Nicheloom

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AI agents that validate your product idea by talking to real users

Details

External ID
46098366
Source
HN
Company
—
Product
AI agents that validate your product idea by talking to real users
Website domain
holyshift.ai
Launched
Nov. 30, 2025
Cohort
—
Upvotes
7
Upvotes percentile
0.37882096069869
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

I built a tool to solve a problem I kept running into: I was making product decisions based on guessing instead of real users. I kept building stuff nobody wanted as I was usually wrong.So, I built HolyShift: AI agents that validate product ideas by talking to real people on Reddit, HN, X, and LinkedIn … then generate a detailed GTM and “Should we build this?” report.No synthetic data (ChatGPT). No predictions. Only real conversations from real people.What it does • Posts platform-native questions (where allowed) • Collects real reactions, objections, pricing signals • Clusters feedback into themes (pain, demand, adoption, pricing …) • Runs a monitoring agent for sentiment analysis • Produces a short validation report (PRD + GTM)All actions are rate limited and reviewed by a human for compliance.How it works (technicals) • Multi-agent pipeline (intake → landscape → engagement → monitoring → synthesis → report) • Platform specific prompting (HN vs Reddit vs LinkedIn …) • Real-time sentiment + clustering via embeddingsLink https://www.holyshift.ai (Early beta)What I’m looking for • What should stay human vs automated? Should we automate this 100%? • How do you do your product validation? Do you talk to your potential users (and who?) before you build?Happy to answer anything.

Enrichment

Theme
task-specific ai agents and assistants
Vertical
Horizontal
Function
Agent / copilot
Audience
B2B
AI stance
AI-native
Project type
Commercial product
Normalized one-liner
ai agents for user research and validation
Manually corrected
False

Could you build this?

Partial While LLM orchestration to generate replies is simple, building automated multi-platform conversational agents that message users without getting immediately banned requires sophisticated anti-bot evasion and platform API integrations.

What it would actually take: The architecture needs distributed headless browser infrastructure (Playwright/Puppeteer with stealth plugins), residential proxy pools, and account warmup pipelines to bypass bot detection on Reddit, X, and LinkedIn. It requires semantic scraping to match contextual discussions, LLM evaluation pipelines to craft non-spammy conversational responses, and webhook listeners to process inbound replies asynchronously while handling rate limits and account bans.

Discussion

12 comments analyzed.

Competitors mentioned: Direct human-conducted user research and interviews, Passive thread analysis tools (analyzing existing complaints)

Concerns raised: Quality control: distinguishing useful feedback from garbage, Observer effect: people give polished answers when asked directly vs. raw unfiltered feedback, Platform bans/ToS violations from posting questions to communities, Scalability with human review step (expensive to scale as consulting model), LLM hallucination: agents agreeing to features or making promises not on roadmap

Feature requests: Move yellow chat CTA button on mobile (usability issue with form submission), Passive observation of existing threads instead of direct outreach, Strict JSON snapshot and response templates to prevent agent drift

Competitors

Other products that read as similar to this one — 220 launches clear the similarity bar, closest 8 shown.

Attention rank: #116 of 221 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 32 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a agent / copilot tool for Agriculture yet.