A close friend of mine, a serial entrepreneur, launched a fintech platform with an unbeatable value proposition: it was entirely free for businesses. The strategy was to monetize later through third-party transaction fees, effectively stripping away all upfront friction for enterprises and catalyze rapid adoption. His company raised a few million in seed, and lifted the curtain, and ' crickets. Nothing happened. Businesses didn't sign up. My friend was confused while prospective clients hesitated. This simply didn't sit well with them. Then the founder decided to do something odd. He charged money on top of the original monetization plan. Same product, same value proposition, but now there is a monthly subscription. Almost overnight, new businesses began signing up. The price-quality heuristic is a cornerstone of behavioral economics. When buyers lack complete transparency, they use price as a shortcut for quality. This is why identical items, from fine wines to electronics, are rated higher when they cost more. In B2B, this effect is amplified: A cybersecurity solution priced far below the market doesn't look like a bargain; it looks like a risk....

S3 Ventures led the financing, which included participation from MHS, Active Capital, NextView Ventures and Ritual. It brings Boulder, Colorado-based Schematic's total funding since its 2023 inception to $12 million. Schematic builds entitlements and enforcement infrastructure for SaaS and AI companies. Put more simply, it serves as a digital gatekeeper for software and AI companies. For example, if a company's sales team wants to give a major client a special discount or extra storage, they have to ask an engineer to go in and 'move the walls.' The process can be slow, expensive and tedious. Instead of burying those rules in the code, a company can plug Schematic into its product. Then, if it, for example, wants to launch a new 'AI Tier' or change how many users a client can have, a person in marketing or sales can flip a switch in a simple dashboard. 'When a software company sells you a plan, something inside their product has to enforce what you can do and access based on what you paid for,' said CEO and co-founder Fynn Glover. 'Most companies build that enforcement infra themselves, often badly, and it becomes the thing that slows down every future monetization change. Schematic is the infrastructure that handles it, so engineering doesn't have to.'...

Good morning & happy Tuesday! Today, all eyes are on Klarna and why this digital bank is being priced as a broken subprime lender (deep dive into Klarna's latest financials, breaking down the most important facts & figures, what they mean & why Klarna might be worth your time and money this year + bonus deep dives into Klarna's AI plays inside), and Robinhood, which is about to allow every investor to invest in the most promising startups (why Robinhood Ventures Fund I is a Trojan horse for the private markets, what to expect next + bonus deep dive into Robinhood's latest financials inside). So let's jump straight into the interesting stuff '' Following the money ' Buy Now, Pay Later (BNPL) pioneer Klarna KLAR 0.00%' recently posted its latest Q4 2025 financials, and it presents one of the more compelling risk/reward asymmetries I have encountered lately. Sure, the stock price chart doesn't look inspiring at all, but consider what that valuation buys: a company that generated $3.5 billion in revenue in FY2025 (up 25% YoY), processed $127 billion in GMV across 26 markets, serves 118 million active consumers, and just delivered its first billion-dollar revenue quarter....

Generative AI is transforming retail pricing decisions by providing an accessible and low-cost alternative to traditional pricing algorithms. Unlike traditional approaches, LLM-based pricing relies on natural language prompts, not custom code and historical data. However, LLM-based pricing introduces challenges around consistency, explainability, and potential biases. Implementation examples demonstrate how to prompt LLMs and use their recommendations to optimize product and service pricing. How can recent advances in generative AI tools be applied to transform pricing decisions' By lowering technical and financial barriers, such tools democratize access to sophisticated pricing capabilities, empowering even small businesses to benefit from artificial intelligence without the need for costly, bespoke solutions. There are fundamental differences between GenAI-driven approaches and traditional algorithmic pricing that should inform its use. Effective pricing recommendations depend heavily on how prompts are crafted (for now, at least). In this article, drawn from my forthcoming book on pricing in the age of AI, I'll be discussing the recent, promising trend of using large language models to support pricing decisions....