You already use ChatGPT, Claude, Copilot - maybe a few automations too. And you're still losing 10+ hours a week to tool switching, broken workflows, and AI that forgets everything the second you close the tab.
Your AI tools are powerful alone. We make them work as one.
You've spent real money on AI. ChatGPT Pro, Claude, Copilot — maybe custom agents and API chains on top. It works… until it doesn't. You're still the glue holding six disconnected tools together. Copying context. Restarting dead automations. Re-explaining yourself every session. The AI was supposed to give you time back. Instead it became another thing you have to babysit.
ChatGPT for one thing, Claude for another, Copilot somewhere else. Six subscriptions. Zero integration. You're the middleware - copying, pasting, and re-explaining yourself between tools that have never heard of each other.
The workflow works until it doesn't. No error, no alert. You find out after the miss, when the thing it was supposed to do didn't happen.
No memory. No preferences. No compounding value. Every conversation starts cold. Your AI is brilliant for 20 minutes, then forgets it ever knew you.
Ten minutes here. Twenty there. All week long. You were promised leverage. You got a second job babysitting tools that were supposed to work without you. That's where the 10+ hours go.
One finding, out of typically 8-15 per audit. This one alone was eating 6+ hours a week.
Email drafts, scheduling, and lookups were being handled the same way as high-stakes analysis. That meant unnecessary wait time on simple tasks and constant context-switching all week — you start something else while waiting, then get pulled back. Six hours a week, gone.
6+ hours/week lost to waiting and context-switching. Premium models take 8-15 seconds per response on simple prompts. Lighter models handle the same tasks in under 2 seconds at 95% quality.
Route routine work to fast paths, reserve heavyweight tools for real reasoning, and carry context forward automatically. Estimated time saved: 6-8 hours/week. Implementation: one afternoon.
The client re-explains their role, preferences, project context, and communication style at the start of every AI session. Across 15-20 sessions per week, that's 3-5 minutes of setup each time. The AI never learns, never remembers, never compounds.
60-90 minutes/week on repetitive context-setting. But the hidden cost is worse: the AI never gets good at your specific work because it has no history to learn from. You're training a new intern every single session.
Implement a persistent memory layer - session summaries, preference files, and domain knowledge that carry forward automatically. The AI should know your patterns by week 2, not ask about them in week 12. Estimated time saved: 1-2 hours/week direct, plus compounding quality improvement.
Garrett Mastro doesn't teach frameworks he read about. He's a full-time options trader who built a fully automated 22-strategy trading system — profitable across every quarter it's run. Then he turned that same systematic, checklist-driven methodology on his own AI stack. What follows is exactly what he built, and how long it took.
Six weeks ago, his AI setup was: ChatGPT, used occasionally, with zero memory and zero integration. Every conversation started from scratch. 2.6GB of documents scattered across Google Drive with no system. Newsletter written manually — hours per issue. No monitoring, no automation, no agents. Just a browser tab he opened when he needed something.
WEEKS 1–2
Established the AI agent's identity, memory system, and operating rules. Audited 2.6GB of Google Drive — 347 documents, 360K words — and built a 14-category taxonomy. Set up Drive API integration and moved 102 files into the new structure. Zero to organized in two weeks.
WEEKS 3–4
Ran a failure audit on 1,494 messages to find every breakdown. Deployed Scout (daily intel monitoring across 89 accounts) and Sentinel (twice-daily security sweeps). Built the Board of Directors — 7 AI models giving independent reviews on major decisions. Installed a local LLM for zero-cost classification at 93.1% accuracy. Added local audio transcription, automated health checks, and a monitoring dashboard.
WEEKS 5–6
Migrated everything from a laptop to a dedicated Ubuntu server. Deployed 9 automated cron jobs that run without intervention — intel, security, backups, health checks, and a supervisor that monitors the monitors. Added a knowledge base librarian bot, automated newsletter workflow, local embeddings replacing cloud APIs, and a smoke test suite with 23 automated checks. Built and launched badmutt.com.
This isn't a hypothetical. It's not a demo environment. It's the actual system running the business you're reading about right now — this website was built, reviewed, and deployed by the same AI stack described above. The methodology that built a fully automated trading system with 15 consecutive profitable quarters is the same methodology we apply to your AI workflow in the cohort.
Audit. We map every tool, prompt, automation, and handoff you're relying on and show you exactly where the time is leaking. Most people discover 2-3 tools they're paying for and barely using.
Simplify. Cut the dead weight. Give every tool one clear job and make them actually share context so you stop being the middleware.
Build. We build the missing pieces — persistent memory, smart routing, automations that don't die — live in your real environment during the daily sessions. Not a deck. Not homework.
Train. We train the system on how you work — your style, your domain, your shortcuts — so it gets sharper every single week instead of resetting every Monday.
Verify. You leave knowing how to maintain it yourself. No dependency on us after the 90 days.
I built a fully automated 22-strategy options trading system — profitable across every quarter it's run, 15 straight. The same systematic, checklist-driven methodology that built that system is what I apply to AI workflows. After fixing my own AI stack — built on OpenClaw, an open-source AI agent framework — and getting 10+ hours a week back, I started wondering why everyone around me was still drowning in the same mess. Badmutt is the answer.
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— Bill B.
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— Carolyn S.
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— Johnny N.
From readers of The Routine Trader and professional collaborators
This is a hands-on implementation cohort. Twelve people. Real workflows. Live help every business day. Join when you need a decision, a fix, or a shove across the line.
$2,500 deposit holds your seat. If we move forward with the July 7 cohort, we invoice the remaining $7,500, due by June 23, 2026. If we do not move forward by June 23, your deposit is refunded in full.
We deploy the entire stack ourselves - configured, tested, running in your environment. Pair it with the cohort: $12,500 total, zero heavy lifting on your end.
Add Done-for-You Implementation — $2,500Twelve people. Ninety days. One cohort that replaces the duct tape permanently. Starts July 7.
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