I Let an AI Agent Run My Blog for 30 Days. Here's What It Actually Did.
How I configured OpenClaw to study my writing voice, handle SEO/AEO/GEO, and publish blog posts autonomously with a single Telegram approval.
10 min read ai-building
Systems Architect · Automation Developer
Build AI Systems That Eliminate Busywork.
Agent pipelines. Automation tools. Claude Code workflows for developers who think differently.
UC Berkeley, Data Science Claude Code early adopter 20+ shipped projects Live production systems
What I build
Claude Code Mastery
Map Context
Build Agent
Ship & Observe
Map context, build agents, ship and observe — the complete loop.
Automation Pipelines
LIVE ▌
n8n + Claude pipelines that run while you sleep.
Published Weekly
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New guide or case study drops every week.
Most dev tutorials cover syntax.
Wecover systems.
Not how to write a for loop. How to build agent chains that outrun your competition while you sleep.
Step 01
Map the Pain Point
Every automation starts with a specific, recurring bottleneck. We find it, measure it, and design around it — not around what looks impressive.
Step 02
Build the Agent Chain
Claude Code, n8n, and custom tooling wired together as a system. Each node does one thing well. The chain handles the complexity.
Step 03
Deploy and Observe
Ship to production, watch the metrics, tune the thresholds. Living systems that get smarter with every cycle.
Topic Clusters
Browse all postsNeurodivergent Systems
ADHD traits as engineering advantages: pattern recognition, resilience, and system design.
2 pillars / 5 supporting
Pillar guides
- How I Built a Productivity System That Works With ADHD (After Years of Failure)
After years of failed GTD attempts and abandoned Notion setups, I built ADHD-friendly Notion templates with energy-aware scheduling and AI processing.
- ADHD Pattern Recognition Is Actually a Superpower for AI Architecture
ADHD pattern recognition isn't noise—it's a superpower for AI system design. Here's how hyperfocus and cross-domain thinking create better architectures.
Supporting posts
- ADHD Parallel Thinking Is Actually Perfect Training for Distributed Systems
ADHD juggling of unfinished thoughts mirrors distributed computing. Managing concurrent mental threads builds intuition for async architectures.
- ADHD Novelty-Seeking Is Actually Your Unfair Advantage in AI
ADHD's dopamine-seeking behavior drives continuous learning and early adoption. This 'shiny object syndrome' is actually technology scouting for the AI era.
- ADHD Chaos Is Actually the Best Training for Production System Failures
Living with ADHD means constant failure recovery. This builds resilience and failure-handling intuition perfect for distributed systems design.
AI Product Development
Claude Code workflows, micro-SaaS execution, and evidence-based AI building.
2 pillars / 12 supporting
Pillar guides
- How I Use Claude Code to Ship Production-Quality Code Every Session
Master Claude Code with quality gates, context management, and evidence-based workflows. The comprehensive guide to building with AI that doesn't break.
- How I Go From Idea to Deployed MVP in Under 24 Hours
The full pipeline from 'I have an idea' to 'it's live on Vercel with Stripe billing.' Every phase explained with the real StatementSync timeline.
Supporting posts
- How I Cut AI Code Errors by 84% With a Two-Gate Verification System
A two-gate mandatory system that blocks implementation until quality checks pass. Here's how it works and why 'should work' is banned.
- How I Stopped Claude Code From Losing Context After Every Compaction
Dev docs prevent Claude Code context amnesia after compaction. Three files that persist task state so Claude picks up exactly where it left off.
- How I Cut AI Token Usage by 60% With Progressive Context Loading
Loading less context upfront makes AI more effective. Here's the 3-tier system that cut my Claude costs while improving output quality.
Bug Bounty Automation
Autonomous security testing with human-in-the-loop safeguards and evidence gates.
2 pillars / 5 supporting
Pillar guides
- I Built a Semi-Autonomous Bug Bounty System: Here's the Full Architecture
How I built a multi-agent bug bounty hunting system with evidence-gated progression, RAG-enhanced learning, and safety mechanisms that keeps humans in the loop.
- I Built an AI-Powered Bug Bounty System: Here's Everything That Happened
Why I chose multi-agent architecture over monolithic scanners, and how evidence-gated progression keeps findings honest. Part 1 of 5.
Supporting posts
- Finding a Vulnerability Without Validation Is Wrong — Here's How to Cut False Positives
Why 'finding' a vulnerability isn't enough, and how response diff analysis cut my false positive rate dramatically. Part 2 of 5.
- Bug Bounty Failures Are Actually Your Best Automated Learning System
How my bug bounty automation learns from rate limits, bans, and crashes to get smarter over time. Part 3 of 5.
- How I Built Unified Bug Bounty Scanning Across HackerOne, Intigriti, and Bugcrowd
How I built unified integration for HackerOne, Intigriti, and Bugcrowd with platform-specific formatters and a shared findings model. Part 4 of 5.
Quantitative Trading Systems
Building, testing, and operating automated trading bots on prediction markets and crypto exchanges.
1 pillar / 3 supporting
Pillar guides
- How I Built a Polymarket Trading Bot That Actually Makes Money
A full technical walkthrough of building a latency arbitrage bot for Polymarket prediction markets — from Binance WebSocket signals to CLOB order placement.
Supporting posts
- The Math Behind Directional Betting in Binary Markets
Expected value, Kelly criterion, and position sizing for binary prediction markets. The mathematics that separate profitable directional bets from guessing.
- Self-Tuner: Building an Adaptive Position Sizing System in Python
How to build a self-tuning position sizing system that adjusts bet size based on recent performance — without overfitting or over-reacting to variance.
- Binance to Polymarket: Building a Real-Time Momentum Signal Pipeline
How to wire Binance WebSocket price feeds into a Polymarket trading bot — signal detection, filtering, deduplication, and latency-optimized order flow.
Answer Engine Optimization (AEO)
Make your content extractable by AI search engines with crawl access and structure.
2 pillars / 2 supporting
Pillar guides
- 6 AEO Factors That Decide Whether AI Search Engines Cite Your Content
AEO is the SEO of AI search engines. Learn to optimize for Perplexity, Claude, ChatGPT, and other answer engines without traditional SEO.
- 8 Steps to Get Your Content Cited by Perplexity, ChatGPT, and AI Search
Step-by-step guide to make your content visible in AI search engines. Includes robots.txt, structured data, and content format optimization.
Supporting posts
- Your robots.txt Is Not Enough for AI Crawlers — You Need llms.txt
What is llms.txt and why do AI engines scan it? Learn how to set up this robots.txt companion file to control how AI crawlers use and cite your content.
- Cross-Posting to Dev.to Immediately After Publishing Is Wrong
Why waiting 72 hours before cross-posting to Dev.to protects your canonical SEO. RSS + Zapier + Slack creates a safe, automated cross-posting workflow.
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The Neurodivergent Engineer
AI automation that works with your brain
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Weekly insights on Claude Code workflows, MicroSaaS builds, and productivity systems designed for ADHD founders. No fluff, just actionable strategies.
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