Developers and hiring managers rely on anecdotes and noisy job board data to understand the market, leading to poor career and hiring decisions driven by narratives like 'AI is killing dev jobs.'
Aggregates and cleans data from FRED, Indeed, LinkedIn, GitHub hiring repos, and recruiter APIs to show deduplicated demand trends by role, seniority, region, and company stage (big tech vs. startup).
Freemium — free macro trends, $29/mo for granular filters, alerts, and salary benchmarking; enterprise tier for recruiters at $199/mo
Real pain but intermittent — developers feel it acutely when job-hunting or negotiating (every 2-3 years), recruiters feel it weekly. The Reddit engagement (2,100 upvotes, 330 comments) confirms people are hungry for this data. However, most devs currently cope with anecdotes, HN threads, and free FRED charts. The pain is real but not hair-on-fire daily.
TAM for talent intelligence is $2-4B and growing fast. The addressable slice for a developer-focused product at $29-199/mo is more modest — maybe 500K active job-seeking devs × $29 = ~$175M/year ceiling for individual tier, plus recruiter/enterprise tier. Not a billion-dollar market for this specific product, but comfortably large enough to build a $5-20M ARR business.
This is the weakest link. Developers notoriously resist paying for career tools — they expect data to be free (FRED is free, Levels.fyi free tier is good enough for many). $29/mo is a real ask when job-hunting happens intermittently. Recruiter/enterprise tier at $199/mo is more natural but requires a sales motion. Monthly churn risk is very high for individual users. You'll likely see high trial-to-cancel rates.
A solo dev can absolutely build an MVP in 4-8 weeks. FRED API is open, Indeed/LinkedIn scraping is well-trodden territory (though ToS-risky), GitHub hiring repos are public. The hard part is deduplication (matching the same job across sources) which is a fuzzy matching problem — good enough with basic NLP, but perfecting it is a long tail. A dashboard with charts and filters is standard web dev work.
This is the strongest signal. Lightcast does aggregation but charges $50K+. TheirStack is close but targets sales teams. LinkedIn is walled-garden enterprise-only. Levels.fyi only does comp. TrueUp is a side project. Nobody has built a real-time, deduplicated, developer-focused demand intelligence dashboard at accessible pricing. The gap is wide and clearly underserved.
Recruiter/enterprise tier is naturally recurring — they need this data constantly. Individual developer tier is problematic: devs subscribe when job-hunting, cancel when employed. You'll see heavy seasonality and churn. Alerts and benchmarking help retention but the core use case is episodic. To make this work as a subscription, you need to make it valuable for employed devs (career monitoring, market awareness) or pivot toward B2B as the primary revenue driver.
- +Clear and wide competitive gap — no one has productized developer job market intelligence at accessible pricing
- +Strong demand signal validation from organic community engagement (2,100+ upvotes discussing exactly this data)
- +High technical feasibility — public data sources, well-understood tech stack, buildable by a solo dev
- +Multiple potential revenue streams (individual devs, recruiters, startup founders, VCs doing due diligence)
- +Timing is excellent — post-layoff era created permanent awareness that job market data matters
- !Willingness-to-pay is unproven for individual devs — high churn risk as users subscribe only during job searches then cancel
- !Data source fragility: Indeed/LinkedIn scraping violates ToS and can break overnight. Over-reliance on scrapeable data without contractual access is a business risk
- !Deduplication quality is the product — if the same job shows up 3x from different sources, trust erodes fast. This is technically solvable but requires ongoing investment
- !Free alternatives (FRED, HN Who's Hiring, Layoffs.fyi) set a high bar for what you need to add beyond freely available data to justify $29/mo
- !LinkedIn or Indeed could ship a similar feature as an add-on to their existing product, leveraging their first-party data advantage
Enterprise labor market analytics platform that aggregates job postings from 40K+ sources, deduplicates, normalizes, and provides workforce intelligence dashboards used by governments, universities, and large enterprises.
Analytics product built on LinkedIn's 900M+ member Economic Graph. Provides talent pool supply data, hiring demand signals, skill trends, and talent flow data
Scrapes job postings across multiple sources to provide competitive and sales intelligence — primarily answering 'who is hiring for what tech stack' as a buying signal for sales teams.
Crowdsourced, verified compensation data for tech roles. Shows total comp breakdowns
Tech job aggregator combined with layoff tracker, funding news, and basic hiring volume signals. Shows 'hot' companies hiring and trending roles.
Dashboard showing deduplicated developer job posting volume trends by role (frontend, backend, ML, DevOps), seniority (junior/mid/senior/staff), region (US metros + remote), and company type (FAANG, mid-market, startup). Data from FRED + GitHub hiring repos + 2-3 scrapeable job boards. Free tier shows macro trends with 30-day lag. Paid tier gets real-time data, granular filters, and weekly email digest with biggest movers. Skip salary benchmarking for MVP — Levels.fyi owns that. Focus on demand signals, which nobody does well.
Free macro dashboard (SEO + content marketing engine) → $29/mo individual tier with real-time data, alerts, and granular filters → $199/mo recruiter tier with API access, saved searches, and team sharing → Enterprise tier ($500-2K/mo) with custom reports and ATS integration. Fastest path to revenue is the recruiter tier — they have budget and daily use cases. Individual dev tier is volume play with high churn.
6-10 weeks to MVP launch, 3-4 months to first paying individual users via content marketing and Reddit/HN distribution. 4-6 months to first recruiter/enterprise customer. The free tier will grow faster than paid — expect 5-10K free users before meaningful paid conversion. First $1K MRR likely at month 4-5.
- “Been watching this FRED data for a while”
- “massive reorganization going on from big tech -> smaller tech”
- “Curious what people here are actually seeing”