A Personal Data Project
Your Saved Posts Are a Diary You Never Wrote
11,323 Instagram saves. Three years of private attention. An AI that reads every post, watches every video, and publishes an editorial magazine about the person who saved them.
11,323
Posts Analyzed
516
Gaza Events
760
Recipes Extracted
225
Person Profiles
21
Sideshifts
114
Training Exercises
5
Deep Dives
What Happens When AI Reads Your Archive
Saves weigh 3x more than likes in Instagram's own algorithm — the strongest signal of genuine interest. But the feature has had three updates in nine years. No search. No export. No tools. Your saves sit behind three taps, in a folder the platform never wants you to think about.
This project takes them back. Four AI models, each doing what it's best at: Gemini watches full videos. Whisper transcribes audio. Sonnet synthesizes meaning across five text sources. Opus extracts structured data from what it sees. Not a prompt — a pipeline of agents that extract, review, and reframe like a strategist, analyst, and editor passing work between them.
Recipes extracted from the food collection
A boolean flag from vision analysis found 97 recipes. AI agents reading all five text sources per post found 612. AI agents that watched the cooking videos found 760. A 684% improvement — not from better data, but from better seeing. A silent video of a chef slicing fennel became a complete recipe with 7 ingredients and 8 steps. The data was always there. You just needed an AI that could watch.
“Likes and comments are social behavior. Saves are private intent. This dataset is the closest thing to a real signal of curiosity, concern, taste, and identity.
Five Deep Dives
Each collection becomes its own editorial project — not a filtered dashboard, but a purpose-built narrative with its own voice, analysis, and design.
6,861 posts
Gaza
28 months of a war, week by week. 516 timeline events, 225 person profiles, 5,700 factual claims. A personal record of following a crisis through the accounts you trust.
1,415 posts
Counterculture
Anti-establishment politics and protest culture. 27% satirical content, a post-inauguration anger spike, and veganism as the fastest-growing theme.
851 posts
Food
8 years of recipes turned into a cookbook you’d actually cook from. 760 structured recipes extracted by AI agents that watched the cooking videos.
202 posts
AI
The fastest-growing collection — 6.5x monthly growth. Builder tutorials and surveillance critiques arriving simultaneously.
114 posts
Hundetrening
Positive reinforcement dog training from 95 accounts. Scandinavian mushroom hunting, consent-first philosophy, and 92% video — a learning journey made computational.
What the AI Sees
The Emotional Packaging Gap
53% of posts score positively on language sentiment — yet 57% are dominated by disgust, anger, or fear. Creators wrap difficult material in accessible, even optimistic, language.
Cross-Collection Sideshifts
Tucker Carlson is coded as fear in one collection and anger in another. 21 figures change emotional register depending on context. The archive contains the same people playing different roles.
The Rhythm of Attention
Saves peak at 4 PM in focused 8-minute bursts of 1.6 posts — punctuated by occasional 23-post deep dives that last hours. Private behavior, made legible.
The Filter Bubble Paradox
High source diversity (Shannon entropy 0.87) but extreme topical concentration — 86% converges on political content. Many voices, one concern.
Not What Software Does
Everyone's talking about AI replacing SaaS. That's thinking too small.
A traditional pipeline is deterministic — same input, same output, same pre-built charts. It only answers questions someone already thought to ask. The interesting work has always been human: What should we ask this data? What's actually valuable here? How do we turn raw numbers into something someone would read?
This skill orchestrates agents that loop in and out of the data — extracting, reviewing, reframing — the way a strategist, analyst, and editor would pass work between them. Each step feeds the next. Each output gets reviewed before it moves on. The result isn't a dashboard. It's a publication.
Not what software does. What an agency with expensive software and technical data scientists does — made reproducible. One person built five editorial deep dives, 760 structured recipes, 225 person profiles, and a psychological portrait. The question isn't what we built. It's what you could build with the same methodology applied to your own data.
SaaS automates processes. A skill automates expertise. Are skills the new software, or the new agency?
Explore
Overview
Collection metrics and trend summaries
Semantic Search
Find posts by meaning, not keywords
Post Galaxy
11,000 posts in semantic space
Topics
14 topic clusters and their evolution
Sentiment
Emotional geography of the archive
Network
690 accounts, 26 communities
Archive Profile
Behavioral fingerprint of attention
Browse
Explore every collection