User
Write something
Pinned
Welcome to The Sovereign AI Society — Start Here
Welcome. I'm Eric — and I built this community because I've seen this pattern before. I spent my career in construction technology and enterprise finance. I was deploying virtual cards for AP automation before anyone my age knew what a P-card was. I built my reputation on enterprise software sales, AP and P2P workflow optimization, and helping companies modernize how they move money. I watched an entire industry shift from paper checks to digital payments — and the professionals who moved first built careers that late adopters are still chasing. AI infrastructure is that same inflection point. Most professionals are renting AI through subscriptions and APIs without understanding what they're paying for or what they're giving up. The Sovereign AI Society exists to change that — helping business professionals own their AI infrastructure, understand what to run locally, what to use in the cloud, and make that decision with confidence. Here's how to get the most out of this place: STEP 1: Introduce yourself Drop a comment below with: - Your name and what you do - - Your current experience with AI (beginner, intermediate, power user) - - What brought you here (privacy concerns? cost savings? curiosity? building a service?) - - Your hardware situation (what are you working with right now?) The community is only as strong as the people in it. Your intro helps us help you. STEP 2: Understand the structure The Sovereign AI Society is built around five pillars: 1. HARDWARE FOUNDATION — Understanding the chips, GPUs, SSDs, and memory that make local AI possible 2. 2. YOUR FIRST LOCAL STACK — Hands-on setup from zero to running inference 3. 3. AI FOR YOUR BUSINESS — Applying local AI to real workflows (finance, docs, operations) 4. 4. THE ENTERPRISE PLAY — Packaging and selling local AI as a professional service 5. 5. ADVANCED OPTIMIZATION — Multi-GPU, fine-tuning, RAG, agentic workflows Start with Module 1 if you're new. Jump to Module 3 if you already have hardware running.
0
0
What's the ONE task you'd automate first if it worked perfectly?
Local AI only becomes real when it does something useful on Monday morning. So let's get concrete: if you could point a local model at one repetitive task in your work and have it nail it every time — what would it be? Drop it below in one line. Invoice coding? Meeting notes? Contract review? First-draft emails? No setup required to answer — just tell us the task that eats your time. I'll reply with a suggested model + approach for each one.
Hot take: for 80% of business work, a local 8B model is all you actually need. Agree or disagree?
Cloud frontier models are incredible — but how often does your day-to-day work (summarizing, drafting, Q&A, cleanup) genuinely require them? I'll make the case that most professionals are overpaying for horsepower they rarely use. Where do you land — team "local is enough" or team "I need the big models"? And what's the one task that actually justifies going to the cloud for you?
0
0
The $500 rig vs. the $5,000 rig — post yours
No judgment, no minimum. Whether you're running a mini PC, a gaming laptop, or a multi-GPU tower, I want to see what everyone's actually working with. Reply with: your machine (CPU/GPU + RAM), what you're running on it right now (or "nothing yet"), and one thing you wish it did faster. Starting-line rigs are just as welcome as finished builds — that's the whole point.
0
0
MONDAY MODEL DROP — May 11, 2026
THIS WEEK'S MODEL: Gemma 4 26B MoE (Q4_K_M) WHAT IT'S FOR: Frontier-quality local reasoning over long business documents — contracts, RFPs, board decks, financial statements, construction specs, vendor agreements. WHY IT MATTERS: Gemma 4 is the first local model where the long context window is real. Gemma 3 advertised 128K but its information-retrieval rate at that length was a brutal 13.5%. Gemma 4 jumped that to 66.4% — and the new 26B MoE goes all the way to 256K tokens (~192,000 words, or a 500-page document). The Mixture-of-Experts design activates only ~4B of 26B parameters per token, so it punches at flagship quality (MMLU Pro 85.2%, GPQA Diamond 84.3%) while staying inside consumer-hardware reach. For our community, this is the model that finally makes "drop the whole contract in and ask questions" a sovereign, on-device workflow. INSTALL: ollama pull gemma4 RUN IT: ollama run gemma4 TRY THIS PROMPT — "Monday Morning Document Triage": You are a senior business analyst preparing my Monday morning briefing. I am pasting a business document below. Produce a one-page brief with: • TL;DR — three sentences. What is this document and what does it ask of me? • KEY OBLIGATIONS — the top 5 commitments, deadlines, or deliverables, each with the exact section/page reference. • DOLLARS & DATES — every specific dollar amount, percentage, deadline, and quantity, with context. • RED FLAGS — any clauses, terms, or numbers that deviate from industry norms or that I should push back on. Be specific. • QUESTIONS BEFORE I SIGN — three sharp questions I should ask the counterparty. • NEXT ACTION — the single most important thing I should do today. Do not summarize generically. Quote exact phrases when calling out risk. DOCUMENT: --- [ PASTE YOUR DOCUMENT HERE ] --- HARDWARE REQUIREMENTS: Minimum: 16 GB unified memory (Apple M1/M2/M3) or 12 GB VRAM (RTX 3060 / 4060 Ti 12GB) — ~12–18 tok/s, shorter contexts. Recommended: 32 GB+ unified memory (M2 Pro/Max, M3 Pro/Max) or 16–24 GB VRAM (RTX 4080 / 4090) — ~25–45 tok/s, comfortable 64K–128K context.
0
0
1-16 of 16
powered by
The Sovereign AI Society
skool.com/the-sovereign-ai-society-8092
Own your AI infrastructure. Local, cloud, or hybrid — for finance pros, operators, and builders who want informed control.
Build your own community
Bring people together around your passion and get paid.
Powered by