“If there are problems in software, it will first start to show up in the riskiest part of the capital structure, which is equity. So that stands to reason. To me, too much press has been spilled on private credit and not enough focus on the fact that there’s a whole bunch of equity underneath that that is the first loss position, and that’s where you probably want to pay the most attention earliest.” – John Waldron – Goldman Sachs
Stress in software and technology financing rarely appears first where commentary is loudest. It tends to surface where contractual protection is weakest, cash flow sensitivity is highest, and valuations have drifted furthest from fundamentals. In contemporary capital structures supporting sponsor-backed software companies, that weak link is typically common equity, not the private credit sitting above it 1. Understanding why requires tracing how software businesses were capitalised through the low-rate era, how private credit stepped into the vacuum left by banks, and why equity investors quietly became shock absorbers for the entire structure.
The factual backdrop is a decade in which recurring-revenue software became the poster child for aggressive leverage. Ultra-low policy rates, abundant venture and growth equity, and a wave of sponsor-led buyouts combined to push valuation multiples to levels that assumed durable double-digit growth and minimal cyclicality. Private credit managers rushed to fund these deals, confident that high gross margins and subscription models would protect cash flows, while covenant packages were progressively loosened. Recent research from Goldman Sachs notes that roughly 23 % of the private credit market is now tied to software loans, a concentration that even industry insiders characterise as excessive by historical standards 7. Against that backdrop, the remark that problems will show up in equity first is not a reassurance so much as a reminder of how the hierarchy of pain actually works.
The speaker, John Waldron of Goldman Sachs, sits at the junction of several relevant vantage points: advisory to private equity sponsors, underwriting and distribution of leveraged finance, and a rapidly expanding private credit platform that now manages roughly USD 145 billion in private credit exposure 2. The firm has reorganised its global banking and markets unit into a Capital Solutions Group designed explicitly to intermediate across financing, origination, structuring, and risk management for corporate and sponsor clients 4. That reorganisation underscores an institutional bet that privately negotiated credit and hybrid financing will remain central to the funding of software and other growth sectors, even as public markets remain volatile.
The substantive claim embedded in the remark is straightforward: equity is structurally the first-loss tranche in a typical leveraged capital structure. Debt instruments in private credit deals are generally senior secured, with priority claims on assets and cash flows, contractual interest payments, and in many cases maintenance covenants that give lenders the right to intervene early. Equity, by contrast, has no contractual claim to cash, absorbs valuation volatility, and can be diluted, written down or wiped out without triggering defaults on the debt. When a software company encounters operational or growth problems, the first place the stress is visible is equity pricing, sponsor mark-downs, and downward revisions of forward projections, long before a payment default appears in the loan book.
To see this more formally in a finance framework, one can model the equity of a levered firm as a call option on the enterprise value. Let V_t denote the enterprise value at time t, D the face value of debt maturing at T, and r the risk-free rate. In a structural model, equity E_t can be represented as:
E_t = V_t N(d_1) - D e^{-r (T - t)} N(d_2)where N(\cdot) is the cumulative normal distribution and:
d_1 = \frac{\ln(V_t/D) + (r + 0,5 \sigma^2)(T - t)}{\sigma \sqrt{T - t}}, \qquad d_2 = d_1 - \sigma \sqrt{T - t}Here \sigma is the volatility of enterprise value. This framing makes Waldron’s intuition transparent. As \sigma rises or expectations for V_t fall due to weaker software fundamentals, equity values react sharply because they are effectively out-of-the-money or near-the-money options. The debt value, especially when senior secured, is comparatively insensitive until the probability that V_T < D becomes meaningful. In other words, early tremors show up in the equity option; the credit claim is hit later.
Software business models appeared to offer unusually favourable parameters for this option-like equity: high gross margins, recurring revenue visibility, and scalable cost structures. Sponsors extrapolated these characteristics into aggressive capital structures, assuming that revenue growth and pricing power would sustain interest coverage and allow rapid de-leveraging. Private credit funds, competing to provide unitranche and first-lien loans, often underwrote based on forward-looking pro forma EBITDA and contractual renewals rather than historic downturn performance. As long as software multiples remained high, equity cushions looked deep and reassuring.
However, that apparent cushion is acutely sensitive to small shifts in top-line growth and discount rates. Consider a simplified discounted cash flow representation for a software firm where enterprise value V is approximated by:
V = \frac{FCF_1}{r - g}with FCF_1 representing next period free cash flow, g the perpetual growth rate and r the discount rate. For high-growth software companies priced as if g is only marginally below r, even modest reductions in g or increases in r can trigger sharp contractions in V. If the firm carries substantial debt D, the equity value E = V - D can be compressed or eradicated long before the debt principal appears at risk. That is the mechanical reason why equity is where deterioration manifests first.
The post-pandemic tightening cycle intensified this sensitivity. Rising base rates increased funding costs, while inflation and wage pressures squeezed operating margins. At the same time, growth expectations for many software companies were revised downward as customers rationalised licences and delayed digital transformation projects. The equity markets reacted quickly: multiples for many high-growth names compressed, IPO windows partially shut, and late-stage venture funding became more selective. Yet the private credit portfolios financing the same companies often looked stable on the surface because borrowers continued to make interest payments and because portfolio valuations lagged public market repricing.
Waldron’s criticism that commentary has focused too heavily on private credit and too little on the equity beneath reflects this asymmetry in information and narrative. Private credit is relatively opaque: positions are not traded with public price discovery, covenants are confidential, and managers disclose performance with a delay. This opacity invites concern that a hidden bubble may be building among software loans. But in many leveraged software platforms, the true point of fragility is not the senior secured loan paying a 7 % to 9 % cash coupon; it is the equity slug that funded the acquisition at a 20x revenue multiple based on aggressive growth plans. When those plans falter, equity valuations must be recalibrated, and sponsors may find themselves injecting additional capital, selling assets, or accepting marked-down exits.
The creation of Goldman Sachs’s Capital Solutions Group is a strategic response to exactly this environment 2,4. By combining financing, origination, and risk management, the firm is effectively positioning itself to manage the full stack of capital from senior loans through mezzanine to equity and preferred instruments. That multi-layered vantage point reveals where risk truly sits in a structure. For a typical sponsor-backed software company, the capital stack might include a senior secured term loan, a revolving credit facility, possibly a second-lien or mezzanine tranche, and a substantial equity contribution from the sponsor and management. The private credit piece grabs headlines because of its size and growth, but the equity is what first absorbs the impact when revenue growth slows, churn rises, or new competitors erode pricing.
The technological context also matters. Software lending has been buoyed by the perceived defensiveness of subscription revenue and the rise of software-as-a-service in mission-critical functions. Yet the AI wave has created new uncertainty. On the one hand, incumbents may face disruption as AI-native competitors undercut them or offer better features. On the other, AI-driven productivity tools promise efficiency gains, but also require capital expenditure and strategic repositioning. Goldman’s own commentary on AI investment expectations suggests that it anticipates continued robust capital expenditure on AI infrastructure, particularly led by US hyperscalers 1. For software firms dependent on those platforms, changes in pricing, infrastructure costs, or competitive dynamics can rapidly alter unit economics, again feeding through to equity valuations long before credit metrics breach covenants.
Debate around private credit risk often centres on whether underwriting standards have weakened and whether concentration in sectors like software is dangerous. Critics argue that covenant-lite structures, aggressive leverage multiples, and a lack of mark-to-market transparency could store up trouble. Proponents counter that private credit managers have tighter relationships with borrowers, better information rights, and the ability to work constructively through periods of stress. Waldron’s emphasis subtly reframes the debate: even if some stress does emerge in software-linked private credit, it is unlikely to be the first or primary place where losses accumulate. Instead, equity investors in highly levered software deals are already experiencing a reset that will change the risk profile of the debt above them.
From a risk-transfer perspective, this is simply the pecking order of claims operating as designed. In a stylised capital structure, suppose a software company has enterprise value V = 800, senior debt D_1 = 500, junior debt D_2 = 100, and equity E = 200. If operational issues reduce V to 650, the entire 150 decline hits equity first, leaving E = 50 while both tranches of debt remain fully covered. Only once V < 600 do junior lenders face principal impairment, and senior lenders are not at risk until V falls below 500. Empirically, that means that by the time private credit portfolios start to show meaningful realised losses, equity investors are likely to have endured a prolonged period of write-downs, down-rounds, and unfavourable exits.
One objection to the argument is that equity valuations in private markets are themselves opaque, so relying on equity as an early warning signal may not be straightforward. Sponsor marks can lag reality, especially where there is no transaction to force a repricing. However, several practical indicators exist: reduced bidding for new software assets, an increase in broken auction processes, widening gaps between buyer and seller expectations, more frequent use of structured equity solutions, and sponsors injecting additional preferred equity to support over-levered portfolio companies. These behaviours are the qualitative signs that equity is absorbing stress. Lenders involved in capital solutions work will see these signals well before a payment is missed on a private credit instrument, which strengthens Waldron’s case that attention should be directed there.
Furthermore, software as a sector amplifies equity risk because its intangible asset base offers limited hard collateral. When lenders underwrite against recurring cash flows and customer contracts, recovery values in a default scenario are highly uncertain. Source code, customer lists, and data have value, but often far less than the optimistic projections baked into the original deal. This makes the presence of a deep equity cushion more critical: equity holders are the ones effectively underwriting the uncertainty in those intangible values. A thin or rapidly eroding equity layer should therefore be a red flag not only for sponsors but for lenders who have relied on that buffer as part of their loss-absorbing structure.
The comment also points to a broader narrative tension: the media appeal of a looming private credit crisis versus the less dramatic but more probable story of prolonged equity pain and restructuring in software portfolios. Predicting a systemic private credit event is headline-grabbing, yet the more subtle reality may be a drawn-out process of sponsor-led recapitalisations, minority stake sales, and operational turnarounds that gradually reconcile inflated entry valuations with more modest cash flow outcomes. For institutions like Goldman Sachs, which straddle advisory, lending, and asset management, the objective is not only to avoid losses but to position themselves as indispensable intermediaries in this adjustment process.
In that sense, the expansion of Goldman’s private credit and alternatives capabilities is both a risk and an opportunity 2,6,8. On the one hand, increased exposure to software-heavy private credit portfolios means the firm is deeply intertwined with the sector’s fortunes. On the other, the ability to deploy fresh capital into recapitalisations, structure preferred equity or convertible instruments, and engineer liability management transactions allows it to influence where value ultimately settles in the capital structure. If equity investors have already absorbed substantial losses, new capital providers can negotiate favourable terms, effectively resetting the stack in their favour.
For allocators evaluating private credit funds with material software exposure, the practical implication of Waldron’s point is clear: analysis cannot stop at lender protections and yield. It must extend to the resilience of the equity beneath. Key questions include the entry valuations at which sponsors acquired assets, the magnitude and terms of any subsequent equity injections, the extent of operational improvements realised versus pro forma, and the degree to which AI and other technological shifts may disrupt core customer value propositions. Lenders who merely look at historical default and recovery statistics for software lending without interrogating these equity dynamics risk underestimating tail risk.
Equally, for software company executives and boards, the message is that equity market discipline is already back. The era when abundant private capital would fund perpetual growth without close scrutiny has faded. As AI changes cost structures and competitive moats, and as higher rates persist, equity will continue to bear the brunt of experimentation and missteps. Private credit remains available, but is likely to price risk more discriminately and insist on clearer visibility into how equity sponsors will support businesses through volatility.
The broader significance of this perspective lies in its reminder that capital structures are ecosystems. Focusing on a single layer in isolation, whether equity or private credit, can be misleading. In software-heavy portfolios, where cash flows are promising but uncertain, and technological trajectories are in flux, the interaction between layers determines where losses land and where new value is created. By insisting that scrutiny turn first to the equity that stands in the first-loss position, Waldron is not exonerating private credit from risk; he is demanding a more sophisticated conversation about where fragility actually resides and how it will propagate through the stack over time.
References
1 Sonali Basak, “Goldman’s AI Expectations” (LinkedIn analysis of Goldman Sachs commentary on AI and infrastructure spending).
2 Institutional Investor, “Goldman Expands Private Credit Ambitions With Major Overhaul”.
3 ETF Database, “Scaling RIA Growth: The Goldman Sachs AI Playbook”.
4 Goldman Sachs Press Release, “Goldman Sachs Announces Creation of Capital Solutions Group”.
5 Goldman Sachs Asset Management, “Private Equity” product overview.
6 Goldman Sachs Asset Management, “Private Credit” product overview.
7 Goldman Sachs Research, “Cracks in Private Credit” (redacted report on sectoral concentration and leverage in private credit).
8 Private Debt Investor, “Goldman Sachs chases demand for private credit”.
References
1. “Goldman’s AI Expectations” – https://www.linkedin.com/pulse/goldmans-ai-expectations-sonali-basak-ixg8e
2. Goldman Sachs’ John Waldron Dismisses AI Capex Concerns, Says … – 2026-05-12 – https://stocktwits.com/news-articles/markets/equity/goldman-sachs-john-waldron-ai-capex-continue-healthy-clip/cZXXiL8Reii
3. Goldman Expands Private Credit Ambitions With Major Overhaul – 2025-01-14 – https://www.institutionalinvestor.com/article/2eaad054qel0icuwrgcu8/corner-office/goldman-expands-private-credit-ambitions-with-major-overhaul
4. Scaling RIA Growth: The Goldman Sachs AI Playbook – ETF Database – 2026-05-13 – https://etfdb.com/future-etfs-content-hub/goldman-sachs-ai-playbook/
5. Goldman Sachs Announces Creation of Capital Solutions Group – 2025-01-13 – https://www.goldmansachs.com/pressroom/press-releases/2025/creation-of-capital-solutions-group
6. Private Equity – Goldman Sachs Asset Management – 2026-03-05 – https://am.gs.com/en-us/advisors/products/private-equity
7. Private Credit – Goldman Sachs Asset Management – 2026-01-28 – https://am.gs.com/en-us/advisors/products/private-credit
8. [PDF] CRACKS IN PRIVATE CREDIT | Goldman Sachs – 2026-04-27 – https://www.goldmansachs.com/pdfs/insights/goldman-sachs-research/cracks-in-private-credit/TOM_private%20credit_Redacted.pdf
9. Goldman Sachs chases demand for private credit – 2025-01-21 – https://www.privatedebtinvestor.com/goldman-sachs-chases-demand-for-private-credit/
10. Goldman Sachs Private Credit Fund LLC – SEC.gov – 2022-12-31 – https://www.sec.gov/Archives/edgar/data/1920145/000119312523077970/d410243d1012g.htm
