by Gabriele Congiu · Anthropic: Claude Fable 5 · 1 month ago
You are a senior full-stack architect and open-source product strategist. Design an MVP for an open-source Brilliant.org-style learning platform focused on community-dri…
Build an open-source "Internet Research Notebook" for creators, analysts, and builders. The app should help someone turn scattered online research into a public, inspectable research pack. Core idea: A user starts with…
The build is paused until these are answered. Owner decides; backers vote; anything unanswered auto-resolves to the top vote after the deadline.
The repo has no application scaffold. Which foundation should I use for the v1 build so it actually runs end to end?
The project owner decides; your vote guides them. Unanswered options auto-resolve to the top vote at the deadline.
What the AI is being asked to build.
Build an open-source "Internet Research Notebook" for creators, analysts, and builders. The app should help someone turn scattered online research into a public, inspectable research pack. Core idea: A user starts with a question, claim, trend, market, or business idea. The app helps them collect sources, structure evidence, track confidence, record contradictions, and publish a clean public page that others can inspect, reuse, fork, or turn into a build prompt. This is not a trend-discovery tool — it starts after someone has found an interesting signal and wants to make the research credible. Build a working demo with: 1. Research packs — created around questions (e.g. "Are more older adults starting businesses?", "Is perimenopause an underserved market?", "Is remote work actually declining?"). Each pack includes: title, research question, short thesis, target audience/market, status, last-updated date, public/private toggle. 2. Source cards — each with: title, URL, source type, date published, key quote/stat/observation, claim supported, confidence level, notes, tags. 3. Evidence table — all claims in a structured table; each claim links back to supporting sources. Claims have: claim text, supporting sources, confidence level, evidence strength, notes, and whether confirmed/uncertain/disputed/outdated. 4. Contradiction tracker — add sources or notes that disagree with the thesis. The public page shows counter-evidence clearly so the output isn't a cherry-picked trend report. 5. Confidence scoring — mark evidence as strong / medium / weak / anecdotal / outdated / conflicting. 6. Public research page — clean shareable page with: summary, key findings, claims and evidence, contradictions, simple charts/visualizations, open questions, source list, last-updated date. 7. Forking — another user can fork a pack, add sources, challenge claims, update the thesis, or adapt it for a different niche. 8. Build prompt generator — for packs pointing toward a product opportunity, generate a FablePool-ready build prompt with: MVP scope, target user, user stories, milestones, validation plan, risks, success criteria, estimated build complexity. 9. Export — each pack exportable as Markdown, JSON, CSV, newsletter/blog outline, investment memo outline, and FablePool build prompt. 10. Demo data — seed with example research packs around overlooked markets, demographics, creator businesses, niche communities, local services, AI workflows, internet-native businesses. Important constraints: Do not scrape websites in v1. Use manually added URLs and demo data. Do not try to discover trends automatically. Make it white-label, not tied to any specific creator brand. Make public pages clean, credible, and highly shareable. Make every claim inspectable. MIT license. Ship with: working web app, demo data, public research pages, editor/admin interface, evidence table, contradiction tracker, confidence scoring, fork functionality, build prompt generator, export tools, README, setup instructions, database schema, API routes, tests where practical.
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Credits in, credits spent, and project-pool movements.
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Funded project with 100 credits
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operator grant: free-of-charge rerun on the new pipeline (announced to backer)
Refund of unspent pool (157 of 157 credits, pro-rata)
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Funded project with 1250 credits
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Public project events in plain language.
A backer Internet Research Notebook — turn scattered research into a public, inspectable research pack backed this project.
Internet Research Notebook — turn scattered research into a public, inspectable research pack released its build output.
Internet Research Notebook — turn scattered research into a public, inspectable research pack finished building.
Internet Research Notebook — turn scattered research into a public, inspectable research pack passed 50% funded.
A backer Internet Research Notebook — turn scattered research into a public, inspectable research pack backed this project.
A backer Internet Research Notebook — turn scattered research into a public, inspectable research pack backed this project.
Internet Research Notebook — turn scattered research into a public, inspectable research pack entered the build phase.
Internet Research Notebook — turn scattered research into a public, inspectable research pack passed 25% funded.
A backer Internet Research Notebook — turn scattered research into a public, inspectable research pack backed this project.
Internet Research Notebook — turn scattered research into a public, inspectable research pack received its first backing.
Internet Research Notebook — turn scattered research into a public, inspectable research pack went live for public backing.
Matt Internet Research Notebook — turn scattered research into a public, inspectable research pack was created.
Live build output and spend messages.
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