HackerNews Signals

Overview

HackerNews Signals capture product launches (Show HN), trending tech discussions, and company mentions from Hacker News via the Algolia API. Each signal is enriched with company identification, B2B relevance scoring, founder extraction, and outreach hooks.

We process HackerNews daily, filtering for Show HN launches, high-engagement stories mentioning companies, and hiring threads. Each signal includes an engagement score based on points and comments, plus LLM-generated outreach hooks.

Signal Subtype

Signal	Subtype Enum	Description
Show HN Launch	`showHnLaunch`	Product launches posted as Show HN
Company Mention	`companyMention`	Trending stories mentioning a company
Hiring Thread	`hiringThread`	Company appearing in Who's Hiring threads

Schema

{
  "signal_id": "hn-47580350",
  "signal_type": "hackernews",
  "signal_subtype": "showHnLaunch",
  "association": "company",
  "detected_at": "2026-03-30T22:10:22Z",
  "company": {
    "name": "Acme AI",
    "domain": "acme.ai",
    "industries": ["Artificial Intelligence", "SaaS"]
  },
  "data": {
    "hn_id": "47580350",
    "hn_title": "Show HN: Acme AI – Automate your GTM workflows with AI agents",
    "hn_url": "https://acme.ai",
    "hn_author": "acmefounder",
    "hn_points": 232,
    "hn_comments": 98,
    "hn_link": "https://news.ycombinator.com/item?id=47580350",
    "story_type": "show_hn",
    "company_name": "Acme AI",
    "company_description": "AI-powered GTM workflow automation platform.",
    "product_name": "Acme AI",
    "product_description": "Automate prospecting, research, and outreach with AI agents.",
    "founder_names": ["Jane Smith"],
    "key_features": ["AI agents", "GTM automation", "CRM integration"],
    "target_market": "B2B sales and marketing teams",
    "competitive_angle": "AI-native approach vs. traditional workflow tools.",
    "relevance": 0.9,
    "is_b2b": true,
    "outreach_hooks": [
      "Congrats on the Show HN launch — 232 points is impressive traction.",
      "Saw the HN discussion around your AI agents — would love to connect."
    ],
    "tags": ["ai-product", "b2b", "gtm-automation"],
    "engagement_score": 4.36,
    "source": "hackernews-algolia",
    "confidence": "high",
    "sentiment": "positive"
  }
}

Field Reference

Core Fields

Field	Type	Description
`signal_id`	string	Unique identifier (prefixed `hn-`)
`signal_type`	string	Always `"hackernews"`
`signal_subtype`	string	See subtypes table above
`detected_at`	string (ISO 8601)	When the HN post was created
`association`	string	Always `"company"`

Company Object

Field	Type	Description
`company.name`	string	Resolved company name
`company.domain`	string	Primary website domain
`company.industries`	array[string]	Industry classifications

Data Object

Field	Type	Description
`hn_id`	string	HackerNews story ID
`hn_title`	string	Original post title
`hn_url`	string	URL shared in the post
`hn_author`	string	HN username of the poster
`hn_points`	integer	Upvote count
`hn_comments`	integer	Comment count
`hn_link`	string	Direct link to HN discussion
`story_type`	string	`show_hn`, `story`, or `hiring`
`company_name`	string	Extracted company name
`company_description`	string	LLM-generated company summary
`product_name`	string	Product name (for Show HN)
`product_description`	string	LLM-generated product summary
`founder_names`	array[string]	Extracted founder/maker names
`key_features`	array[string]	Key product features extracted
`target_market`	string	Target market description
`competitive_angle`	string	Competitive positioning
`relevance`	float (0-1)	B2B relevance score
`is_b2b`	boolean	Whether the product is B2B
`outreach_hooks`	array[string]	Ready-to-use outreach messages
`tags`	array[string]	Classification tags
`engagement_score`	float	Composite engagement metric
`source`	string	Always `"hackernews-algolia"`
`confidence`	string	`high`, `medium`, or `low`
`sentiment`	string	`positive`, `neutral`, or `negative`

Delivery

Detail	Value
GCS Bucket	`gs://autobound-hackernews/`
Refresh	Daily
Format	JSONL + Parquet