Choosing the Right Tool: Lessons from 72 Hours of Infrastructure Hell
We wasted 3 days on Azure before switching to Cloudflare in 20 minutes. Here's the framework we should have used from the start.
Documenting the real AI journey - from learning to implementation.
Building Alien Brain Trust in public. Real insights. Real challenges. Real solutions.
We wasted 3 days on Azure before switching to Cloudflare in 20 minutes. Here's the framework we should have used from the start.
After 3 days fighting Azure Static Web Apps, we switched to Cloudflare Workers. Working endpoint in 20 minutes. Here's exactly how we did it.
After 3 days of infrastructure battles, our Learn Labs enrollment system is live. Get access to our Secure AI Prompt Builder course with hands-on labs and automated security testing.
We spent 72 hours fighting Azure Static Web Apps for a simple enrollment form. CORS errors, deployment token mismatches, and workflow failures. Here's what went wrong.
Azure free tier gives 1M function calls and 10k Key Vault operations. With 5-minute caching, we reduced usage 99% and can scale 100x before paying. Here's the cost breakdown.
How Azure Managed Identity eliminates API keys, passwords, and secrets from your code entirely. DefaultAzureCredential does the authentication for you.
We spent 15 extra minutes implementing Azure Key Vault instead of environment variables. That decision saved months of migration pain. Here's why doing it right from the start matters.
Azure Functions gives 1M free requests vs Vercel's 100k and Netlify's 125k. Plus Key Vault integration, GitHub Actions, and enterprise-ready secrets management.
Built a complete Azure Functions enrollment system with Airtable, GitHub API, and Key Vault in under 90 minutes. Here's the time breakdown and what made it fast.
Upgraded enrollment system from environment variables to Azure Key Vault with expiration tracking, audit logs, and tagging—still completely free.
How we diagnosed and fixed a broken blog auto-publishing system, implemented Git Subtree sync, and learned why multi-repo architectures need clear workflows.
After 90 days and 132 tasks, here are the frameworks that work: decision trees for when to use AI, prompt patterns, quality gates, and repeatable workflows.
We tested 12 AI tools over 90 days. Here's what we actually use daily, cost analysis ($847/month), and why we chose Claude for 80% of work.
AI automated Linear issue creation, support triage, and meeting notes conversion. Here's the pipeline that saved 8 hours in 90 days on PM busywork.
AI saved 14 hours on content in 90 days, but raw AI content is generic. Here's the 3-pass system (draft → refine → humanize) that preserves brand voice.
Template-driven documentation with AI saved 22 hours in 90 days. Here's the workflow, quality checklist, and when to let AI write your docs.
AI learns fast, works tirelessly, but makes predictable mistakes. Here's how we use skills and guardrails to catch bugs before they ship.
Security testing showed the highest time savings per task (2.3 hours). Here's how we used AI to generate 1,200+ jailbreak tests and harden 10 prompts in parallel.
68 hours saved on development in 90 days. But the real shift isn't speed—it's structure. Here's what the AI-augmented company actually looks like.
Real data from three months of AI-augmented work: what worked, what didn't, and the measurable time savings across development, security, and content tasks.
We launched 3 AI agents in parallel to complete a landing page (872 lines), waitlist form (595 lines), and prompt hardening—all simultaneously. Here's what we learned.
Linear keeps us on track across long AI conversations—4 milestones, 37 issues, zero confusion about what's done and what's next.
The skills we've built prevent repeated mistakes—from exposed API keys to broken path resolution—turning every failure into a permanent safeguard.
From manual ticket updates to full automation—37 issues, 195 lines of code, one spectacular encoding failure, and zero seconds of manual work.
Building a 588-line credential manager with platform-native encryption across Windows, macOS, and Linux—zero plaintext secrets, foolproof setup.
Instead of hardening prompts sequentially (2.5 hours), we launched 4 Claude agents in parallel. 8 prompts hardened in 15 minutes.
Our first Linear import corrupted 44 issues due to encoding errors. Here's how we debugged, validated, and fixed it.
14 prompts tested, 10 needed hardening. We used parallel agents to fix 73 high-risk vulnerabilities simultaneously. Here's what we learned.
Testing AI prompts at temperature 0.0 AND 0.9 reveals edge cases you'd never find with single-temperature testing. Here's the data.
Step-by-step breakdown of fixing 9 critical vulnerabilities in a landing page copywriter prompt. Real fixes, real results.
Real security testing results from automated jailbreak attacks on production AI prompts. No theory. Just results.
Twenty-four minutes in pajamas. No whiteboard, no laptop—just voice and Grok. A complete course outline, secure labs, pricing, and lead-gen page before 7:25 AM.
Skills commoditize. Coding, writing, security ops—they're getting swallowed by LLMs. In five years, if you're not building, you're maintenance. Learn to steer machines or wait tables.
It's live. The course isn't perfect—it's raw, it's real, it's done. Thirty minutes and you'll have a vault of prompts that can't screw you. No fluff. Just results.
Twenty minutes of brake lights. Normally, rage. But I opened Grok, didn't shut up, and had a complete product by the time the light turned green.
No pitch—just facts. Every template, test, and real-world patch from this week, wrapped into a course. Secure prompts that actually work. No jailbreaks, no HR drama.
From yelling at Siri to having a real back-and-forth with Grok while driving — the moment AI stopped being a tool and started being a co-founder.
How one commute proved the AI-First Mindset actually works (and why most people are still using AI wrong)
The meta-skill of learning to leverage Claude and AI tools to build secure, production-ready features at record pace - lessons from shipping real projects
AI can build features in minutes, but success requires constant validation and feedback. Learn why the feedback loop matters more than perfect prompts.
How a double URL encoding vulnerability slipped past AI-powered development and what I learned about testing AI-generated code
From hitting usage limits mid-session to uninterrupted 4+ hour flow states. My journey switching from Claude.ai to Claude Code and optimizing my AI development workflow.
A real-time case study of how AI-powered development is 96% faster than traditional dev teams for feature delivery
How I discovered 7 security vulnerabilities in AI-generated code and used AI to fix them - a practical guide to security-conscious AI development
How I cut development time by 75% using Claude to intelligently adapt proven templates for new client projects
Breaking down the exact workflow I use to deliver client projects 70% faster with Claude while maintaining professional quality
A real-world case study of using AI to deliver production-ready ecommerce solutions for a small business client in record time
Technical decisions behind Alien Brain Trust - what I'm building, buying, and why. A framework for platform selection you can apply to your own projects.
Cut through the noise - here are the AI resources I actually use daily, weekly, or regularly. No fluff, just what delivers value.
Inside look at the AI-1001 course - what makes it different, who it's for, and why I'm building an AI education platform focused on real-world implementation over theory.
Honest reflections from my first week building Alien Brain Trust with AI - what worked, what didn't, and what surprised me about the reality of AI implementation.
The irony and beauty of teaching AI while still learning it - why I'm documenting this journey publicly and inviting you to learn alongside me.
After 25+ years in cybersecurity, I'm diving deep into AI - and documenting everything along the way. This is day one of building Alien Brain Trust while learning in public.
An honest look at the AI tools I'm using to build Alien Brain Trust - what's working, what's not, and why I chose each one.
Starting my public AI journey - setting up my development environment with Claude Code while building Alien Brain Trust's AI education platform.
Bridging the gap between AI theory and practical implementation - why I'm building Alien Brain Trust to serve professionals who need to actually use AI, not just understand it.