The definitive guide to maximizing your reach on X (Twitter), based on reverse-engineering the open-source algorithm.
X (formerly Twitter) open-sourced their recommendation algorithm, and xAI released an updated version in January 2026. This playbook distills thousands of lines of code into actionable rules that anyone can follow to maximize their reach.
No fluff. No guesswork. Just algorithm-backed strategies.
| If you want to... | Read this |
|---|---|
| Get the essentials | Golden Rules |
| Understand scoring | Scoring System |
| Optimize before posting | Pre-Post Checklist |
| Avoid penalties | Avoiding Penalties |
| Deep dive | Action Weights Reference |
Your Post Score = Σ (weight × P(action))
Where actions include:
├── POSITIVE: reply (+2×), like, retweet, quote, share, follow
├── NEGATIVE: block (-10×), mute, report (-20×), "not interested"
└── NEUTRAL: click, dwell time, profile view
Key insight: The algorithm predicts 19 different user actions and weights them. Your goal is to maximize positive action probability while avoiding negative signals.
x-algorithm-playbook/
├── rules/ # Core strategies (start here)
│ ├── 00-golden-rules.md ← The 10 most important rules
│ ├── 01-scoring-system.md ← How your posts are scored
│ ├── 02-content-optimization.md
│ ├── 03-engagement-tactics.md
│ ├── 04-timing-frequency.md
│ ├── 05-avoiding-penalties.md
│ └── 06-growth-strategies.md
│
├── checklists/ # Actionable checklists
│ ├── pre-post-checklist.md
│ ├── weekly-audit-checklist.md
│ └── profile-optimization.md
│
├── case-studies/ # Real examples
│ ├── viral-thread-anatomy.md
│ └── common-mistakes.md
│
└── reference/ # Technical deep-dives
├── action-weights.md
├── filter-system.md
└── algorithm-faq.md
- Replies are king — Posts that generate replies score ~2× higher
- Avoid negative actions — One block = -10× the value of a like
- Space your posts — Author diversity penalty kicks in after 1st post
- In-network first — Your followers see you before non-followers
- Video > Image > Text — But only if video exceeds minimum duration
- Dwell time matters — Longer content = higher engagement signal
- Don't trigger filters — 12 filters can completely hide your content
- Engage authentically — Algorithm tracks your interaction patterns
- Niche down — Consistent topics improve retrieval matching
- Quality > Quantity — One great post beats five mediocre ones
The algorithm uses a Grok-based transformer model (Phoenix) to predict engagement:
┌─────────────────────────────────────────────────────────────────┐
│ YOUR POST ENTERS THE SYSTEM │
└─────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ CANDIDATE SOURCING │
│ ├── Thunder: Posts from accounts user follows (in-network) │
│ └── Phoenix: ML-discovered posts (out-of-network) │
└─────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ FILTERING (12 filters can remove your post) │
│ ├── Age filter (too old) │
│ ├── Muted keywords │
│ ├── Blocked/muted authors │
│ └── Spam/safety filters │
└─────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ SCORING (Phoenix ML Model) │
│ ├── Predicts P(like), P(reply), P(retweet)... for 19 actions │
│ ├── Weighted sum = final score │
│ └── Author diversity penalty applied │
└─────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ RANKING: Top-scored posts shown first │
└─────────────────────────────────────────────────────────────────┘
| Action | Weight | Impact |
|---|---|---|
| Reply | ~2× | Highest positive signal |
| Quote Tweet | ~1.5× | Strong engagement |
| Retweet | ~1× | Good reach |
| Like | ~1× | Baseline positive |
| Follow Author | ~1× | High intent signal |
| Share (DM/Link) | ~0.5× | Moderate |
| Click | ~0.3× | Weak positive |
| Dwell Time | Variable | Longer = better |
| "Not Interested" | ~-1× | Negative signal |
| Mute | ~-5× | Strong negative |
| Block | ~-10× | Very strong negative |
| Report | ~-20× | Devastating |
Found an insight? Want to add a case study? PRs welcome!
See CONTRIBUTING.md for guidelines.
- X Algorithm Source Code (xAI) — Primary source for this playbook
- X Algorithm (Twitter Archive)
- X Algorithm ML Components
- Original analysis from codebase review
MIT License - Use freely, attribution appreciated.
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