Why I Created SLOS — Part 3: What SLOS Actually Is

Someone once told me: for £20 a month, you could feed the same data to Claude and get a reasoned cash flow analysis. They're right. That was never the question I needed to answer. Ask Claude, or ChatGPT, or any AI tool, to analyse your cash position today, and it will give you a genuinely reasoned answer. Fast. Articulate. Often insightful. Ask it again next month — different analyst, different prompt, different mood — and you'll get a different answer. Not because the tool is wrong. Because a one-off answer was never built to be consistent. That's the gap. Not intelligence. Governance. A finance director cannot walk into a board meeting with "I asked Claude and it said..." That sentence has no persistence of methodology behind it, no audit trail, and nobody accountable when the numbers get challenged six months later. It's a reasoned guess, produced once, by whoever typed the prompt that day. SLOS is not a reasoned guess. It is a standard, applied identically every day — the same daily reconciliation, the same 13-week methodology, the same discipline — whether it's me running it or a junior analyst uploading a template on a Tuesday morning. That consistency is not a feature. It is the entire point. A report tells you what happened. A one-off AI answer tells you what someone thinks happened, once. A standard tells you why it keeps happening — the same way, every time, in a form an auditor can rely on and a board can trust. That is what SLOS actually is. If you've ever been asked "why not just use AI for this?" — I'd like to hear how you answered. Comment, or send me a message. Mala Sun — Founder of Stonerose Treasury