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A guided interview turns a founder’s expertise into personal LinkedIn posts on a recurring subscription.
200+ paying users · 80 bootcamp members at €89 before tax
The product sells a repeatable outcome: customers talk through their expertise, then leave with a post that sounds like them.
Fewer bars = easier, cheaper, or faster for an AI-assisted solo builder. Editorial judgments based on the case details.
Alchi is a software product that turns a founder or independent professional's spoken expertise into LinkedIn posts. Pierre Guilbaud was already a LinkedIn ghostwriter for impact-oriented founders and converted that service knowledge into a self-built SaaS. Customers answer guided interviews; the product turns their ideas, experience, and phrasing into drafts intended to sound more personal than generic AI copy. Guilbaud said the product had more than 200 paying users and about €13,000 MRR in September, after passing €10,000 MRR. He described starting near €2,000 MRR in the first month and later rising from roughly €4,000–€5,000 to €13,000. A seven-day trial produced an early €22.80 Stripe payment after a customer used the two available posts and wanted to unlock more. To prepare for a quieter summer, Guilbaud invited a WhatsApp group to join a paid bootcamp; 80 people joined over 15 days at €89 before tax, adding about €4,000 MRR. He reported Claude token costs at roughly 20% of revenue around €5,000 MRR.
For an interview-to-post product, the first customers are easiest to reach through the founder's existing expertise and audience. Guilbaud already ghostwrote for founders, so he could recognize the workflow and invite people who were actively trying to publish on LinkedIn.
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“Et en fait, tu vois, en avril, si on m'avait dit que je ferais 13K de MRR en septembre, je t'aurais dit c'est impossible.”
1:07:47 · hear it in the videoFrench, as spokenData credibility: MRR, paying users, bootcamp enrollment, first payment, and token-cost figures are founder-reported in an interview; no invoices, Stripe dashboard, or independent financial records were described.
The first dollar arrived when a trial user wanted more output than the free allowance included. Guilbaud recalled a Stripe notification for €22.80, corresponding to €19 before tax, after a customer completed two posts during a seven-day trial and wanted to unlock additional posts.
Alchi's growth loop joins expertise, customer outcomes, and visible building. Guilbaud's ghostwriting work gave him practical knowledge of how founders describe their work and what makes a post feel authentic.
A content product can go quiet during seasonal dips or after the founder's public updates stop attracting attention. Guilbaud anticipated lower LinkedIn activity in summer and used that period to prepare a stronger launch for the return to work.
Alchi is a guided content workflow for independent professionals and entrepreneurs who want to publish thoughtful LinkedIn posts without starting from a blank page. A user answers interview-style questions, and the system converts those answers into drafts that preserve personal experience, opinions, and vocabulary. The intended distinction is depth and specificity: AI assists with shaping ideas rather than inventing a generic post from a short prompt. Guilbaud said the generation pipeline takes about 12 or 13 steps and a finished post can take around a minute and a half to produce. He described more than 200 paying users and additional free users. The product includes a draft history and a process for starting another interview. It also sends three personalized post ideas by email each Thursday and can prompt users to book their next writing session after finishing a post. Those reminders make the product a recurring habit rather than a one-off generator. The most important product constraint is preserving the user's voice while keeping the interview short enough to repeat.
Alchi earns subscription revenue. Guilbaud cited about €13,000 MRR in September and said the product had passed €10,000 MRR. A customer initially paid €19 before tax after using two posts during a seven-day trial and wanting to unlock more. Later, 80 people joined a paid bootcamp at €89 before tax over 15 days; he attributed roughly €4,000 of MRR growth to that effort, taking the business from about €5,000 to €13,000. These are founder-reported figures, and the bootcamp cohort may have different retention from ordinary subscribers. The transcript also references more than 200 paying users. It does not provide a complete plan mix or churn rate, so the average recurring revenue per user cannot be derived reliably. For a similar product, offer a clear recurring tier based on interview or post volume, then add higher-touch workshops as a separate source of revenue. Measure renewal after trial, posts completed, published output, and paid conversion by acquisition channel. Keep one-time cohort receipts distinct from recurring subscription revenue in internal reporting.
The founder said Alchi was self-built with AI coding tools and described using Claude. Around €5,000 MRR, he estimated token costs at roughly 20%, while acknowledging that model use and iteration affect the figure. He later described a codebase exceeding 120,000 lines and more than 200 paying users, alongside free users. He said the €200-per-month Claude plan could be exhausted quickly when using a more intensive model, and that he sometimes reserved capacity for bugs. These figures are self-reported and do not establish total gross margin: payment fees, hosting, support, and founder labor are not quantified. The product's multi-step writing pipeline likely makes cost per generated post an important operating metric. A new builder should log token use by workflow, use a cheaper model for routine steps where quality holds, and set usage limits tied to subscription tiers. Keep interviews and drafts structured so model changes do not erase customer history. Complexity can accumulate quickly in an AI-built codebase, so invest in tests, backups, and observability before growth makes a failure affect hundreds of users.
Copy the service insight before copying the full software. Guilbaud had firsthand experience ghostwriting for founders, which helped him understand the questions needed to draw out useful material. A solo builder can interview five consultants, manually turn their answers into posts, and identify which prompts reliably produce publishable drafts. Then automate the repeated steps: interview capture, draft generation, editing, saved posts, and a reminder for the next session. Keep the promise narrow, such as helping consultants publish one credible LinkedIn post each week. Alchi's founder used public progress updates, direct user conversations, and a WhatsApp group to build demand, then added a paid bootcamp for people who wanted more structure. That launch tactic can work when the builder already has an audience and credibility; without those, start with targeted outreach to a specific profession and show a sample post from a real interview. Change the product around the customer's voice and publishing routine. Do not compete solely on the number of AI models or templates; those are easy to copy and do not guarantee that a user will publish.
The main risk is retention. A user can try an AI writing tool, generate several drafts, and then stop when the novelty fades or LinkedIn activity slows. Guilbaud explicitly said he wanted to see whether he could stabilize the €10,000 MRR level and recognized that some bootcamp participants might churn after receiving a discounted bundle of value. The product also depends on quality: generic or inaccurate drafts can damage a user's professional reputation. Multi-step generation and a growing codebase create engineering and model-cost risks; he estimated token costs at around 20% near €5,000 MRR, but total costs were not reported. Competition from general AI writing tools is intense, so Alchi needs a defensible workflow based on interviews, voice capture, and repeat usage. A founder should watch activation through first published post, repeat interview rate, paid renewal, and support requests. Separate cohort revenue from ordinary subscriptions, and avoid assuming that a temporary MRR increase represents stable recurring demand. If users do not publish or return, refine the outcome before expanding features.
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