Documenting the real AI journey - from learning to implementation.
Building Alien Brain Trust in public. Real insights. Real challenges. Real solutions.
Our website lives in a Git repo. Claude Code edits it directly in conversation. GitHub tracks the change. Cloudflare deploys it. The whole pipeline takes under 5 minutes.
We sat down with Claude Code, Linear, and a CLEAR prompt to pressure-test a workshop concept. Three hours later we had a product name, pricing, curriculum, platform, and updated website.
The full builder stack — thesis in your repo, Claude reads it, writes your Linear backlog, builds with you in VS Code — only works when Claude Code is in your editor. Here's the setup and why the loop changes how you build.
The fastest way to build a project backlog isn't to write it yourself — it's to write a clear product thesis, put it in your repo, and let Claude act as your Product Owner. Here's the exact setup and the prompts that make it work.
When you build with AI, your repo isn't just a backup. It's the context your AI reads to understand what you're building. Here's how to structure your project so Claude can read your thesis, generate your backlog, and help you build coherently from Day 1.
Most founders skip the most important step: getting crystal clear on what they're building and why — in writing. The CLEAR method walks you through using AI to develop your product thesis, which then becomes the foundation your entire project builds from.
We came in with a simple workshop idea. Claude Code pushed back on scope, ran the revenue math, identified the real moat, and helped us design something that could do $87k in year one. Here's how that conversation went.
We created 5 projects, 9 labels, 6 custom views, and 19 issues in Linear using a Node.js script Claude Code wrote and ran in the same session — with credentials pulled live from AWS SSM.
We sat down with no backlog and a vague direction. 90 minutes later we had 5 projects, 6 custom views, 19 prioritized tickets, and a product launch plan. Here's how the CLEAR method made it possible.
We eliminated all static AWS access keys from our infrastructure — no more secrets in GitHub, no more long-lived credentials. Here's exactly what we did and why.
After shutting down an autonomous AI company, here's the framework we actually use now — and why starting slow with agents beats scaling fast.
We built an autonomous AI company. It worked. That was the problem — here's what happened when agents ran too fast to correct.
Anthropic accidentally shipped ~2,000 internal files in a Claude Code update. No customer data was exposed — but the incident surfaces a risk pattern that security teams adopting AI tooling can't afford to ignore.
We were burning 30-45 minutes every session fighting AWS auth, missing secrets, and dead port forwards. One script fixed all of it. Here's how we built it.
AI will find a way. If your secrets strategy isn't airtight before you start running agents, you will get burned. Here's what happened to us and what we did about it.
We run ABT with a CEO, CTO, CMO, and CFO — all AI agents with distinct personas, real responsibilities, and hard-learned workflow rules.
How we went from root CLI access and accidental IAM user deletion to SSM Parameter Store, dedicated service accounts, and SSO. The real story.
We spent an evening getting Paperclip AI running from scratch: expired invites, root permission blocks, port forward failures, and a CEO agent that finally came alive at midnight.
We set a goal: $10k/month ABT + $5k/month STR = financial independence in 60 days. Here's what's working.
We run a full AI agent orchestration platform — CEO, CTO, CMO, CFO, and COO agents with persistent memory and GitHub access — on a $19/month AWS instance. Here's the exact stack.
We've rebuilt Alien Brain Trust's operating model five times in six months. Each revision taught us something the previous one couldn't. Here's what changed and why.
Agents save time. But giving them push access to your repo is a permission boundary you should think about twice.
We lost our entire AI agent configuration overnight. The rebuild took under 2 hours. The difference wasn't luck — it was a discipline we almost didn't have.
Stop treating token budgets as an afterthought. Here's how to measure token consumption, set realistic budgets, and cut costs without cutting corners.
Named volumes, orphaned containers, and a wiped database taught us to build a $3.50/month backup stack that covers every failure mode. Here's the exact setup.
Bigger isn't always better. How bloated context windows become a security liability and a leak vector for sensitive information.
We lost 16 hours of AI agent configuration overnight. Not from a hack. Not from a failed backup. From a Docker default that nobody warns you about.
Prompt injection is now a production risk. Here's what to test for and how to defend at every layer of your AI pipeline.
Six months, three complete rewrites, and the one metric that finally worked. How we built autonomous quality checks that actually catch problems.
Cut through the noise of RAG hype. We built a practical retrieval pipeline that increased Claude's accuracy by 34% and costs nothing to run. Here's the code.
AI security isn't about catching bad prompts. It's about catching failures your testers never thought to run. We found critical vulnerabilities in production systems using tactics that looked innocent on paper.
Anthropic's Website Wizard prompt from their library, our 3-line modification, and the exact tweaked version we used to replace Squarespace in 2 hours.
How I used Claude Code to build, deploy, and DNS-flip my entire website from Squarespace to Cloudflare Pages in a single session — saving $396/year.
Five practical AI projects that follow the scrape-build-refine-deploy pattern. Each one saves time or money, and each one can be done in a single sitting.
Starting an AI Builder series. Why rebuilding your website is the best first project to learn practical AI — tangible results, low risk, immediate value.
We built an autonomous AI agent that simulates a student, evaluates every module, and creates pull requests to fix what it finds — all running on a $7 ARM64 instance.
We discovered our jailbreak test suite was flagging every refusal as a critical vulnerability. Here's the debugging story, the fix, and what it taught us about scoring AI responses.
Our AI graded every module as 'incomplete.' The content was fine. The evaluator could only see the first 3KB of 20KB files. Here's how we found and fixed it.
We built an AI test bot that enrolls in our course as a student, follows the onboarding emails, and grades every module. It found 15 issues we missed.
What's actually trending in AI right now—DeepSeek's open-source moment, agent failures, and why 2026 is the year AI gets practical.
My AI agent failed. Not because it wasn't smart. Because I didn't connect the pipes.
Tim Ferriss wrote about the 4-hour work week. With AI agents, the math has changed. Here's how to get 40+ hours of output from 10 hours of input.
Three skills have become non-negotiable in the AI age. If you're not learning them now, you're watching the train leave the station.
Used to think if you weren't on a board, you were dead. Then spreadsheets. Now AI. Same hill. Better wheels.
AI-first isn't 'use the tool.' It's asking: how do I make this disappear in three months?
When grunt work dies, noise dies too. Three decisions. Zero emails. 7 minutes to find $73k in leaks.
Not every tool is a tool. Some are dynamite. Pick up the detonator or get off the field.
Zero human words. 50 posts. One month. What happens when your diary writes itself.
Complete marketing campaign from concept to live Squarespace page in one session - landing page, flyer, payment integration, and deployment.
I gave Claude a client project in the morning and came home to a complete marketing campaign - landing page, print flyer, payment integration, and live deployment.
From first post to free course launch - what 90 days of building in public taught us about AI-augmented content creation.
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.
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.
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), I 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. I used parallel agents to fix 73 high-risk vulnerabilities simultaneously. Here's what I 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.
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.
Starting my public AI journey - setting up my development environment with Claude Code while building Alien Brain Trust's AI education platform.