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Bruce – AI signal radar for Reddit/HN that learns what matters to you

Bruce – AI signal radar for Reddit/HN that learns what matters to you

by rklosowski·Feb 24, 2026·3 points·2 comments
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AI Analysis

●●●BangerSolve My ProblemShip ItSlick

F5Bot but it learns your signal vs keyword matching noise.

Strengths
  • •Reinforcement learning feedback loop adjusts scoring weekly
  • •Monitors 5+ sources unified via RSSHub, covering newsletters to YouTube
  • •REST API + MCP server enables workflow integration out-of-box
Weaknesses
  • •Freemium SaaS competes against free alternatives like F5Bot and email filters
  • •Learning curve requires acting on signals consistently for value
Category
SaaS
Target Audience

Founders, product managers, and marketing teams launching SaaS

Similar To

F5Bot · Feedly AI · Punchmetrics

Post Description

I built Bruce because I was drowning in noise while trying to launch my own SaaS.

I had F5Bot set up for keywords, but it was sending me 50+ alerts a day — mostly irrelevant. I'd spend 20 minutes triaging to find 2 threads worth responding to. The problem wasn't lack of monitoring, it was lack of signal.

Bruce is different: instead of matching keywords, it scores every item 0-100 against your product context, ICP, and competitor list. It understands why something is relevant, not just that a keyword appeared.

The part I'm most excited about: it learns. Every time you act on a signal or dismiss one, Bruce adjusts. By week 2, it's surfacing very different (better) things than week 1.

What it monitors: Reddit, Hacker News, RSS feeds, ProductHunt, and anything with an RSS endpoint via RSSHub (YouTube channels, newsletters, etc.)

Stack: Next.js 15, PostgreSQL, Drizzle, Better Auth, my self-built AI runtime, RSSHub.

Live at https://smartbruce.com

Happy to answer questions about the scoring model or architecture.

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