Tim Salikhov, CFA

The SBA just implemented SOP 50 10 8 guideline changes... Here's what every buyer and investor needs to know: 1. 10% Equity Injection Now Mandatory Remember when you could count seller financing on 2-year standby as equity? That’s gone. Now you need hard equity for at least 10% of the purchase price, seller notes can still count for up to half of that required equity, but it has to be on full standby for the ENTIRE loan term, not just 2 years. Overall, I see this as a beneficial change, we see a lot of deals and 90-95%+ leverage deals break way more often than <80% leverage. The majority of deals we see getting done and set up for success are with ~20% of equity down. 2. Multi-Step Buyouts Are Dead This one hurts… The SBA now requires all ownership changes to happen in a single closing. Gone with the tiered buy-out approach. I was just talking with an HVAC owner last week who wanted to gradually transition his business to his service manager over 5 years. That elegant structure used to be pretty common with employee buyouts. Now it’s impossible with SBA financing. We're going to need entirely new capital strategies for employee transitions or partnerships – and that's a huge problem because gradual handoffs are perfect for many business owners who wanted to slowly phase into retirement and train the new owner. 3. Co-Borrower Requirements Will Kill Seller Equity Rolls This one is brutal. If a selling owner retains any ownership after closing (even less than 20%) they must personally guarantee the loan for two years post-sale. Layer in that all new equity holders even 1% passive investors will be classified as a co-borrower is the nail in the coffin for seller equity roll deals. This change will effectively eliminate seller equity rolls in SBA deals. Convincing a seller to personally guarantee millions of debt betting on the acquirer they just met a couple months ago, is not going to work. Overall, this is horrible for individual buyers reliant on the SBA. Big win for shops who have access to non SBA debt. 4. Expansion Exception to Equity Injection No equity injection is required if: - The buyer and seller entities share identical ownership - They operate under the same 6-digit NAICS code - And are geographically close. So, 0% down deals are simple and easy if you already have a platform and want to do a mini roll-up. Means less of a need for raising equity for follow-on acquisitions. — There’s a bit more to say, but those 4 changes I see are the most impactful to most of our acquirers. These changes take place June 1. The Mainshares team will continue monitoring SBA updates and providing further insights as new information becomes available.

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VCs are great at pattern recognition. But sometimes pattern recognition becomes a shortcut: “That category doesn’t work.” That’s why I’m writing a Substack series of CFO-style post-mortems — not to relive failures, but to show where the next winners can still be built. First up: African e-logistics. What broke ? If you’re building (or investing) in a sector VCs are cautious about, this lens helps you answer one question: Is the category dead — or were the mechanics just misunderstood? Full breakdown in the comments.

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The One Big Beautiful Bill Act (OBBBA) may be the most founder-friendly tax shift we've seen in years — especially for software, AI, and tech businesses considering an exit. Three provisions stand out: 1. Section 1202 Expansion Up to $15M in capital gains exclusions, with scaled benefits starting after year 3 — great news for growth-stage C-Corps. 2. 100% Bonus Depreciation Returns Buyers can fully deduct tangible assets upfront. That reshapes how asset deals are modeled vs. stock deals. 3. Interest Deductibility Grows Shifting from EBIT to EBITDA-based deductions gives more flexibility in leveraged buyouts — and more room to negotiate. These aren’t just tax details — they materially impact deal structure, valuation models, and timing. For founders, this is a rare moment to revisit your exit strategy. DM me for a confidential conversation about your company’s options. #TechM&A #SoftwareFounders #SaaSExits

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Most PE firms say they underwrite businesses. In reality, many are underwriting Founders and hoping it transfers. That gap is where multiples get destroyed. I’ve seen firms pass on strong financials and I’ve seen firms overpay for them. The difference wasn’t revenue. It wasn’t margin. It was transferability. If EBITDA requires the founder’s personality to hold, it is not durable EBITDA. It is rented performance. This is where investors get uncomfortable. A business can show: - $5M+ EBITDA - Clean growth - Strong customer retention - Attractive industry tailwinds And still deserve a discounted multiple. Why? Because operational control does not transfer. Here’s what kills Enterprise Value quietly: - Founder gravity - When key customers, hiring decisions, pricing authority, and escalations orbit one person - Spreadsheet finance - When dashboards exist but reconciliation requires tribal knowledge - Heroic revenue - When pipeline depends on speaking gigs, relationships, or personal credibility that doesn’t scale - Undefined operating cadence - When meetings happen, but decisions don’t - When EBITDA drops the moment the founder stops being the shock absorber This is not a talent problem. It’s an operating system problem. Investors are not buying historical performance. They are underwriting what happens the first 24 months after control shifts. Two businesses. Same EBITDA. Same growth. One sells at 4x. The other at 9x+. The difference is whether the machine works without the hero. In VC, this shows up as “founder-led growth.” In PE, it shows up as “execution risk.” Same issue. Different capital stack. The firms that win in this cycle are not paying for narrative strength. They are paying for: + Transferable customer relationships + Decision rights that don’t escalate by default + Financial systems that produce signal without drama + A leadership bench that can run without supervision Because once capital gets selective, charisma stops compounding. Systems do. Investor lens question: If the Founder stepped back tomorrow, what happens to EBITDA in the next two quarters? Does it hold? Or does it reveal what was actually being underwritten?

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Proposed QSBS update being considered for private company investors: “Taxpayers would be able to invest at later stages in startups and still get QSBS, cash out earlier and still get a partial benefit, and skip taxes entirely on up to 50% more of their windfalls.” https://lnkd.in/ge9_Vu-B

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Perhaps more than any other internal discipline, the Finance & Accounting function often requires the most improvement among newly acquired SMBs. The company's new reality - which now includes a lender, an audit, and a Board of Directors, among other things - almost always requires new people, tools, and processes. This is often overwhelming for new CEOs, who are likely already consumed with countless other internal priorities. To help us make sense of what to prioritize, who to hire, and what to measure, I'm joined this week by Nicholas Andrews, CPA, Founder of the Aspen Consulting Group, a company that performs finance, accounting, and operations consulting for a wide range of SMBs. In our conversation today, we cover: - How much cash to keep on your balance sheet at any given time - Low friction ways to shore up liquidity, should it ever become a problem - Less obvious strains on cash flow that are often missed by CEOs - How much financial information CEOs should be sharing with their employees - What to do when your carefully crafted budget goes out the window in February or March - Whether you need a Controller or a CFO - How to make your first senior Finance & Accounting hire - ...and much more Thanks to Oberle Risk Strategies and Boulay for making this episode possible. https://lnkd.in/gPV9Jefw

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Should a founder be an insider or an outsider? This is an ongoing debate for investors in vertical AI. Insiders bring deep domain expertise and strong industry relationships, while outsiders bring a fresh perspective and fewer legacy assumptions. Jin from Fieldguide is a former auditor who built an AI platform for the CPA industry. While he’s clearly an insider, he believes the answer isn’t binary. What matters more is first-principles systems thinking: an obsession with the problem and a willingness to rethink workflows from the ground up. Jin is a great example of this. Rather than just doing audit work, he spent a lot of his time at the Big Four improving internal systems and processes. The most compelling founders pair genuine passion for the vertical and the problem with strong AI knowledge and systems thinking skills. That combination is the trifecta for a vertical AI founder. Shoutout to Troy from Andreessen Horowitz for the topic. More in the clip below.

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I’ve seen founders celebrate 8-figure exits. And end up taking home much less money than expected. Here are 7 M&A terms that explain why: 1️⃣ Working Capital Adjustment Buyers expect a business to be delivered with a “normal” level of working capital. Sounds boring?  It’s not. It’s one of the first places where value quietly disappears. If you don’t model this early, you’re leaving room for ambiguity. Treat it as part of the purchase price and not an afterthought. 2️⃣ Earnout A portion of the price is paid out over time if the business hits certain targets. Looks good on the slide deck. But if targets shift post-acquisition (which they can), good luck hitting them. If you’re relying on an earnout, make sure: - Targets are locked - Definitions are tight - Incentives are aligned Make sure you push for more cash upfront and lock in clear targets before you sign the LOI. 3️⃣ Due Diligence Most founders think it’s just a finance check. I repeat, don't take this lightly. It’s the deep dive buyers do before closing the deal. In reality, the buyer is expected to tear through everything: - legal docs - org charts - employee contracts - and commercial risks. One missing contract or messy cap table? That “almost closed” deal can disappear fast. 4️⃣ Indemnity Cap This limits how much liability the seller carries after the close. But here’s where it gets tricky: Some things, like “fundamental reps” or fraud, are often excluded from that cap. If you don’t spell it out clearly, you might think you're protected… and still end up writing a check a year later. Don’t assume the cap covers everything. Read it closely. Negotiate it tighter. 5️⃣ Escrow Buyers typically hold back a portion of the payment, just in case something goes wrong post-close. It’s standard.  But the details matter. If 20% is tied up for 18–24 months, it changes the math. That headline number is not what hit your bank account. Focus on what’s real.  Cash in hand beats vanity numbers. 6️⃣ Liquidation Preference Investors get paid first. That’s the rule. But what seems fair in one round can compound fast over multiple raises. I’ve seen great exits on paper like $100M+, where common shareholders walked away with almost nothing. Fanduel is one of the most popular examples. Preferences stack.  Read the fine print and model every scenario. 7️⃣ LOI (Letter of Intent) It's a non-binding document that outlines the core terms of the deal. But don't let the word "non-binding" fool you. Founders treat it like a formality. It’s not. 90% of your negotiating leverage disappears after signing. Push hard on purchase price structure, working capital terms, exclusivity, and timelines before the LOI, not after. Hope you found this helpful! Let me know if there's something that still confuses you. -------- Over the past 15 years, my team at FE International has closed 1,500+ deals, with a combined value of over $50 billion. Get a free valuation (Link in comments)

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Public software is down 40% in 12 months. The selloff has been indiscriminate. Companies hitting their revenue targets are getting hammered alongside the ones that deserve it. The market isn't distinguishing between well-positioned and poorly-positioned software companies.   That will change. When it does, the companies left standing will be the ones with moats that matter in a world where agents do more of the work.   The Emergence partnership spent yesterday debating a question I think every founder and investor should be asking (and, judging by my LinkedIn feed, it seems they are...):   Which software moats actually survive in an AI era?   Here's the spectrum we landed on (from least to most defensible):   1. Workflow   Pre-Claude, getting humans to do their jobs inside your software was a powerful moat. But if agents are doing the work, who cares about the human workflow? Cursor vs Claude Code is the canary in the coal mine: one owns the workflow, the other just executes—and developers are increasingly choosing execution over process.   2. Integrations   MCPs are rapidly commoditizing the glue between systems. Being the connector used to be a moat. Soon, it'll be a utility.   3. Data repository   Static repositories are table stakes. Owning customer data matters less than understanding what to do with it.   4. System of action   Now we're getting somewhere. If your software touches money, customers, or real-world outcomes (think Gusto or Shopify), ripping it out is genuinely painful.   5. Full context   The most important new moat in AI. Understanding how a full task gets done across systems, knowing what a user needs across many different sources. This is what agents need to be useful, and the companies that own it become indispensable infrastructure. But it's young and unproven. If context becomes portable (the way integrations are being commoditized now), this moat could erode too.   6. Brand   The moat that survives every platform shift. Trust compounds over time and can't be replicated by a new entrant with better tech. When everything else gets commoditized, the vendor you trust still wins.   7. Network effects   The most underappreciated moat in AI, and potentially the most enduring. But not all network effects are equal. Workflow-based ones (more humans in the tool) are vulnerable. Data and trust-based ones (every user makes the product smarter) actually accelerate with agents. LinkedIn, Doximity, and Slack all still have this. Relatively few AI native companies have prioritized it...yet.   --   The bottom line: Seat-based pricing and workflow stickiness were the backbone of the last era. Both are eroding. The next era rewards companies tied to outcomes, context, and trust.   If you're a founder, stress-test your moats against this spectrum. If your primary defense is "our users do their jobs in our software," you have work to do.   Because the world is moving towards selling outcomes, not software.

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If you think ARR alone determines your valuation, you’re playing yesterday’s game. According to recent data from Aventis Advisors SaaS Valuation Multiples 2015‑2025, median revenue multiples have collapsed from the frothy peaks of 2021 and now sit significantly lower. Investors aren’t doling out “growth at all costs” premiums anymore. They’re demanding 𝘱𝘳𝘰𝘰𝘧 𝘰𝘧 𝘥𝘶𝘳𝘢𝘣𝘭𝘦 𝘦𝘤𝘰𝘯𝘰𝘮𝘪𝘤𝘴 and 𝘱𝘳𝘰𝘧𝘪𝘵𝘢𝘣𝘪𝘭𝘪𝘵𝘺. Here’s the blunt truth that most founders still haven’t internalised: Profitability and cash flow, not just top-line growth, are now 𝘤𝘰𝘳𝘦 𝘷𝘢𝘭𝘶𝘢𝘵𝘪𝘰𝘯 𝘥𝘳𝘪𝘷𝘦𝘳𝘴. When interest rates climbed and liquidity tightened, companies burning cash were punished hardest. Those with genuine operating leverage, expanding margins and cash generation saw multiples hold up far better. So if you’re building a SaaS business, you must zoom out and connect the dots between pricing, packaging and valuation. Step away from the vanity metrics! Why? Because pricing doesn’t just move ARR. It shapes: • Net Revenue Retention (expansion revenue = valuation alpha) • Gross margins (cash flow is real, not hypothetical) • Rule of 40 performance (growth + profitability = valuation lift) • CAC payback and CLTV (capital efficiency = lower risk) Only one of those is a momentary brag metric — 𝗽𝗿𝗶𝗰𝗶𝗻𝗴 𝗶𝗻𝗳𝗹𝘂𝗲𝗻𝗰𝗲𝘀 𝗮𝗹𝗹 𝗼𝗳 𝘁𝗵𝗲𝗺. Founders obsessed with engineered growth but blind to the quality of that growth are getting paid at lower multiples today. The data show profitable SaaS businesses are being awarded 𝗵𝗶𝗴𝗵𝗲𝗿 𝗘𝗩/𝗘𝗕𝗜𝗧𝗗𝗔 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲𝘀 and better revenue multiples than their unprofitable peers. It’s why a 10-point improvement in Rule of 40, or a discipline in pricing that prevents churn and drives expansion, isn’t “nice to have.” It’s the difference between a 3–4x multiple and an 8–10x multiple on ARR. And valuation isn’t something you “get” at exit. It’s something you 𝗯𝘂𝗶𝗹𝗱 every quarter through disciplined commercial decisions: • Stop selling dollar usage — sell 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴 𝘰𝘶𝘵𝘤𝘰𝘮𝘦𝘴. • Stop chopping prices — design 𝘱𝘢𝘤𝘬𝘢𝘨𝘦𝘴 𝘵𝘩𝘢𝘵 𝘦𝘹𝘵𝘳𝘢𝘤𝘵 𝘷𝘢𝘭𝘶𝘦. • Stop chasing logos — engineer 𝘦𝘹𝘱𝘢𝘯𝘴𝘪𝘰𝘯 𝘱𝘢𝘵𝘩𝘴. • Stop ignoring margins — demand 𝘤𝘢𝘴𝘩 𝘨𝘦𝘯𝘦𝘳𝘢𝘵𝘪𝘰𝘯. Investors understand this. They price for the future, not the headlines. If you want to see how improving NRR, Rule of 40, or EBIT margin — one lever at a time — compounds into multiples on multiples, I can show the sensitivity maths that founders need in their dashboards. Because in the current SaaS market, 𝘷𝘢𝘭𝘶𝘦 𝘪𝘴𝘯’𝘵 𝘨𝘪𝘷𝘦𝘯. 𝘐𝘵’𝘴 𝘦𝘯𝘨𝘪𝘯𝘦𝘦𝘳𝘦𝘥. If you would like a copy of our 𝗱𝘆𝗻𝗮𝗺𝗶𝗰 𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻 𝘁𝗼𝗼𝗹 featuring 5 valuation methods, complete SaaS P&L, unit economics, 'goal seek' based on desired valuation, and a sensitivity analysis - send a connection request and comment "SaaS Valuation" below. 👇

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The real reason for the 𝐝𝐢𝐯𝐢𝐝𝐞 𝐛𝐞𝐭𝐰𝐞𝐞𝐧 𝐅𝐢𝐧𝐚𝐧𝐜𝐞 𝐚𝐧𝐝 𝐑𝐞𝐯𝐎𝐩𝐬: GaaP vs. Non-GaaP revenue. Don't be scared RevOps community. Read on if you want to help your CRO. Let’s break it down 👇 𝐆𝐚𝐚𝐏 𝐑𝐞𝐯𝐞𝐧𝐮𝐞: • Defined by Generally Accepted Accounting Principles • Handled by: Finance • Tools: NetSuite, QuickBooks, Sage Intacct 𝐍𝐨𝐧-𝐆𝐚𝐚𝐏 𝐑𝐞𝐯𝐞𝐧𝐮𝐞: • ARR. MRR. The recurring stuff. • Handled by: - Finance for recognition (ASC 606, IFRS 15) - RevOps for drivers (churn, expansion, etc.) •Tools: Maxio, Equals Here’s the kicker: It’s actually easier for Finance to understand ARR… …than for RevOps to bridge ARR into GaaP revenue. That’s the divide. So how do we bring them together? → RevOps must guide FP&A through the ARR drivers of churn, expansion, contraction, and new ARR—from a customer journey perspective. → FP&A must help RevOps understand why ARR may be higher or lower then reported revenue so RevOps understands how they drive GaaP revenue growth. This is how you help your CRO and CFO get aligned. This is how you build trust between Finance and RevOps. Get on the same page Speak the same language Level up. #CRO #RevOps #CFO #FPandA #SaaS

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This week's accounting AI round-up is live. Three things: 1. AuditBoard rebranded to Optro. 2. Is it true that the new AI-native horizontal ERPs are selling for $10K ACVs (down from $75K). If true, this is creative self-destruction playing out in real time. It's why I backed GoodDay Software instead—vertical focus, deep inventory management for Shopify merchants. 3. We have a new unicorn in accounting AI (details in the newsletter). Full details, plus fundraises, partnerships from Intuit + Anthropic, Thomson Reuters hitting 1M CoCounsel users, and new product launches across the space: https://lnkd.in/gsF3g4rN

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Every day we speak to founders who've structured their companies exactly the way good advisors told them to — multiple entities, holding companies, intercompany arrangements — and then get declined because a lender called it "messy." Last week: a $5M SaaS business, 65% margins, zero debt, three entities, clean books, growing fast. Two lenders declined them — not because the business was risky, but because their systems couldn't untangle the structure. That's not a credit problem. That's a data problem the lender couldn't be arsed solving. Lenders confuse complexity with risk. And it comes down to tooling. Deterministic systems — rules, scorecards, thresholds — are great at consistency. Same logic, every time, fully explainable. Regulators love them. But they're brittle. Novel business structures break them. So the model says "decline" when the right answer was "dig deeper." Non-deterministic systems — ML, pattern recognition, probabilistic models — find signals humans miss. Margin compression months before a payment issue. Revenue seasonality buried in years of company-specific data. But "the model says no" isn't a credit decision. It's an abdication. You need both. At Tractor Ventures we've assessed hundreds of millions in loan applications to the borrowers most lenders call "too hard." Here's how: A deterministic scorecard analyses dozens of metrics across years of real-time company-specific financial data. Consistent. Auditable. Explainable. AI layers on top: normalising multi-entity structures, reclassifying messy financial data, flagging covenant risks before they become payment problems, generating the specific questions our credit team should be asking. Then a human makes the call — armed with better data and sharper questions than they'd ever prepare manually. Automate the quant. Amplify the qual. Keep humans where judgment matters. The result? A loss rate that would make most banks envious. And customers who come back over and over. Complexity isn't risk. It's a data problem we've solved.

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What happens when rapid growth isn’t backed by disciplined financial management? I once worked with an industrial distribution company that expanded globally—but overinvested in inventory. When the market shifted, they couldn’t maintain their ratios or cover their leverage, and ultimately went bankrupt. If you're in a volatile industry like energy, it's critical to stay conservative and keep a close eye on the fundamentals. Growth is powerful—but only when it’s sustainable. #Abunden #BusinessGrowth #CFO #FinancialManagement #SustainableGrowth

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I’ve spoken to over 2 dozen MDs at PE firms I can confidently say that the arb of figuring out how to implement Vertical AI at portfolio companies is very real right now It will fundamentally change underwriting for those who can do it predictably and unlock generational returns. Most are aware they need to act. Very few have.

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