AI Automation Blog

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.

7 Claude Code Workflows Built for ADHD Developers
How ADHD developers use Claude Code's intelligent caching and workflow orchestration to replace chaos with systems. Practical examples included.

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.

Building Software Without AI-First Architecture Is Already Wrong
My thesis on why the future of software development starts with AI agents, not IDE plugins. MicroSaaSBot is proof of concept.
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.
Per-File SaaS Pricing Is Wrong — Here's Why I Charge Flat Rate Instead
The strategic thinking behind flat-rate SaaS pricing in a market dominated by per-transaction models. Heavy users save money, you get loyalty.
I Built an AI That Ships SaaS Products: Here's Everything That Happened
Announcing MicroSaaSBot—the AI system that takes ideas from validation to deployed MVP with minimal human intervention. It built StatementSync in one week.
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.
Writing Code Before Validating Your Idea Is Wrong
The validation phase that prevents building products nobody wants. Market research, persona scoring, and the go/no-go decision that saves weeks of effort.
I Built a Multi-Agent SaaS Builder: Here's the Full Architecture
Deep dive into MicroSaaSBot's multi-agent architecture: Researcher, Architect, Developer, and Deployer agents working in sequence to ship SaaS products.
How I Validated a Pain Point and Shipped a SaaS in 7 Days
How I validated a bookkeeper pain point and shipped a working SaaS in 7 days using MicroSaaSBot. The story of StatementSync from idea to production.
Using pdf-parse on Vercel Is Wrong — Here's What Actually Works
Why pdf-parse fails on Vercel serverless and how unpdf solves it. A debugging story with zero native dependencies and 3-5 second processing times.
Full AI Automation Without Human Review Is Wrong — Here's Why I Changed My Approach
Keep humans in control when building AI security tools. Full automation sounds impressive until your reputation tanks from false positives.
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.
ADHD Working Memory Is Actually Your Systems Architecture Superpower
ADHD working memory limitations force abstraction. Unable to hold all details, you naturally build mental models—exactly what system architecture requires.
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.
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 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 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.
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.
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.
Full Automation for Security Research Is Wrong — Here's What Actually Works
Why mandatory human review protects researcher reputation better than any algorithm. Building AI that knows when to stop. Part 5 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.
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.
Trusting AI-Generated Code Without Verification Is Wrong
The psychology of skipping verification and how forced evaluation achieves 84% compliance. Evidence-based completion for AI-generated code.
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 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 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.
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.
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.
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.
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.
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.
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.
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.
Your LLM Hallucinating Facts Is Wrong — Here's How RAG Fixes It
RAG combines LLMs with real-time data retrieval to provide accurate, up-to-date responses. Learn how RAG works and why it matters for AI builders.