Tibo Louis-Lucas: From Repeated Failures and an Earnout Exit to a Self-Reported $1M+ MRR Portfolio
French founder who spent years on non-revenue startups, shipped 11 products in months until Tweet Hunter worked, sold it and Taplio under an earnout he later called a financial mistake, then rebuilt a multi-product AI portfolio without taking outside capital.
- MRR
- $1M+ (self-reported portfolio)
- ARR
- ~$12M+ (implied, self-reported)
- Users
- Not publicly broken out
- Founded
- 2021 (Tweet Hunter); current portfolio post-2023/24
- Team
- Small / co-makers and contractors
- Stack
- AI wrappers, Next.js/React-style, SEO tooling, Stripe
Early years: two startups that taught the wrong lessons slowly
Thibault Louis-Lucas, known online as Tibo (@tibo_maker), is a French builder who has been unusually public about both the wins and the parts that did not work. His first companies followed a more traditional path. In interviews he has described an early parenting app (neither founder was a parent) and a later coding-education product that raised money, hired, and still failed to generate meaningful revenue. One of those efforts left him with substantial personal debt after the company collapsed.
The pattern he later called out was simple and expensive: he spent roughly two years on each of those projects before accepting they were not going to work. Free users, funding, and activity were not the same as people paying. That distinction became central to everything that followed.
Eleven products in a few months
In 2021, partnering again with co-founder Tom Jacquesson, Tibo changed the operating system. Instead of protecting one idea for years, they decided to ship roughly one product per week until something produced revenue. They built about ten products that did little commercially. The eleventh was Tweet Hunter.
Tweet Hunter stood out in a crowded scheduling space by focusing on content ideas and inspiration rather than just calendar management. Early revenue appeared quickly—Tibo has said it reached meaningful MRR within days of launch. They later built Taplio as the LinkedIn counterpart. Growth leaned on organic channels, Product Hunt, creator partnerships (including equity or profit shares with influencers), and public building. By 2022 the combined products had crossed roughly $1M ARR. Tibo was named Product Hunt Maker of the Year.
The sale and why he calls the math a mistake
In 2022 they sold Tweet Hunter and Taplio to Lempire. The headline structure was up to about $10 million: roughly $2 million upfront plus an earnout. At signing the products were generating on the order of $1.5 million in combined ARR. To unlock most of the remaining money, Tibo and Tom stayed and grew the business. Combined ARR later reached about $8 million, unlocking roughly $6 million of the earnout and bringing the total collected to about $8 million.
Tibo has been explicit that this felt like a poor financial outcome relative to the work. By the end they had effectively received around 1× the final ARR for a company they had grown substantially after selling it. After splits with the co-founder, partner shares, and French taxes, his personal take-home was meaningfully less than the headline. He has also described the psychological pressure of the earnout—the sense that missing targets meant losing money he had already mentally counted—and the platform risk that remained while he no longer owned the upside. Changes to Twitter’s API under new ownership created real operational stress during that period.
In his own words across posts and interviews, he has said he would not structure a deal that way again. The experience clarified that he preferred to keep the compounding assets rather than sell the future growth at a price negotiated on earlier numbers.
Rebuilding without the earnout clock
After leaving the earnout period he returned to building, this time with a clearer preference for ownership. Current products include Revid.ai (AI short-video creation, pivoted from an earlier acquisition called Typeframes after watching how users actually used the tool), Outrank (SEO / organic traffic tooling that evolved from a more limited content generator), SuperX, PostSyncer, Feather (acquired), and others such as Bazzly. He runs them under the TMAKER umbrella and documents the work on X and via a newsletter at tmaker.io.
Self-reported figures have been substantial. In 2025 he posted that Outrank had crossed $120k–$130k MRR and was adding roughly $1k new MRR per day at points. In early 2026 he referenced Revid doing around $600k MRR and being profitable without investors. He has publicly stated that the portfolio crossed $1,000,000 in monthly recurring revenue. These are his numbers, shared in posts and interviews; they are not independently audited public financials. Exact splits, churn, and current per-product breakdowns are not fully disclosed. Third-party leaderboard sites sometimes aggregate or estimate them; where those differ from his direct statements, his own posts are the primary source used here.
Distribution remains central. He continues to build in public, run the newsletter (tens of thousands of subscribers by his account), use SEO, and iterate based on what users actually do. Pricing has generally been in ranges that filter for serious users rather than maximizing free sign-ups. He has described charging early as the cleanest validation signal.
What the work looks like now
The portfolio approach means attention and trust built on one product can help the next, but it also means managing multiple surfaces, co-makers or contractors, support, and platform or model risks. AI has made certain kinds of shipping faster; it has not removed the need for distribution or the cost of bad-fit customers. Recent posts show continued iteration—for example, refining who Bazzly should serve after a waitlist revealed niches that damaged shared infrastructure.
Margins and exact unit economics are not public. What is clear from his statements is a preference for products that can run profitably without external capital, and a willingness to kill or pivot experiments that do not show paid demand.
Lessons that hold up under scrutiny
Speed of learning beats speed of building if the learning is tied to payment. Two years on a non-revenue idea is expensive. A week or two of real usage plus a charge can be cheaper even if most experiments die.
Earnouts are conditional compensation for future work, not guaranteed purchase price. If you believe you can grow the business to the target, calculate what that growth is worth while you still own the equity. Headline multiples that mix today’s company with tomorrow’s results obscure the trade.
Platform risk is real when the product is tightly coupled to someone else’s API or algorithm. Owning the customer relationship and the core workflow reduces (but does not eliminate) that exposure.
Finally, public building compounds when it is specific. Revenue updates, pivots explained, and honest post-mortems create an audience that is already somewhat pre-sold on the next experiment. The audience is not magic; it is a distribution channel that still requires a product people will pay for.
All revenue figures in this piece are drawn from Tibo’s own public statements or contemporary interviews in which he discusses the numbers. They should be treated as self-reported. Independent verification of current portfolio MRR is not available from public audited sources.
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