Mainstream job boards (LinkedIn, Indeed) serve stale, duplicated, and heavily promoted listings, while trying to track direct company career pages manually or via custom scrapers is fragmented and brittle.
Major job boards (LinkedIn, Indeed) serve stale, duplicated, promoted, and irrelevant listings, forcing job seekers to manually monitor disparate company career pages directly.
I spent 18 months building a job board for software engineers because LinkedIn was driving me insane
I spent 18 months building a job board for software engineers because LinkedIn was driving me insane
if you want to make it really niche there is no api for it.
commenti also have a pretty much random job board for a very niche, lets say, passion. do you scrape these 120 pages with your own scraper or some api? because from a first experience maker if you want to make it really niche there is no api for it. and do you use pyhton to scrape these pages or what do you use? :)
Builders and high-intent tech job seekers who need programmatic, deduplicated access to direct company career pages instead of stale aggregator feeds.
Repeated explicit frustration regarding mainstream aggregator data quality combined with the heavy engineering pain of maintaining custom crawlers.
Zero aggregated or promoted noise; 100% direct-from-source tracking with structural monitoring resilience that abstracts away fragile CSS selectors.
A robust micro-scraping engine and API that continuously monitors direct company career pages (Greenhouse, Lever, Workday, custom ATS), providing a unified, deduplicated, ultra-fresh feed of real job listings.
Users are spending hours a week maintaining custom scraping infrastructure and fixing broken code. Job board creators and job hunters will pay to save substantial maintenance time and get immediate access to fresh leads before they hit aggregators.
“Real-time, deduplicated job feeds straight from company career sites.”
A robust micro-scraping engine and API that continuously monitors direct company career pages (Greenhouse, Lever, Workday, custom ATS), providing a unified, deduplicated, ultra-fresh feed of real job listings.
Launch on Hacker News, r/webdev, and r/cscareerquestions; target indie hackers building specialized directories.
Target company websites utilizing heavy Cloudflare or Datadome protections can block automated requests, degrading data freshness.
Frequent changes to custom career pages can cause scrapers to fail constantly, eating up engineering margins.
Individual software engineers will churn as soon as they find a job, putting pressure on B2B / job board creator acquisition.
Run an Investment Memo to get a structured Go / No-Go verdict, competitor landscape, unit economics, and a 90-day validation roadmap for this opportunity.
Generate an investment memoThis idea scores in the upper-middle range of opportunities surfaced by MonetScope, with a validation sub-score of 8/10 against 3 independently sourced evidence signals. A "promising" rating usually indicates a real pain has been detected and discussed in the open, but the pipeline did not find enough signal to flag it as urgent or high-frequency. These opportunities can still produce excellent businesses — they often correspond to "boring" problems that established players have ignored — but the founder should expect a longer customer-development cycle to confirm willingness to pay.
It sits at the intersection of "api", "automation", "data-management", which makes it relevant to a specific subset of founders rather than a generic horizontal opportunity. SaaS opportunities at this stage tend to win on the strength of their initial wedge — a single workflow that the target user runs every week, where the existing solution is either spreadsheets, a clunky incumbent feature, or a manual process they hate. The build cost is moderate; the distribution cost is everything. The MonetScope pipeline surfaces this category alongside other saas signals, which is why it appears here rather than in a generic "trending ideas" feed.
Scores are derived from real forum discussions across Reddit, Hacker News and X, weighted by evidence volume and signal quality. How scoring works
MonetScope does not generate ideas from a language model's imagination. Every opportunity on this site is anchored to specific source posts and comments from real public discussions — typically on Reddit, Hacker News, or X — where actual users describe the pain in their own words. The AI's role is structuring, scoring, and grouping those signals into a navigable opportunity, not inventing the problem.
MonetScope's spider pipeline runs continuously and surfaces opportunities as new evidence accumulates. The "Updated" date in the header reflects the most recent re-scoring of this specific opportunity. Most saas opportunities visible in the public catalog draw from discussions in the last 30-60 days; older signals are de-prioritized because user pain shifts faster than most founders assume.
Overall score is a composite across six dimensions — pain, urgency, willingness to pay, market size, defensibility, and execution ease — designed to give a single number for triage. Validation score is narrower: it asks "how cleanly does the same signal repeat across independent sources?" An opportunity can score high on overall but lower on validation when one or two large discussions dominate the evidence; conversely, validation can be high on a smaller-overall idea where the signal is consistent but the addressable market is modest.
