Blog Post Workflow

Before writing, search the web for what’s currently hot in AI. Prioritize local and private AI developments — this is the site’s core niche and where we build topical authority. General/cloud AI topics are fine as a secondary mix to capture broader traffic.

Primary focus (local/private AI):

On-device and edge AI model releases (Llama, Gemma, Phi, Qwen, Mistral, GGUF quantizations)
Open-source LLM milestones and community developments
Hardware enabling local AI (Apple Neural Engine, NPUs, edge AI chips, new iPhone/Mac capabilities)
Privacy-focused AI news, regulations, and data sovereignty developments
Practical guides for running AI offline on Apple devices
Benchmarks and comparisons of local models on real hardware

Secondary mix (general AI — use to capture broader search traffic):

Major cloud model releases (GPT, Claude, Gemini) — angle toward what this means for local alternatives
AI product launches, funding rounds, or acquisitions
Viral AI demos, controversies, or regulatory news
“How to use AI for X” practical guides

Pick a topic with high current interest. Rehash the news in original words — don’t copy, add perspective and practical context. When covering general AI topics, frame them through a local/privacy lens where natural (e.g. “New GPT-5 is impressive, but here’s what open-source alternatives can do on your device”). Avoid repeating topics already covered in existing _posts/ files.

Step 2: Keyword Research

Before writing, identify:

Primary keyword — the exact phrase you want to rank for (put in title + first 100 words)
3-5 secondary keywords — related terms and long-tail variations
Search intent — is the reader looking to learn, compare, or do something? Match the format to the intent

Target long-tail keywords (3-5 words) over broad ones. They have lower competition and higher conversion. Example: “run llama locally on iPhone” beats “AI models”.

Prefer keywords in the local/private AI space — this is where the site has the most topical authority and can realistically compete. For general AI topics, find a long-tail angle that connects to on-device or privacy themes.

Step 3: Write the Post

Frontmatter (Required)

---
layout: post
title: "Primary Keyword Near the Front — Keep Under 60 Characters"
description: "Compelling summary with keywords. Action-oriented. 140-155 characters max."
keywords: "primary keyword, secondary keyword, long-tail variation, related term"
date: YYYY-MM-DD
---

File Naming

_posts/YYYY-MM-DD-slug-with-keywords.md — put keywords in the slug.

Title Rules

Front-load the primary keyword (first 3-4 words ideally)
Stay under 60 characters so it doesn’t get truncated in search results
Use power formats: “How to…”, “X Best…”, “Why…”, “Guide to…”, “X vs Y”
Make it specific — “5 Best Local LLMs for iPhone in 2026” beats “AI Models You Can Use”

Content Structure

Opening paragraph (first 100 words):

Answer the core question immediately (inverted pyramid style)
Include the primary keyword naturally in the first 1-2 sentences
This paragraph is what AI answer engines and featured snippets extract — make it self-contained and concise

Body:

Use ## (H2) for main sections — phrase these as questions or keyword-rich statements people actually search for
Use ### (H3) for subsections within those
Keep paragraphs to 2-4 sentences max for scannability
Use bullet lists, numbered lists, and bold key phrases — these get extracted by AI Overviews
Include a definition or summary block near the top (featured snippet bait)
Aim for 1,500-2,500 words for comprehensive guides, 800-1,200 for news/opinion pieces
Cover the topic completely — depth beats length. Address follow-up questions a reader would naturally have

Closing:

Summarize key takeaways
Optionally mention Enclave AI if it naturally fits, but don’t force it — the goal is traffic, not promotion

Keyword Placement

Place the primary keyword in these locations:

Title (near the front)
First paragraph (first 100 words)
At least one H2 heading
Meta description
URL slug
Naturally throughout the body (don’t stuff — write for humans, entity coverage matters more than density)

Use secondary keywords and semantic variations throughout the body. Google understands concepts via entity relationships, not keyword counting.

Internal Linking

Link to 2-3 related existing blog posts using descriptive anchor text (not “click here”)
Link to relevant site pages (features, FAQ) where natural
This builds topical authority through content clusters — Google rewards interconnected coverage of a subject

Formatting for AI Answer Engines

Modern search is shifting to AI-generated answers that cite sources. To get cited:

Put a direct, concise answer in the first paragraph
Use clear heading hierarchy (H2 > H3) so AI can parse structure
Include lists and tables for comparative or step-by-step content
Write paragraphs of 40-60 words for optimal extraction
Add FAQ-style H2s phrased as questions (“How does X work?”, “What is X?”)

Topic Diversity

Check existing posts in _posts/ before writing to avoid overlap. Rotate across these angles:

News/trends — what just happened in local or general AI this week
How-to guides — practical tutorials (running models locally, quantization, optimization)
Explainers — breaking down complex AI concepts for a general audience
Comparisons — model X vs model Y, local vs cloud, tool A vs tool B
Listicles — “N best local models/tools/tips for…”
Opinion/analysis — industry predictions, what a development means for privacy and local AI
Use cases — creative or professional applications of AI on-device

Aim for roughly 70% local/private AI content and 30% general AI content to maintain niche authority while capturing broader traffic. Each post should have a distinct primary keyword that no other post targets.