Marc Romano

The software landscape in early 2026 is undergoing what many analysts are calling a 'Great Reckoning'. The rules that built your SaaS company are quietly being rewritten. And most founders won’t realize it until their valuation tells them. The recent pullback in giants like Salesforce and Workday isn't just a market "dip"; it’s a structural re-evaluation of how software is built, priced, and sold. For privately held companies, this has shifted the "valuation game" from a focus on growth at all costs to a rigorous defense of their long-term moat in an AI-native world. Private software companies are no longer being valued on simple revenue multiples alone. Investors are now running "AI stress tests." If your private company depends on selling seats to human workers who do repetitive tasks, your valuation multiple has likely compressed by 30–50% compared to 2024. Here is what I think existing privately held companies need to do in this AI disruption era. 1. Use your existing customer data (securely and ethically) to fine-tune "Small Language Models" (SLMs) that perform better than GPT-4 on specific industry tasks. 2. The workflow is the moat. If your software is where the user spends their day, your AI features will be more "sticky" than a standalone AI tool. 3. Instead of charging per user, charge based on the outcome (e.g., "per claim processed" or "per campaign generated"). 4. Position your software as a "digital employee" rather than a tool. If your software can autonomously handle 80% of a task, you can capture a portion of the labor cost you are saving the client. 5. As a private company, you can pivot your entire roadmap in a short period of time. Don't be afraid to kill a legacy feature if an AI-native version makes it obsolete. 6. One major weakness of AI is "hallucination" and lack of precision. Private software companies can win by building a deterministic layer over the probabilistic AI. Wonder if there are any other scenarios to survive for software companies in this AI disruption era?

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Lucky to work with people like Laura Sánchez-Quiñones Campuzano at IDC Ventures. Sharp take on how AI is reshaping the software stack and what that means for SaaS business models.

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Too many teams treat PAS 2080 as a reporting burden. It’s not. It’s a competitive filter. What we’ve laid out here is a faster, cleaner path to compliance, aligned to how preconstruction processes already work. Required reading if your bids are heading into regulated territory 👇 https://lnkd.in/eQWZQVB8

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I consolidated a PE-backed portfolio company's tech stack from 18 systems to 4. The initial pitch to the board: "This will streamline operations." The reframe after I walked them through the numbers: "This eliminates $780K in annual SaaS spend, improves adjusted EBITDA by 4 points, and at our 6x exit multiple, that's $4.7M in additional enterprise value." Same operational project. Different lens. This is the difference between executing a Value Creation Plan and driving exit value. Most operators focus on the work itself, faster, cleaner, more efficient. But when you have equity in the deal, you start asking different questions: "How does this decision translate to the exit multiple?" I've led this type of operational work across 5 PE-backed acquisitions totaling $3.4B+ in exit value. The operators who drive the highest returns aren't just executing plans, they're building enterprise value with every decision. When I take board seats, this is the first mindset I install with portfolio company leadership teams: Think like an owner, not an employee. Why? The best operational improvements are the ones that compound directly to exit value.

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If you’re a CEO/founder or PE operator and your tech org is: ❌ Shipping late ❌ Stuck in reactive mode ❌ Struggling through the Series A/B jump, or post-acquisition integration or after a major release It’s not “a delivery problem.” It’s an operating model problem. At the inflection point, the old playbook breaks: what worked at 10 engineers fails at 40… and breaks again across multiple products/teams. That’s where I come in as a fractional CTO: - Spot platform and delivery risks before they hit revenue and retention - Rebuild execution rituals (prioritization, ownership, release confidence) without derailing the roadmap - Align architecture + team structure to your value-creation plan (growth, margin, or exit timeline) If you’re feeling the strain of growth, I can help you turn “busy and reactive” into predictable shipping, and a platform that scales. #CTO #SaaS #StartupScale #PrivateEquity #TechStrategy

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Most SaaS companies believe they understand their customers - until a renewal falls through without warning. QuadSci's co-CEOs saw this pattern at Elastic and MuleSoft and concluded the real problem wasn't data: it was signal. Their platform processes trillions of product telemetry events to predict churn and expansion up to 18 months out, with 94% accuracy. Find out why enterprise customers managing billions in at-risk ARR are betting on behavioral data over gut instinct, and what QuadSci's $8M raise means for the future of go-to-market intelligence.

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SaaS leaders, imagine reclaiming 25-30% of your team's lost productivity..... Distractions alone cost enterprises billions yearly, while disengaged employees drain profits at $550B globally. Workforce analytics changes everything: real-time tracking of active/idle time, app usage, and screenshots reveals hidden gaps, from skill mismatches to burnout risks. Top teams using these insights balance workloads, predict attrition 3x better, and drive 40% output gains without micromanaging. In 2026, it's your edge for scaling efficiently What do you think ??? How much hidden productivity is your team losing? Comment below!

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