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Ideia novaConsumer social

Algorithm Mirror

há 3 semanas · Avaliada em 20 de out. de 2026 · ID HBV-261020-05

Resumo

BriefingHipótese

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).

DescriçãoHipóteseModelo

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-alvo

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.

Dor

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 que esta nota

Por que a nota foi 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.

Barreira de entradaHipótese

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.

Sinais de demanda

Posts no X (7 dias)

2949

Tendência do sinal

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 na 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 e concorrentes

TAM

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

SAMHipótese

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

SOMHipótese

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

Concorrentes

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 negócio

MonetizaçãoHipótese

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

Hipótese de receita (mensal)Hipótese

~$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.

Construção e go-to-market

Stack tecnológica

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

Canais 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")

Riscos

Principal risco

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 os riscos

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

Próximo passo de validação

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%.

Fontes

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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ProductBots.ai

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O arquivo do briefing está em inglês.

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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

Ideia novaConsumer social· há 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
confiança 50%
Por que a nota foi menor: Legal and reputational risk of naming accounts publicly, plus platform DOM changes breaking the extension.
Abrir o ProductBots.ai →

Pesquisa, não recomendação de investimento. Os números mantêm o rótulo com que foram publicados.

Resumo

Briefing○Hipótese

Descrição○Hipótese≈Modelo

Cliente-alvo

Dor

Por que esta nota

Barreira de entrada○Hipótese

Sinais de demanda

Posts no X (7 dias)

Tendência do sinal

Demanda na web✓Verificado

Mercado e concorrentes

TAM

SAM○Hipótese

SOM○Hipótese

Concorrentes

Modelo de negócio

Monetização○Hipótese

Hipótese de receita (mensal)○Hipótese

Jobs to be done

HXC

Construção e go-to-market

Stack tecnológica

Canais de GTM

Riscos

Todos os riscos

Próximo passo de validação

Fontes

Ideias relacionadas

Rage Index

BriefingHipótese

DescriçãoHipóteseModelo

Barreira de entradaHipótese

Demanda na webVerificado

SAMHipótese

SOMHipótese

MonetizaçãoHipótese

Hipótese de receita (mensal)Hipótese