47jobs – Marketplace for "Vibecoders"

Hacker News

Hi HN, I'm building 47jobs, a marketplace connecting clients with "vibecoders" - developers who specialize in AI-assisted development. What's vibecoding? Instead of writing code manually, vibecoders use natural language prompts with AI tools (GPT, Claude, v0) to rapidly prototype and build features. They describe what they want in plain English, and AI generates working code that they iterate on until it's production-ready. The productivity gains are incredible - what used to take weeks now takes hours. Why this matters: - Traditional hiring focuses on syntax knowledge - The real skill now is prompt engineering and AI collaboration - Clients need rapid prototyping and validation - There's no platform specifically for this new type of developer I'm pre-selling early access passes ($47) to validate demand and build a community before launch. The response has been encouraging so far. Would love HN's feedback on the concept and landing page: https://47jobs.xyz Is this the future of development, or am I missing something?

Visit product View on Hacker NewsJul 21, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, new, coding · Missing: mac, agents, macos

84%84% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

20%20% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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