ScholarFlow: Structured AI Academic Writing Workflow

Strong Opportunity. The demand for "universal instructions" on Bilibili indicates a large segment of users who have the tool (LLMs) but lack the technical skill (prompt engineering) to achieve their desired outcome. A software wrapper that productizes these instructions into a guided workflow solves this "know-how gap."

Users are overwhelmed by the "blank box" of AI. They know AI can write papers, but they don't know the sequence of commands needed to produce something high-quality, properly structured, and academically sound. They are currently hunting for "magic prompts" in comment sections, which is a high-friction, unreliable manual behavior.

• The 'Crunch-Time' Student: Undergraduate or Graduate students facing a 48-hour deadline for a major paper.
• The International Scholar: Researchers writing in their second or third language who need help with formal academic structures.
• The Thesis-Stuck Senior: Students who have the data/research but are paralyzed by the organization of a long-form thesis.

Multiple users on Bilibili specifically requested "universal instructions" (求万能指令) in response to a tutorial video. This indicates they don't want to learn how to prompt—they want a button or a command that "just works." This is the classic signal for a SaaS to replace a manual or complex process.

ScholarFlow Basic: A web-based multi-step wizard.

1. Input Stage: Field of study, paper type (Literature Review, Empirical Study, etc.), and raw notes/topic.
2. Logic Layer: A backend prompt chain that first generates an outline, asks the user for feedback, and then drafts one section at a time.
3. Output Stage: A formatted Markdown or Word document with placeholders for citations.

Academic success is directly tied to future earnings and status. Students already pay for Grammarly, Chegg, and Turnitin. A tool that actually builds the draft rather than just checking it is a high-value proposition. The monthly subscription fits the 4-year cycle of a degree.

Low to Medium. This is a classic LLM wrapper. The value lies in the domain-specific prompt engineering and the UI/UX of the workflow, not in building the underlying AI models. A solo developer can build this using Next.js and the OpenAI API in under 3 weeks.

With roughly 20 million students in the US and 40 million in China, reaching 100-1,000 paying users at $20/month is highly realistic. The market is fragmented enough that a niche, "academic-first" brand can compete against general AI tools.

The primary strategy should be Social Proof/Tutorials. Since the evidence was found on Bilibili, creating "study hack" videos that demonstrate the tool's ease of use compared to manual prompting is the most direct path to conversion.