Original AI Mastermind pitch deck - an overview of the complete AI automation system. Slide 1: The Setup Two AI agents working in tandem: - CASE (Mac Mini, CTO/CMO): Content creation, LinkedIn outreach, social media automation, infrastructure - TARS (MacBook, COO/CRO): Operations, client pipeline, revenue tracking, meeting prep Shared data via git sync. Primary: MiniMax M2.5. Fallback: Sonnet 4.6. Slide 2: Feedback Loop Architecture Core concept: Data Collect > Analyze Patterns > Rewrite Strategy > Execute (loop). 7 active feedback loops auto-optimize outreach, content, engagement, and sales conversion. Slide 3: Daily Schedule Morning crons, afternoon engagement, evening content scheduling, overnight batch processing. Slide 4: Model Allocation Tiers - Premium (Opus): Strategic rewrites that control other crons - Standard (Sonnet): Human-facing tasks, DMs, judgment calls - Budget (Qwen/MiniMax): Mechanical tasks, templates, clicking buttons Slide 5: Before vs After Before: Manual everything, 0 pipeline, no systems. After: Automated outreach (20 connections/day), content pipeline, CRM tracking, automated follow-ups. Slide 6: Key Learnings - Sub-agents need explicit completion criteria - Ralph loops prevent context overflow - Browser profile isolation is critical - Model tier selection saves significant cost - Feedback loops require data logging from day one Slide 7: Full Tech Stack OpenClaw, Claude, MiniMax, Qwen 3.5, Facebook Graph API, Instagram API, Upload-Post, Calendly, Himalaya email, git sync, bash scripts. Slide deck available - reply if you want the link.

Slide deck from the AI Mastermind group covering the full automation system architecture. Key topics: 1. The Setup - Two AI agents working together: CASE (Mac Mini) handles content, outreach, and infrastructure. TARS (MacBook) handles operations, client work, and pipeline. Both share data via git sync. 2. Feedback Loop Architecture - The core concept: Data Collect > Analyze Patterns > Rewrite Strategy > Execute > repeat. Active loops include: Content Performance, LinkedIn Outreach, Engagement Rules, Blog Analytics, Profile Viewers, Calendly Attribution. 3. Daily Schedule - Morning: LinkedIn acceptance check, content ideas. Afternoon: DM replies, engagement. Evening: Content scheduling, pipeline review. Overnight: Batch crons, git sync. 4. Model Allocation - Opus for strategy/conversation (main session only), Sonnet for human-facing tasks, Qwen/MiniMax for mechanical/template tasks. 46 of 57 crons run on free/cheap models. 5. Tech Stack - OpenClaw (agent framework), Claude, MiniMax, Qwen 3.5, Facebook Graph API, Instagram API, Calendly API, Himalaya email CLI, git-based sync between machines. 6. Key Learnings - Sub-agent rules, Ralph loops for long-running tasks, browser profile isolation, content performance tracking, autonomy guardrails. Slide deck available - reply if you want the link.

Session notes from Feb 25, 2026. Topics covered: 1. OpenClaw Architecture - How the agent system is structured: feedback loops that persist across sessions, failure-to-guardrail pipeline, tiered memory with trust scoring, nightly extraction and synthesis, friction detection for contradicting instructions. 2. LinkedIn Automation - Outreach strategy using targeted connection requests (20/day), personalized DM sequences, content-driven engagement. Profile optimization, niche targeting (physicians, founders, operators). 3. Social Media Automation - Posting workflows for LinkedIn, Facebook, Instagram, and TikTok. Content repurposing pipeline: one idea turns into posts across all platforms. Cron-based scheduling, engagement tracking, performance feedback loops. 4. Tools & Stack - OpenClaw, Claude Sonnet, MiniMax, Qwen, Facebook Graph API, Instagram API, Upload-Post service. Git sync between two agents (CASE and TARS) for coordinated workflows. Slide deck available - reply if you want the link.

Session notes from March 4, 2026. We covered four topics: 1. iMessage Forwarding - How to forward iMessages from your phone to your Mac to receive all SMS 2FA codes without a physical SIM nearby. Works on any service, supports multiple devices, instant delivery. 2. Qwen 3.5 - Alibaba's new 397B parameter model benchmarking near Claude Opus 4.5 level. 200K context window, costs ~$2/month via API. A serious contender for cron/automation tasks. 3. Ollama Cloud - $20/mo gives 20x the free tier requests. Includes Qwen 3.5, MiniMax VL models, full model library. No hardware required, API-compatible (drop-in replacement), 99.9% uptime SLA. 4. OpenClaw Apps - What you can build: sales outreach automation, scheduling bots, CRM sync, social media posting, email automation, research scraping. Plus self-learning feedback loops: collect data daily, analyze weekly, auto-optimize. Slide deck available - reply if you want the link.