Agentic AI

Marielle the Nutrition Knower spent years answering the same client questions about food, supplements, and workout nutrition. After leaving her practice to raise her children, she built a Custom GPT called The Nutrition Desk, uploading her own guides and programming it to ask users about their goals before advising. She sells monthly membership access through her newsletter for ten euros and drives traffic through TikTok videos debunking nutrition myths.

Cleo the Toddler Sleep Fixer watched exhausted parents struggle with bedtime routines throughout her years as an early childhood educator. She built a Pickaxe agent called The Bedtime Helper that generates a personalized sleep plan based on a short questionnaire. She charges nine dollars per month and found her first wave of users through a parenting Facebook group, growing largely through word of mouth since.

Amara the West Africa Trip Planner had worked in travel and watched budget tourists consistently struggle to find reliable information about Senegal, Ghana, and Ivory Coast. She built a Pickaxe agent called Plan My WA Trip that generates day-by-day itineraries based on dates, budget, and interests. She charges eight dollars per month and drives traffic through an Instagram account featuring her own travel photography.

Tobias the Small Business Namer had spent years in branding and noticed that the earliest and most paralyzing moment for new entrepreneurs was often just deciding what to call their business. He built a Pickaxe agent that guides users through a structured naming session, asking about their offer, audience, tone, and values before generating name options with short explanations of why each one works. He charges a one-time fee of fifteen euros per session rather than a subscription and drives traffic through LinkedIn posts where he shares naming breakdowns of well-known brands.

Siana the Language Pattern Spotter had always believed that language learners fail not because they lack exposure but because nobody tracks their specific recurring mistakes. She built a standalone voice-based agent that gives users twenty minutes of daily conversational practice, then sends an end-of-day summary highlighting their mistakes and explaining the underlying language logic behind each one, compared to how their native language works. Because the agent builds a personal mistake profile over time, it becomes more useful the longer a user stays. She charges a monthly subscription through her website and drives traffic through TikTok clips showing real end-of-day summaries with learner details blurred.