---
id: "claim-algorithm-training-necessity"
type: "claim"
source_timestamps: ["00:08:41", "00:09:15"]
tags: ["best-practices", "data-scraping"]
related: ["action-train-algorithm", "concept-browser-automation"]
speakers: ["Alessio Bertozzi"]
confidence: "high for this architecture; not a universal prerequisite"
testable: true
---
# Training the Instagram Algorithm is a Prerequisite for Effective AI Scraping

## The Claim

Before running the 'Creator Finder' agent, the user **must manually train the Instagram algorithm** on the account connected to the [[entity-claude-in-chrome|Claude Chrome extension]]. Without this, the AI wastes credits parsing irrelevant content.

See [[quote-algorithm-training]] for the verbatim explanation.

## Mechanism

The AI agent relies on the Instagram **Explore** or **For You** pages to discover new creators via [[concept-browser-automation]]. An untrained algorithm filled with memes, unrelated hobbies, or random content will cause the AI to:

- Waste API credits analyzing useless profiles
- Spend more time on the task overall
- Produce a low-quality Creator List

A highly targeted Explore page ensures the AI only evaluates high-quality, niche-relevant candidates.

## Validation

- Instagram's Explore/Feed recommendations are documented to be driven by user interactions (likes, saves, watch time). The mechanism is well-established in recommender-systems literature.
- **Mechanism plausibility:** ✅ High
- **As a 'hard prerequisite':** Not universal. The agent could discover creators via direct search queries (hashtags, usernames, keywords), third-party databases, or external search engines without relying on Explore at all.

## Verdict

A **plausible best practice for this specific design** (which relies heavily on Explore). Not a universal prerequisite for AI scraping; it is an architectural choice. No empirical benchmarks are cited comparing 'trained vs. untrained Explore feed' on cost or relevance.

## Operational Implication

Do this before first run: [[action-train-algorithm]].