Chike Agbai

AI isn’t killing venture, SaaS-era valuation math is, the “AI margin tax,” why $100M ARR can be a mediocre outcome at 25–60% gross margins, and the one metric (contribution margin per action) founders and investors should obsess over. https://lnkd.in/gpiR6APY

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The most salient narrative in tech today is the end of software. Public software companies have been pummeled, down 20%+ in the last 3 months. But I think the bear case rests on weak logic. There are 3 main categories of concern driving this narrative: 1. Vibe coding means businesses build their own software 2. AI automates away jobs, and seat licenses plummet 3. AI-native companies take share from legacy incumbents The first one doesn't hold up. The second is too important to dismiss casually, but lacks evidence thus far. The third strikes me as most threatening, but it, too, rests on a flawed logical foundation.   On rolling your own software, customers who choose to build almost always regret it. An internal IT team can build a CRM, but they can't maintain and improve it like a dedicated software company. Anthropic spending 8-figures on Workday for HR software shows that incumbent providers have more to offer than software skeptics realize.   Sure, there's a risk of AI automating away seats (and therefore seat licenses). But this creates opportunity for software incumbents to deliver AI-infused software that allows customers to do just that. Software vendors can easily shift to usage-based or other value-based pricing models. Relatedly, there's a larger fear that AI will trigger massive unemployment among knowledge workers. This deserves to be taken seriously. However, unemployment is currently quite low by historical standards, and current AI is beyond what most considered AGI a few years ago. I think the worriers here are moving the goalposts. The third concern--AI-native companies decimating software incumbents--is the most formidable. 20-25 years ago, Google hoovered up the attention economy by building the dominant consumer Internet product. Could Anthropic or OpenAI do something like this in b2b? It's not my base case, but it's the scenario that goes the farthest with me.   That said, I think there are 2 misunderstandings embedded here.   The first is that only AI startups can use AI tooling to accelerate product velocity. They aren't. The engineers at Shopify and Workday have the same access to Cursor, Claude Code, or open-source AI models.   The second, bigger misunderstanding is that these markets are zero-sum. By definition, technology expands the existing pie. So I disagree with the idea that AI growth will come at the cost of existing software companies. AI will massively expand software spend.   Which brings me to what's hardest to reconcile. If you believe AI-native startups will create major value, you're implicitly underwriting a world with fragmentation and switching costs among knowledge work tools. You can't hold that public software companies are all in the blast radius of Anthropic AND back the Harveys or Open Evidences of the world.   It doesn't add up, as the bull case of one is implicitly the bull case of the other. And while the market is voting like these are opposites, I expect the weighing machine to disagree.

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Layer is tackling one of the most overlooked pain points for SMBs: accounting. They’re gaining real traction doing so. Emergence is leading their seed round to bring embedded, AI-powered accounting to the SMB software stack. Kevin Spain highlights what makes this team and product so compelling. 

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Here's a problem we see all the time in early studios: they copy-paste a VC fund's operating cadence and wonder why nothing feels right. Weekly deal flow reviews. Portfolio monitoring calls. Valuation-focused LP reports. All borrowed wholesale from a fund playbook. But a VC fund's primary activity is deal selection -- source, evaluate, check, board, wait. A studio's primary activity is venture creation -- generate, validate, recruit, build, launch. Those are fundamentally different jobs. When you run a studio like a fund, things break in specific ways: Your meetings are wrong. You're reviewing deal flow instead of venture build progress -- milestones, blockers, resource allocation. The work is building, not sourcing. Your team is wrong. Studios need builders at every level -- operators, designers, engineers. Not just investment professionals. You can't build companies with a team designed to pick them. 📉 Your metrics are wrong. Entry valuations and markups don't tell you anything useful. Cost-to-build-a-venture, time-to-market, and venture survival at 18 months -- those are the numbers that actually measure whether the studio is working. Your LP reporting is wrong. Report operational progress -- what's building, what's launching, what's been killed and why. Not just portfolio movements. Here's the lesson -- the studios that struggle most are the ones that adopted VC templates without modifying them for fundamentally different work. The portfolio companies don't exist until the studio creates them. Not a fund that happens to build things. A builder that happens to have a fund. The operating rhythm should reflect which one is primary. 🎯

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Zoom plans to acquire Bonsai. A deal that positions Zoom to lead AI workflows for solopreneurs. Here’s why this move matters 👇 For context: Bonsai is a client management platform that helps solo operators manage contracts, payments, and projects in one place. But Bonsai’s real value lies in its AI foundation. The Seattle-based startup developed “machine teaching,” a way to train AI models without coding expertise. For Zoom, the acquisition is about moving beyond meetings to own the broader workflow layer. Here’s the current landscape: • Microsoft dominates enterprise productivity • Google leads cloud-native collaboration • Zoom owns meetings But no one owns the solopreneur workflow. That’s the gap Zoom wants to fill. With Bonsai, Zoom can: - Run client operations end to end - Capture the fast-growing solopreneur market - Integrate AI-driven automation directly into workflows - Expand into CCaaS with recurring, high-margin revenue Bonsai gains access to Zoom’s user base and its growing AI stack including Zoom Docs and AI Companion. Together, they can scale Bonsai’s platform far faster than it could alone. Zoom’s acquisition of Bonsai is about owning the AI-powered workflows that will drive the future of solo business. ----- Our team at FE International is more bullish than ever on the rise of AI-first businesses. If you're a founder curious about your company’s true value, get a free valuation. (Link in comments) 👇

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Every hire, product feature, and GTM experiment is a capital allocation decision, most teams just don’t call it that. I’m kicking off a 3-part series on capital allocation for founders, operators, and finance leaders with a simple question: ➡️ Will the next $1 you deploy become worth more than $1? Series overview Part 1: defines the core concept + the math Part 2: where capital goes + how to measure whether it’s working Part 3: AIMS framework for communicating allocation decisions to management teams and your board Part 1 (attached here) lays the practical foundation: 🔹 The $1 invested test and ROIIC vs. hurdle rates (scoreboard vs. decision lens) 🔹 A lightweight “investment brief” to evaluate bets (GROW / BUILD / BUY) 🔹 The small metric toolkit that translates finance into operating decisions (NPV / payback / ROIIC / incremental margin) 🔹 Early-stage proxies when DCF inputs are unknowable (burn multiple + revenue quality) 🔹 Operator “vital signs” to spot drift early (profit engine, leverage, cash conversion, optics) Series Roadmap ✔️ This series (Parts 1–3): breadth-first. shared, lightweight framework to define value creation, choose decision-grade metrics, and communicate tradeoffs clearly ✔️ Next series: depth-first. momentum drivers + operational decisions that need near real-time measurement to spot drift early and course-correct fast Read Part 1 here and Part 2 and 3 on substack. Next Series will be out next week. 💰 What’s one bet you’re funding right now, and how will you prove it’s working?

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