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Idea nuevaConsumer social

Algorithm Mirror

hace 3 semanas · Evaluada el 20 oct 2026 · ID HBV-261020-05

Resumen

BriefingHipótesis

New idea. Existence check: Searches (20 Oct 2026) found no dedicated generator for "how the algorithm sees me" from feed screenshots, and no product that pairs it with friend answers. Closest analogs: ChatGPT caricature prompts (manual trend), Spotify Bedroom (internet-bedroom.com, room from Spotify data), EraBoard and…

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Decor8 (aesthetic quizzes), oomfmap.com (AI personality grid from an X handle; X mentions 76% below peak), CutNoodle X Recap ("X personality"), Wimo brain-map template, NGL and Tellonym (anonymous friend questions). Partial overlap with HBV-261019-04 Rage Index (feed analysis), which scores rage bait rather than identity. X: 2,949 posts/7d (Up 6% Wed→Mon (full UTC days: Wed 14 234 → Mon 19 249); peak Fri 16 762; Mon 19 is 67% below peak — ≥50% below peak: POP 5.3 window-closed signal; window 2026-10-13 10:30 UTC → 2026-10-20 10:00 UTC (Tue 13 Oct and Tue 20 Oct are partial UTC days; full days Wed 14 → Mon 19)). Revenue hypothesis: ~$2K–$5K/month at month 6 (HYPOTHESIS: 200k cards/month × 0.5–1% buyers × ~$3).

DescripciónHipótesisModelo

Upload a few screenshots of your feeds (TikTok For You, Instagram Explore, Pinterest, YouTube) and get an AI portrait of "who the algorithm thinks you are"; then invite friends to answer six quick questions and get a side-by-side "Algorithm vs Friends" card to share. Who: Gen Z and young millennials (16–30) who post identity memes and "how X sees me" trends on TikTok, Instagram and X; first in English, then Portuguese and Spanish.…

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Pain: People are curious and uneasy about what recommendation algorithms "think" of them and enjoy comparing that to how friends see them, but today they have to improvise with ChatGPT prompts and cannot compare with friends. Monetization: Free card; one-off paid HD poster and "deep read" (about $2–$4, hypothesis); optional monthly re-scan; No approved price. Build: 1–2 agent-weeks (screenshot upload with on-device redaction, vision model labeling, portrait generator, friend-invite form, card renderer, checkout); stack: Next.js on Vercel; vision LLM for labeling; image model for the portrait; Postgres; Stripe; server-side cards. GTM: Share cards on TikTok, Instagram and X; friend-invite loop (each user needs friends to answer); faceless trend accounts; SEO pages ("how TikTok sees me").

Cliente objetivo

Gen Z and young millennials (16–30) who post identity memes and "how X sees me" trends on TikTok, Instagram and X; first in English, then Portuguese and Spanish.

Problema

People are curious and uneasy about what recommendation algorithms "think" of them and enjoy comparing that to how friends see them, but today they have to improvise with ChatGPT prompts and cannot compare with friends.

Por qué esta puntuación

Por qué obtuvo una puntuación menor: Fad decay: the core X trend fell 67% from its peak within three days, so the friend-invite loop must carry growth after the trend moment.

Ventaja defensivaHipótesis

Friend-answer graph and card library: The moat is the invite graph and the best-known card format, not the model calls. Repeat scans and friend comparisons create a reason to come back; competitors start without friend data. Status: Hypothesis.

Señales de demanda

Publicaciones en X (7 días)

2949

Tendencia de la señal

Up 6% Wed→Mon (full UTC days: Wed 14 234 → Mon 19 249); peak Fri 16 762; Mon 19 is 67% below peak — ≥50% below peak: POP 5.3 window-closed signal

Demanda en la webVerificado

The "how the algorithm sees me" wave peaked on Thu 15–Fri 16 Oct (747 and 762 posts) and fell to 249 on Mon 19; the "how others see me" prompt family is steady at ~100 posts/day. Korean saju brain maps (A1 today) show the same appetite for identity images. Other X counts (same window, Verified X API): 765 posts: ("how …

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my friends see me" OR "how others see me" OR "how people see me" OR "describe me in one word" OR "first impression of me" OR "what do you think of me") -is:retweet

Mercado y competidores

TAM

Not sized this run — Scope: Paid personality and identity images. Method: No market report fetched. (Basis: n/a)

SAMHipótesis

~$24K–$60K / yr (hypothesis) — Scope: English-language cards. Method: 200k cards/month × 0.5–1% × ~$3 × 12 (HBV assumption). (Basis: HBV assumption)

SOMHipótesis

~$24K–$60K ARR (hypothesis) — Scope: Month-6 run-rate if 200k cards/month. Method: as SAM. (Basis: Low (hypothesis))

Competidores

Manual ChatGPT/Grok image prompts; Spotify Bedroom; EraBoard; Decor8; oomfmap.com; CutNoodle X Recap; NGL, Tellonym, Sendit; platform-native recaps (Spotify Wrapped, Pinterest Predicts).

Modelo de negocio

MonetizaciónHipótesis

Free card; one-off paid HD poster and "deep read" (about $2–$4, hypothesis); optional monthly re-scan; No approved price.

Hipótesis de ingresos (mensual)Hipótesis

~$2K–$5K/month at month 6 (HYPOTHESIS: 200k cards/month × 0.5–1% buyers × ~$3).

Jobs to be done

When an identity trend is all over my feed, I want to get my own version in seconds and see if my friends agree, so I can post something that feels like me and talk about it with friends.

HXC

Maya, 19, Manchester (illustrative) · Student who posts "how X sees me" trends and moodboards on TikTok and Pinterest. Buying signal: Tried the ChatGPT version of the trend; would send the friend link to her group chat to see whether friends agree with the algorithm, and buy the HD poster for her wall.

Construcción y go-to-market

Stack tecnológico

Next.js on Vercel; vision LLM for labeling; image model for the portrait; Postgres; Stripe; server-side cards

Canales de GTM

Share cards on TikTok, Instagram and X; friend-invite loop (each user needs friends to answer); faceless trend accounts; SEO pages ("how TikTok sees me")

Riesgos

Riesgo principal

Fad decay: the core X trend fell 67% from its peak within three days, so the friend-invite loop must carry growth after the trend moment.

Todos los riesgos

Value: Attention — Trend falling 67% from peak | Usability: Attention — Privacy of screenshots | Feasibility: Supported — Standard APIs | Business Viability: High — Low willingness to pay

Siguiente paso de validación

Ship in 7 days; target 50,000 cards and a 20% friend-invite completion rate in 14 days; kill if invite completion is under 10%.

Fuentes

X API counts (window above)
existence web searches (20 Oct 2026)
internet-bedroom.com
oomfmap.com (X news, Oct 2026)
cut-noodle.com
wimouniv.com

ideaidentityshare-cardai-portraitfriend-invite-loopb2cgen-zglobalbrazillatam

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La puntuación, las fuentes, los riesgos y el siguiente paso, por correo.

ProductBots.ai

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# Briefing: Algorithm Mirror

Source: Startup Ideas HQ (HB Ventures), found 2026-10-20. ProductBots Opportunity Score: 57/100, evidence confidence 46%.
Evidence labels (Verified, Self-reported, Hypothesis) are kept as written by the researcher.

## Goal for ProductBots.ai
Turn this idea into a validated MVP plan and a first build. Start from the next validation step; do not assume unlabelled numbers are verified.

## What it is
Upload a few screenshots of your feeds (TikTok For You, Instagram Explore, Pinterest, YouTube) and get an AI portrait of "who the algorithm thinks you are"; then invite friends to answer six quick questions and get a side-by-side "Algorithm vs Friends" card to share.

New idea. Existence check: Searches (20 Oct 2026) found no dedicated generator for "how the algorithm sees me" from feed screenshots, and no product that pairs it with friend answers. Closest analogs: ChatGPT caricature prompts (manual trend), Spotify Bedroom (internet-bedroom.com, room from Spotify data), EraBoard and Decor8 (aesthetic quizzes), oomfmap.com (AI personality grid from an X handle; X mentions 76% below peak), CutNoodle X Recap ("X personality"), Wimo brain-map template, NGL and Tellonym (anonymous friend questions). Partial overlap with HBV-261019-04 Rage Index (feed analysis), which scores rage bait rather than identity. X: 2,949 posts/7d (Up 6% Wed→Mon (full UTC days: Wed 14 234 → Mon 19 249); peak Fri 16 762; Mon 19 is 67% below peak — ≥50% below peak: POP 5.3 window-closed signal; window 2026-10-13 10:30 UTC → 2026-10-20 10:00 UTC (Tue 13 Oct and Tue 20 Oct are partial UTC days; full days Wed 14 → Mon 19)). Revenue hypothesis: ~$2K–$5K/month at month 6 (HYPOTHESIS: 200k cards/month × 0.5–1% buyers × ~$3).

## Customer and pain
Target customer: Gen Z and young millennials (16–30) who post identity memes and "how X sees me" trends on TikTok, Instagram and X; first in English, then Portuguese and Spanish.
Pain: People are curious and uneasy about what recommendation algorithms "think" of them and enjoy comparing that to how friends see them, but today they have to improvise with ChatGPT prompts and cannot compare with friends.

## Market and competitors
TAM: Not sized this run — Scope: Paid personality and identity images. Method: No market report fetched. (Basis: n/a)
SAM: ~$24K–$60K / yr (hypothesis) — Scope: English-language cards. Method: 200k cards/month × 0.5–1% × ~$3 × 12 (HBV assumption). (Basis: HBV assumption)
SOM: ~$24K–$60K ARR (hypothesis) — Scope: Month-6 run-rate if 200k cards/month. Method: as SAM. (Basis: Low (hypothesis))
Competitors: Manual ChatGPT/Grok image prompts; Spotify Bedroom; EraBoard; Decor8; oomfmap.com; CutNoodle X Recap; NGL, Tellonym, Sendit; platform-native recaps (Spotify Wrapped, Pinterest Predicts).
Geography: Global English first; then Brazil and Spanish-speaking Latin America

## Business model
Monetization: Free card; one-off paid HD poster and "deep read" (about $2–$4, hypothesis); optional monthly re-scan; No approved price.
Revenue hypothesis (monthly): ~$2K–$5K/month at month 6 (HYPOTHESIS: 200k cards/month × 0.5–1% buyers × ~$3).

## Build and go-to-market
Build effort (agent-weeks): 1–2 agent-weeks (screenshot upload with on-device redaction, vision model labeling, portrait generator, friend-invite form, card renderer, checkout)
Time to first revenue: ~2–4 weeks after launch
Tech stack: Next.js on Vercel; vision LLM for labeling; image model for the portrait; Postgres; Stripe; server-side cards
GTM channels: Share cards on TikTok, Instagram and X; friend-invite loop (each user needs friends to answer); faceless trend accounts; SEO pages ("how TikTok sees me")

## Risks and next step
Main risk: Fad decay: the core X trend fell 67% from its peak within three days, so the friend-invite loop must carry growth after the trend moment.
Next validation action: Ship in 7 days; target 50,000 cards and a 20% friend-invite completion rate in 14 days; kill if invite completion is under 10%.

## Sources
X API counts (window above); existence web searches (20 Oct 2026); https://internet-bedroom.com/; https://oomfmap.com (X news, Oct 2026); https://cut-noodle.com; https://www.wimouniv.com/en/brain-map

Idea nuevaConsumer social· hace 3 semanas
Rage Index
A browser extension and web app that measures how much of your feed is rage bait and AI slop, gives you a shareable Rage Score card, publishes a weekly public Rage Index of the most rage-farming accounts and topics, and sells a calm-feed filter and digest.
57/100
confianza 50%
Por qué obtuvo una puntuación menor: Legal and reputational risk of naming accounts publicly, plus platform DOM changes breaking the extension.
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Investigación, no asesoría de inversión. Los números conservan la etiqueta con la que se publicaron.

Resumen

Briefing○Hipótesis

Descripción○Hipótesis≈Modelo

Cliente objetivo

Problema

Por qué esta puntuación

Ventaja defensiva○Hipótesis

Señales de demanda

Publicaciones en X (7 días)

Tendencia de la señal

Demanda en la web✓Verificado

Mercado y competidores

TAM

SAM○Hipótesis

SOM○Hipótesis

Competidores

Modelo de negocio

Monetización○Hipótesis

Hipótesis de ingresos (mensual)○Hipótesis

Jobs to be done

HXC

Construcción y go-to-market

Stack tecnológico

Canales de GTM

Riesgos

Todos los riesgos

Siguiente paso de validación

Fuentes

Ideas relacionadas

Rage Index

BriefingHipótesis

DescripciónHipótesisModelo

Ventaja defensivaHipótesis

Demanda en la webVerificado

SAMHipótesis

SOMHipótesis

MonetizaciónHipótesis

Hipótesis de ingresos (mensual)Hipótesis