After 122 episodes covering SaaS metrics, GTM analytics, and the evolving world of AI-native software, Dave "CAC" Kellogg and Ray "Growth" Rike announce that The Metrics Brothers podcast is going on hiatus.

In this abbreviated special episode, Ray and Dave reflect on what made the show work, what made it hard, and why now is the right time to take a pause. They share their top-performing episodes across 122 weeks, including the all-time most-listened episode on NRR, a breakout episode on pipeline generation, and the Intercom AI transformation episode that set a record for first-week downloads.

They also explain the primary driver behind the break: AI changed the subject matter faster than their accumulated operator experience could keep up. What started as two veterans trading war stories about metrics they had lived with for decades became something that required more prep, more research, and more time to do with the quality they demanded. Both hosts decided they would rather spend more time inside AI from an operator's perspective to gain real-life AI experience, then return with better stories to tell.

Ray shares his plans to accelerate the AI to ROI podcast and newsletter, expand AI benchmarking initiatives with partners including Scale Ventures, and build out advisory services for companies trying to measure and justify AI business impact. Dave will be putting more time into Kellblog, deepening his work with the Balderton Capital portfolio and his advisory clients.

The Metrics Brothers consistently ranked in the Top 25-50 on Apple Podcasts in the Business Management category. All 122 episodes remain available in the archive.

Listeners with feedback or ideas for what comes next can reach the Metrics Brothers at metricsbros@benchmarkit.ai.

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Salesforce made waves in February 2026 by introducing the Agentic Work Unit, or AWU, as a new way to measure and potentially price AI agent activity. The Metrics Brothers, Ray "Growth" Rike and Dave "CAC" Kellogg dig into whether the AWU is a legitimate step toward outcome-based pricing, a vendor-specific adoption metric, or just another awkward intermediate measure in the long, messy history of software pricing models.

Episode Highlights:

• Tokens are not business metrics. Ray and Dave open by drawing a clear line: tokens measure text processing and compute consumption, not business outcomes. Nobody walks into a board meeting announcing they processed 14 billion word fragments, and enterprise buyers should not be priced on that basis.
• What Salesforce is actually trying to do with the AWU. Defined as "one discrete task accomplished by an AI agent," the AWU is Salesforce's attempt to bridge the gap between low-level compute metrics and business outcomes. The hosts debate whether it is a pricing metric in waiting, an AI adoption signal, or simply the best available approximation of work performed by agents.
• A short history of bad pricing units. From CPU counts to MIPS to kilocharacters to gigabytes, Ray and Dave trace the long, humbling history of software vendors searching for a pricing metric that maps to value. The Soviet chandelier analogy makes an appearance, courtesy of Appian CEO Matt Calkins.
• Activity versus outcome: the core tension. Ray argues the AWU is directionally right but fundamentally an activity metric, not a true economic outcome. Dave is more skeptical that outcome-based pricing can scale broadly, pointing out that customers say they want value-based pricing until a vendor actually tries to take a cut of the upside.
• Vertical AI applications have the clearest path. Both hosts agree that verticals with well-defined, countable outputs, such as cases resolved in customer support or claims processed in insurance, are best positioned to price on outcomes and may not need the AWU at all.
• The AWU needs a new name, and probably a new definition. Ray and Dave close with the observation that just as NRR took nearly a decade to emerge as a standard SaaS metric, meaningful AI metrics will take time to mature. The AWU, as currently defined, is a Salesforce-specific construct and unlikely to become an industry standard.

If you are a B2B SaaS or AI-Native software operating executive, this conversation on one of the first agentic AI metrics to measure work activity is a great listen.

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What happens when a $6.4 billion PE buyout becomes a cautionary tale for every SaaS operator, investor, and board member? In this episode, Dave "CAC" Kellogg and Ray "Growth" Rike break down Private Credit: what it is, how it works, and why it is showing up everywhere from venture rounds to leveraged buyouts. Then they walk through the Medallia deal step by step to show exactly how the model breaks.

What we covered:

Private credit 101: from venture debt to leveraged buyouts

Private credit is non-bank lending done by funds instead of banks, with a repayment-first mindset rather than a returns mindset. Capital deployment hit nearly $600 billion in 2024, up 78% from 2023, with 22 to 25% of that concentration in SaaS companies. Ray and Dave explain the difference between venture debt (lending to startups post-round) and direct lending (providing the "L" in LBO transactions), and why these structures have moved from niche to standard in software finance.

How debt is priced and why it costs what it costs

Private credit loans are floating-rate instruments priced at SOFR plus 500 to 800 basis points. In the zero-rate era that meant 6 to 9% all-in. Today it means 10 to 13%. Dave explains warrants as the "sweetener" (typically 5 to 15% of the loan amount, translating to under 2% equity ownership) and why the real economic driver is repayment, not upside. Ray frames the contrast with VC math: a lender who loses principal on one deal has no portfolio-level offset.

The terms that matter: PIK, bullets, and covenants

Pay-in-kind interest defers cash pain today by adding to the principal balance tomorrow. A $100M loan PIK-ing at 10% annually becomes $121M in two years and $133M in three. Bullet loans put the entire principal due at maturity, which for most companies means refinancing or a sale event. Dave's strongest language is reserved for covenants, which he calls the "third rail": liquidity, EBITDA, ARR growth, and coverage ratio thresholds that give lenders the right to call the loan if tripped. He argues these belong on page one of every board dashboard, every time.

The Medallia case study: when all the assumptions move against you

Thoma Bravo acquired Medallia in 2021 for $6.4 billion at 9x revenue, with roughly $1.8 billion of debt backed by Blackstone, Apollo, and KKR. The deal was underwritten on continued growth and margin expansion toward 25% free cash flow. Instead, growth slowed, base rates rose more than 400 basis points, PIK interest compounded the balance from $1.8B to $2.2B, and EBITDA of $200M fell below annual interest expense of $300M. Interest coverage dropped below 1x. Thoma Bravo's $5 billion equity investment went to zero. Lenders took the keys via debt-for-equity conversion.

Why these structures can look stable and then break fast

The Medallia deal was not unusual at entry. The problem was that PIK, rising rates, and slowing growth are individually manageable and jointly lethal. By March 2026, Blackstone was marking its first-lien Medallia debt at 60 cents on the dollar. Ray notes that between 2015 and 2025, more than 1,900 software companies were acquired by PE in deals worth over $440 billion, and 20 to 25% of all private credit went to SaaS. The exposure across the sector is large.

The lesson Rory O'Driscoll would underline

Dave closes with a line from Rory O'Driscoll: as soon as something becomes a formula, the play is probably over. Private credit for SaaS worked reliably for nearly a decade. The combination of higher rates, compressed multiples, and closed IPO and M&A windows revealed that the formula was underwriting a world that no longer existed. Senior debt gets paid first. When the debt is impaired, the equity is gone. The math does not negotiate.

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