elevator operators) is that this time it's us — white-collar knowledge workers facing displacement. Ray adds that blue-collar jobs (truck drivers, Uber drivers, warehouse workers) face equal or greater long-term risk from AI plus robotics, but those disruptions don't generate the same visceral fear in the media and investor class. Both agree the timing of adoption is the biggest unknown. Long-term, history favors the Citadel view. Short-term, the transition could be painful.

On Government Response: Dave and Ray agree that political and regulatory intervention is inevitable if unemployment spikes materially, whether through labor protections, AI regulation, or fiscal stimulus.

On Economists' Reactions: Real economists, including Noah Smith (Noahpinion) and Wharton's Jeremy Siegel, largely dismissed the Citrini piece, wi Siegel arguing that productivity gains generate new income and demand, Smith calling it a "scary bedtime story." Dave's takeaway for operators: let the Metrics Brothers do the 20 hours of reading so you don't have to.

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In this episode, the Metrics Brothers, Dave "CAC" Kellogg and Ray "Growth" Rike dive deep into the ICONIQ State of AI: Bi-Annual Snapshot Report. Published in January 2026, this 44-page report summarizes insights from ~300 software executives on the front lines of building and scaling AI products.

Ray and Dave explore a market transition from experimental model races to the challenge of building durable, economically sound products. Key discussions in this episode include:

• Differentiation Beyond the Model: Why 69% of builders are focusing on vertical AI applications and why 49% cite the application layer (UX and workflows) as their primary competitive edge over the underlying model.

• The Gross Margin "U-Curve": A look at the shifting economics of AI, where aggregated gross margins are projected to climb to 52% by 2026, even as inference and infrastructure costs remain significant hurdles.

• Pricing Evolution: The rise of outcome and usage-based pricing, with only 23% of companies still relying on seat-based models as customer demand shifts toward value-aligned monetization.

• AI as an Internal Force Multiplier: How R&D teams are leading internal adoption, with 83% of companies now measuring success through productivity gains and 59% through direct cost savings.

Whether you are a CEO or CFO navigating AI product gross margin concerns or a GTM leader rethinking your proof-of-concept strategy, this episode provides the benchmarks you need to understand the "new phase of maturity" in the AI market.

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In this extended episode, the Metrics Brothers tackle the "elephant in the room" - the SaaSpocalypse. With nearly $1 trillion in market value wiped out recently, Ray and Dave go beyond the stock market headlines to analyze the structural shifts hitting the industry.

The duo breaks down the three primary drivers of the current market "carnage", including the AI Fear of Being Obsolete (FOBO), Regression to the Mean for SaaS stocks and Changing Valuation Methodologies, before diving into the newly released Aviner report, The Future of SaaS: A Fork in the Road. Using Aviner’s "Red Pill vs. Blue Pill" metaphor, they debate whether SaaS companies must fundamentally pivot to "agentic" systems or accept maturity and financialize by focusing on profitability.

Covered in This Episode:

The SaaSpocalypse Explained: Why the stock market is currently a "rugby scrum of information" and why stock price is a measure of future expectations rather than current health

ServiceNow as a Bellwether: An analysis of how a "Rule of 56" company can beat expectations and still see a 30% stock drop in a single month.

FOBO (Fear of Being Obsolete): How the "revenge of build vs. buy" and the collapsing cost of coding are demoting traditional SaaS apps to mere systems of record.

The Aviner Report Breakdown:

• Part 1: The hard data on slowing revenue growth (cut from 40% to 20%) and the "aberration" of 2019–2021 multiples.
• Part 2: The binary choice between embracing AI "Systems of Context" or financializing for net income.

The "Architect Strategy": Ray’s argument for a third path where SaaS companies coexist with AI by providing the governance and orchestration layer

Buyer Sentiment vs. Market Narrative: Why 63% of software buyers believe existing vendors will be the beneficiaries of AI, contradicting the current "SaaS is dead" stock market trend.

Key Metrics & Concepts Mentioned

• Rule of 40 vs. Rule of 60: How the standard for SaaS health is shifting
• Stock-Based Compensation (SBC): Why excluding this from profitability metrics is no longer passing the "financialization" test
• The Three-Layer Taxonomy: Systems of Record, Systems of Engagement, and Systems of Context
• Multiple Compression: The shift from 15x revenue multiples back to the historical 5x mean

Resources Mentioned

• Report: The Future of SaaS: A Fork in the Road by Aviner Growth (Jan 2026).
• Book: The Reckoning by David Halberstam.
• Book: Profit Pools by Orit Gadiesh and James L. Gilbert.

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In this episode of the Metrics Brothers podcast, Ray Rike and Dave Kellogg tackle one of the most critical yet misunderstood metrics in the U.S. economy: Labor Productivity. Amidst the rapid rise of Artificial Intelligence, the "Metrics Brothers" break down how productivity is officially measured by the Bureau of Labor Statistics and why historical technology booms, from SaaS to Cloud, haven't always moved productivity growth as much as expected.

Key Takeaways: A deep dive into the ratio of economic output per hour worked, including what the BLS excludes (farms and government) and the nuances of white-collar labor tracking.

• Historical Trends: A comparison of the post-war boom versus the "SaaS era," exploring why the last 20 years have seen a 66% relative decrease in productivity growth despite trillions in tech investment.
• The AI Impact: Three potential scenarios for the future of work, from "exploding output" to "labor displacement," and why AI might fundamentally remake work in ways the Cloud never did.
• Global Benchmarking: How the U.S. stacks up against leaders like Ireland and Norway in output per hour.

Why Listen? Whether you are a SaaS leader, investor, or white-collar professional, this episode provides a roadmap for staying on the "right side of the divide" in the upcoming AI-driven economic shift.

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Brand is one of the most powerful assets a company can build and one of the hardest to measure. In this episode of The Metrics Brothers, Dave “CAC” Kellogg, and Ray "Growth" Rike take on one of marketing’s most persistent challenges: how to measure brand in a world obsessed with direct attribution and near-term ROI.

The conversation starts with what a brand really is, originating from literal marks of ownership and evolving into a promise of quality, trust, and differentiation. From there, Ray and Dave explore why strong brands create pricing power, customer loyalty, category leadership, and long-term defensibility, even if those benefits do not always show up cleanly in dashboards.

They then break down practical ways to measure brand that align marketing and finance perspectives, including indirect valuation approaches such as brand value and goodwill frameworks, along with comparative metrics like direct and branded web traffic, share of voice, share of search, and inbound pipeline contribution. The episode also covers market research fundamentals including awareness, consideration, trial, and repurchase, and why dedicating a portion of your marketing budget to measurement is essential to sustaining brand investment.

Finally, the Metrics Brothers dig into brand measurement techniques that work in practice, including self-reported attribution, lift experiments, and analyzing sales conversations to see how brand shows up late in the buying process, often at the exact moment a deal is won.

If you have ever struggled to align brand investment with measurable outcomes, justify brand spend alongside demand generation, or connect long-term brand building to real business results, this episode provides a grounded, metrics-driven framework for doing exactly that.

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The State of Generative AI in the Enterprise 2025

In this episode of The Metrics Brothers, Ray Rike and Dave Kellogg break down the 2025 State of Generative AI in the Enterprise report from Menlo Ventures and explain what the data really says about where enterprise AI adoption is accelerating and where the market is consolidating.

The headline takeaway: AI software is scaling faster than any software category in history. Enterprise AI spend has exploded from roughly $1.7B in 2023 to nearly $37B in 2025, reaching scale in just three years. This revenue milestone took SaaS more than 15 years to achieve. Foundational models now represent the single largest area of spend, highlighting how infrastructure and model access remain core to enterprise AI strategies.

Ray and Dave also explore a major strategic shift inside the enterprise: buy is decisively beating build. In 2025, 76% of enterprise AI solutions are purchased rather than built internally, up sharply from 53% the year prior. Rapid model evolution, ongoing retraining costs, and model drift are making internal AI development far more expensive to maintain than many teams originally expected.

One of the most surprising findings is on go-to-market efficiency. AI software pilots convert to production at nearly twice the rate of traditional software, with roughly 47% of AI pilots reaching production versus about 25% for conventional enterprise software. This runs counter to recent narratives suggesting enterprise AI pilots are stalling and points to clearer ROI and faster time-to-value.

The episode also dives into what Menlo calls the first true “AI killer app”: AI-assisted coding. Coding tools now account for more than half of departmental AI spend, with over 50% of developers already using AI coding assistants and adoption exceeding 65% among top-quartile teams. Real-world examples show meaningful productivity gains, including double-digit increases in development velocity and significant time savings during legacy system upgrades.

Industry-wise, healthcare emerges as the largest buyer of vertical AI, representing 43% of vertical AI spend. This is notable given healthcare’s historically lower IT spend as a percentage of revenue. Much of the value is coming from administrative automation such as medical scribing, where AI directly reduces non-clinical workload and unlocks meaningful productivity gains for care providers.

Finally, Ray and Dave examine the shifting competitive landscape among foundation model providers. Anthropic has surged to roughly 40% share of enterprise AI usage, up dramatically from prior years, while OpenAI’s share has declined as Google continues to gain traction. The discussion centers on focus versus breadth and why enterprise positioning and reliability may matter more than consumer mindshare.

Key takeaways from the episode:

• AI software is the fastest-scaling software category ever
• Enterprises are rapidly moving from build to buy
• AI pilots convert to production at nearly 2x traditional software
• AI coding is emerging as the first true enterprise AI killer app
• Anthropic’s enterprise focus is translating into meaningful market share gains

If you care about how AI adoption actually translates into spend, productivity, and competitive advantage inside large organizations, this episode is a must-listen.

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The claim that “95% of AI projects fail” has become one of the most repeated talking points in enterprise AI. But where did it come from, and does it actually hold up?

In this episode, Dave "CAC" Kellogg and Ray "Growth" Rike take a detailed, data-driven look at the MIT NANDA report, titled The GenAI Divide: State of AI in Business 2025. They break down how the "95% fail rate" statistic went viral, why it stuck, and why the underlying evidence does not support such a sweeping conclusion.

What Ray and Dave cover:

• Why the NANDA report is often mistaken for a peer-reviewed academic study when it is not
• How ambiguous definitions of “failure” turn partial adoption into sensational headlines
• Data inconsistencies and methodological gaps that undermine the 95% claim
• The difference between failed AI initiatives and early-stage pilots or experiments
• Why measuring AI success by the percent of projects is misleading compared to the business value created
• The rise of Shadow AI and employee-driven adoption, and why that may be a feature, not a flaw
• How the report’s conclusions conveniently align with the authors’ proposed NANDA architecture
• The real issues enterprises face with AI: workflow integration, governance, and change management

The episode also discusses why personal productivity gains still matter to the P&L, even if they do not appear as a clear line item, and why fear-driven AI narratives can do real damage within organizations.

Key takeaway:

The NANDA report raises some legitimate concerns about scaling AI from pilot to production, but the infamous “95% of AI projects fail” claim does not survive close inspection. Leaders should read the report skeptically and push back when flawed statistics begin to drive decisions and strategy.

Recommended for:

CFOs, operators, AI leaders, and anyone tired of scary AI statistics that fall apart under scrutiny.

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Brand vs Demand: Why B2B Marketing Is Stuck in a Measurement Trap

In this episode of The Metrics Brothers, Dave "CAC" Kellogg and Ray "Growth" Rike tackle one of the most persistent and controversial questions in B2B marketing: Brand vs. Demand.

The discussion is grounded in new data from the 2026 B2B Brand vs Demand Benchmark Report. While most marketing teams say they believe brand and demand are complementary, the numbers tell a more complicated story.

Today’s reality?

Marketing budgets are still heavily skewed toward short-term demand generation, with roughly 70% of spend allocated to demand and only ~25% to brand. Yet when asked how they want to invest, marketing leaders overwhelmingly say they’d prefer a much more balanced future, closer to 50% demand and 40% brand.

So why the disconnect?

Ray and Dave dig into the root cause: measurement.

Demand generation is tied to metrics CFOs understand like pipeline dollars, opportunities, and ARR. Brand, on the other hand, is still largely measured using proxy metrics like website traffic and awareness, leaving many executives unable to confidently link brand investments to revenue outcomes. Only 28% of companies say they can directly tie brand activity to pipeline, and when budgets are cut, brand is sacrificed five times more often than demand.

The episode also explores:

• Why performance marketing struggles are pushing CMOs back toward brand
• The growing inefficiency of demand spend aimed at “future buyers”
• How much of the “demand” budget is effectively unmeasured brand spend
• The dangerous gap between belief in brand and proof of impact
• Why AEO, AI search, and LLM visibility will make brand ROI even harder and more urgent to measure

Ray and Dave don’t just highlight the findings, they discuss the reality of Chief Marketing Officers making the Brand vs Demand budget allocation trade-offs.

One key takeaway? Until brand investments can be credibly connected to pipeline efficiency, win rates, and ARR, it will remain more a faith-based investment instead of a financial one the CFOs understand.

If you’re a CMO trying to defend brand spend, or a CFO trying to understand where marketing dollars truly drive growth, this episode is required listening.

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In this episode of The Metrics Brothers, Dave "CAC" Kellogg and Ray "Growth" Rike break down the 2025 Tidemark Vertical & SMB SaaS Benchmark Report. Drawing from data across 200+ companies, the report explores control points, multi-product expansion, fintech monetization, and AI adoption, but not all conclusions hold up under scrutiny as they are sometimes take on the tone of a narrative summary rather than insights purely from data-backed research.

Ray and Dave dig into what the data actually supports versus where narrative may be running ahead of evidence. They unpack the concept of “control points,” examine why fintech (especially payments) continues to dominate expansion strategies, and challenge whether multi-product really delivers the retention and growth advantages many assume. Along the way, they highlight where benchmarks are useful, where definitions blur, and why context matters more than ever.

The episode also explores the rapid rise of AI inside Vertical SaaS, from attach rates to monetization models and asks the hard question: "Does AI actually drive better performance, or is it simply becoming table stakes?"

If you’re building, investing in, or operating a vertical SaaS business, this episode helps separate signal from story.

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In this episode of The Metrics Brothers, Ray Rike and Dave Kellogg unpack Benedict Evans’ latest landmark presentation, AI Eats the World, and explore why this moment may rival or even surpass the original “software is eating the world” era. Drawing parallels to Marc Andreessen’s 2011 thesis, they examine how AI is no longer just another platform shift, but a force capable of reshaping labor, capital allocation, and entire industries at once.

The conversation spans the explosive rise in AI infrastructure spending, from hyperscaler capex surging past $400B to the growing strain on power, compute, and supply chains. Ray and Dave discuss why this moment feels different from past tech cycles, not just because of scale, but because AI directly targets labor, which represents more than half of global GDP. They explore whether AI is creating real moats or accelerating commoditization, and why many enterprises are still stuck in experimentation rather than true deployment.

The episode also dives into historical parallels from elevators and telephone operators to cloud computing highlighting how software enabled automation always feels threatening before it quietly becomes invisible.

Along the way, they unpack the strategic tension facing AI leaders: go down the stack for scale or up the stack for value capture. With insights on hyperscalers, OpenAI, Oracle, and the economics of AI adoption, this episode challenges leaders to rethink how value will actually be created and captured in the age of AI.

If you want to understand what’s hype, what’s durable, and why “AI eating the world” may be the most consequential shift since the internet itself, this episode is a must-listen.

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