Hey everyone, We are currently looking for a capable AI Systems / Python Backend Engineer to join us as a strategic technical partner. 🤝 The Partnership Opportunity: Simon and I are highly experienced in business growth, scaling, and enterprise sales. We have a hot, high-velocity outbound pipeline and are actively engaging mid-market operations ($10M+ revenue band). We don't just want someone tucked away behind a screen writing code. We want a technical co-founder to ride along with us. You will be sitting beside us as our technical authority during discovery and scoping sessions with potential enterprise clients, helping us translate their operational pain into engineered solutions. 💼 The Commercial Structure: This is a founding partner / technical co-founder role. We are working on a deferred, milestone-based compensation or profit-share structure that triggers the moment we onboard our first wave of enterprise clients (which we are actively pitching and closing right now). If you want to leverage your engineering skills alongside a proven sales and business machine, this is your ground-floor entry point. 🧱 What We Are Building: We build API AIOS (Artificial Intelligence Operating Systems) and secure Operational Digital Twins that sit quietly on top of mid-market enterprise legacy systems (e.g., ERPs, custom SQL databases, and platforms like SimPRO). Our engine ingests raw operational edge data (chaotic email streams, webhooks, file logs), processes them asynchronously using multi-agent LLM loops, and pushes structured data payloads back into core legacy databases 100x faster than manual human coordination. 🛠️ The Tech Stack You'll Architect: - Infrastructure & Ingestion: Setting up isolated, multi-tenant cloud environments (AWS/GCP), secure cloud data lakes, webhook listeners, and raw email parsing engines. - Guardrails & Orchestration: Engineering programmatic cost-controls, semantic prompt caching, and managing complex, asynchronous Multi-Agent Loops utilizing frameworks like LangChain, CrewAI, or AutoGen (Sensing ──► Interpretation ──► Execution payloads). - Models & Action: Dynamic routing across frontier models (Claude 3.5 Sonnet, GPT-4o) and building custom, secure REST API connectors (OAuth 2.0) to inject validated JSON payloads back into client software.

Hey everyone! Thrilled to be joining this community from Mangawhai / Auckland, New Zealand. I am partnering up with Simon (who just posted his intro earlier!) to launch our Consultant + Builder arbitrage agency. Simon brings a deep background in global B2B corporate strategy, and my focus is entirely on Operations, Systems Management, and Client Delivery Architecture. > We are firm believers that the only strategy that matters for businesses right now is how AI integrates into their operations. Our model is built around pure consulting—Simon diagnoses the bottlenecks and facilitates the high-level roadmap, while I package the workflows, manage the project delivery, and coordinate the infrastructure. My Goal: To build a seamless, organized agency engine that lands and delivers our first paid $2,500 AI Infrastructure Audit within 30 days. My Why: Securing professional freedom, working on our own terms, and building a modern, automated business from scratch. Let’s Connect: Since I will be overseeing our project handoffs, I am looking to connect with reliable, high-caliber Builders inside this hub. If you are a technical wizard who loves building complex AI agents or data pipelines but hates client management and sales, we should talk. Drop a comment below—I’d love to connect! 🤝

Hey everyone, Wanted to drop a quick update on what’s happening behind the scenes here at Strategic AIOS. Over the last few days, we’ve been quietly auditing workflows and mapping out how businesses actually scale without throwing endless headcount at the problem. The biggest takeaway so far? Most businesses aren’t suffering from a lack of talent—they are suffering from invisible friction. Hours are being leaked every single week just keeping systems on life support (manual data entry, app hopping, and constant follow-ups). We are currently building the framework to completely eliminate that friction. We aren't just linking apps together with basic automations; we are embedding an autonomous AI operating system designed to execute high-level strategy in the background. Where we are at right now: - Infrastructure: Finalizing the core operating architecture so it’s frictionless to deploy. - Auckland Transition: We are officially migrating our main operations back to Auckland at the end of August to scale up our face-to-face delivery and local partnerships. - Case Studies: Preparing to document our first live rollouts so you can see the exact before-and-after metrics. We’re moving fast because the AI space doesn't wait for anyone, and the early adopters are going to absolutely dominate this next chapter. I’ll be dropping some practical step-by-step breakdowns of our architecture here soon. In the meantime, I’m curious—for those running teams or agencies in here, what is the single biggest operational bottleneck you are trying to solve before the end of the year? Drop it below, let's swap notes. 👇

We have officially chosen the Consultant path! My partner Simon and I are tackling this together from New Zealand. Simon brings a deep background as a global corporate strategy facilitator, and I am heading up our operations, client onboarding, and delivery frameworks. We chose this path because it allows us to leverage our natural strengths in high-level business strategy and structured execution without getting bogged down in late-night API coding. We love the "Doctor" framework—diagnosing the manual bottlenecks and prescribing off-the-shelf efficiency. Most excited about running our first warm-outreach audits this month, delivering massive time-savings to local Kiwi businesses, and connecting with elite Path B Builders in this community to hand off any complex custom builds down the track. Let’s get to work! 🚀