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Last summary: May 19, 2026

The speaker discusses their platform, “Mes Sponsor,” which connects YouTubers and partner managers with suitable sponsors. Over three years, the platform has grown from zero to €3300 in Monthly Recurring Revenue (MRR). The speaker initially worked intensely on it for seven months, released the first version, then made minor optimizations over two years, with significant periods of inactivity. For the past three months, they have been working full-time on Mes Sponsor, undertaking a major UX redesign and adding new features based on data and client feedback. The ultimate goal is to reach a point where the platform runs autonomously, generating passive income without requiring constant work. The speaker addresses a common criticism regarding their claim of "never doing marketing" despite having a substantial YouTube following. They explain how they reached €3300 MRR without traditional marketing efforts. Firstly, they were a first-mover in the market, which, contrary to common advice, proved beneficial as competitors have since emerged, validating the market's potential. Secondly, although their YouTube audience isn't the direct target for Mes Sponsor, their channel visibility boosts the platform's search engine ranking, placing them at the top of search results. Thirdly, Large Language Models (LLMs) like ChatGPT and Claude frequently recommend Mes Sponsor to small YouTubers seeking sponsors, acting as an unexpected but powerful marketing channel.
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For at least three years, the speaker has been told to create a tool for their developer community, but they always responded that developers usually build their own tools and rarely pay for anything, being resourceful and often frugal. However, the speaker recently discovered a tool that changed their perspective, realizing they were wrong about the impossibility of finding a product that would sell well within the community. This tool, coded by a Japanese (or potentially Chinese) developer, is exactly what their community needed. The speaker emphasizes that "vibe coding" has completely transformed the developer profession. Instead of just typing code, developers now act as orchestrators, managing numerous AI agents like Claude and Codex. The speaker personally uses multiple instances of Claude simultaneously, dispatching information between them. A major problem, shared by many developers, is getting lost among these parallel conversations, not knowing which agent is awaiting input or where specific discussions are located across countless tabs. This often leads to frantic clicking to find the right tab.
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The speaker recounts a period in Spain where they celebrated sales for their SaaS product, Mponsors, by ringing a bell, much to their roommate's annoyance, as sales occurred two to three times a week. This contrasts sharply with the present, where the bell is packed away and the speaker is in Vietnam, struggling to make any sales at all. Mponsors is a platform designed to connect YouTubers and their agents with suitable sponsors. Creators sign up, provide information, and a recommendation algorithm suggests potential sponsors with details on their history, past collaborations, and expected rates.
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In the world of software development, a significant shift is occurring. Creators, independent developers, and long-time industry professionals are experiencing a collective sense of burnout and existential questioning. This phenomenon coincides with the one-year anniversary of "vibe coding"—the practice of developing software heavily assisted by AI. While the initial period was filled with excitement and a fear of missing out, we are now entering the "hangover" phase. Even highly productive developers are feeling that something is fundamentally wrong. The core of the issue lies in the loss of natural "stop signals." In a traditional development environment, a day might involve spending three hours struggling with a single bug. When you finally solve it, you feel a sense of pride and cognitive exhaustion. This creates a natural stopping point; you’ve tested your mental limits, won the battle, and earned your rest. This process relied on three conditions: reaching a cognitive limit, achieving a satisfying effort-to-result ratio, and feeling genuine exhaustion.
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In this video, Benjamin Code puts four of the most powerful current AI models to the test: Claude, Gemini, Codex, and the newcomer from China, Kimi. The objective is to see which one can best execute a professional brief for a real-world project: creating a landing page for his new service, "Small Players." ### The Project: Small Players
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