AI Operation Automation: Get Shit Done Step by Step
Discover how the Get Shit Done™ methodology helps CTOs and CEOs implement AI automation in 30 days. Real results, no delays.
The Problem: Slow Implementation, Endless Meetings
Your company is bleeding money. Manual processes consume 40% of your team's time. You've heard about AI, about Super Agents, about automation. But the last three "digital transformation" initiatives took 18 months, cost three times the budget, and delivered half of what was promised.
You're a CTO or CEO. You don't have time for consultants who talk about "transformational journeys." You need results—operational, measurable, financial. You need AI operation automation that actually works, deployed fast, and delivering impact from day one.
That's where Get Shit Done™ comes in.
This isn't a methodology born in Silicon Valley boardrooms. It's a proprietary framework built by Rhodium to solve a specific problem: how to architect, assemble, and operate AI systems that transform enterprise operations without the typical 18-month implementation nightmare.
In this guide, we'll walk you through the exact steps we use to implement AI operation automation in 30 days. Real. Measurable. Operational.
What Is Get Shit Done™? Beyond the Name
Get Shit Done™ is Rhodium's proprietary methodology for AI operation automation at enterprise scale. It's built on three pillars:
- Design → Define the problem, map the process, identify the AI component that solves it
- Assemble → Integrate best-in-class AI components (no reinventing the wheel; we orchestrate the world's best AI)
- Operate → Deploy, monitor, optimize, and scale the system in production
The difference? Most consulting firms sell you a "roadmap." Rhodium delivers a functioning system in 30 days.
Step 1: The 72-Hour Diagnostic (Week 1)
The Goal: Map your operational pain points and quantify the impact.
This isn't a three-month "discovery phase." In 72 hours, our team runs:
Process Audit — We observe, measure, and document your current workflows. Where is time wasted? Where are errors happening? Where does manual work create bottlenecks?
Financial Impact Calculation — We quantify the cost of inaction. If your customer service team spends 8 hours/day on repetitive questions, and you have 15 agents, that's 120 hours/week. At $25/hour fully loaded, that's $3,120/week or $162,240/year going to tasks that could be automated.
AI Readiness Assessment — Which processes can be solved with current AI? What data do you need? Where are the gaps?
The output: A 72-hour diagnostic report with a clear, numbered problem statement and a preliminary AI solution path.
Real example: A clinic chain contacted us. They were spending 6 hours/day on patient appointment confirmations, medication reminders, and basic Q&A. Our diagnostic showed $184,000/year in avoidable labor costs. Within 72 hours, we had a clear path to deploy HeroDoc (our H.E.R.O. line for healthcare) to automate 90% of that work.
Step 2: Solution Design & Component Selection (Week 2)
The Goal: Design the AI system and select the right components.
This is where most companies fail. They buy a generic software platform and try to force their processes into it. We do the opposite: we design the solution for your problem, then assemble the right AI components.
2A: Process Redesign for AI
We redesign your workflow to leverage AI at the right points:
- Tier 1 (Full Automation) — Repetitive, data-driven tasks. Customer support Q&A, data entry, scheduling.
- Tier 2 (AI-Assisted) — Complex tasks where AI augments human decision-making. Triage, prioritization, recommendations.
- Tier 3 (Human) — Tasks requiring judgment, empathy, or legal authority.
2B: AI Component Selection
This is where AI operation automation gets real. We don't build from scratch. We orchestrate:
- Large Language Models (LLMs) for understanding, generating, and reasoning through operational language
- Automation APIs for connecting systems (your PMS, CRM, ERP, etc.)
- Agentic AI — AI that acts autonomously, makes decisions, and escalates only when needed
- Custom Training Data — Fine-tuning models on your specific domain
Real example: For HeroBistro (restaurant automation), we layer:
- Natural language understanding (order clarification, allergies, modifications)
- Real-time inventory integration (suggesting menu items based on stock)
- Autonomous order routing to kitchen systems
- Customer communication (confirmations, delays, upsells)
All of this runs in parallel, invisible to your team. The system doesn't just process orders—it operates the restaurant.
Output of Step 2: A detailed Technical Architecture Document showing exactly which AI components integrate where, what data flows through, and how the system makes decisions.
Step 3: Data Preparation & Integration (Weeks 2-3)
The Goal: Get your data ready for AI.
AI isn't magic—it's precise. Bad data = bad results. We:
- Inventory Your Data — Catalog all sources (databases, APIs, cloud storage, spreadsheets—yes, we find those)
- Clean & Standardize — Remove duplicates, fix inconsistencies, ensure data quality
- Create Training Sets — Build historical data that teaches the AI how your business works
- Set Up Data Pipelines — Automate the flow of fresh data into the AI system every hour, every minute, or in real-time
This is not glamorous work, but it's critical. A hospital that wants HeroDoc to triage patient calls needs clean patient histories, appointment data, and medical notes. Without it, the AI makes guesses instead of decisions.
Output of Step 3: Verified, clean data pipelines feeding your AI system.
Step 4: AI Training & Calibration (Week 3-4)
The Goal: Train the AI on your specific operations.
We don't deploy generic models. We fine-tune:
- Domain Adaptation — The AI learns the language, rules, and patterns specific to your business
- Decision Trees — We teach the AI when to automate, when to escalate, how to handle edge cases
- Safety Guardrails — Rules that prevent the AI from breaking compliance, losing money, or upsetting customers
This happens in parallel with your team. We don't disrupt operations.
Real example: HeroSocial (our AI for organic demand generation) learns from your past successful campaigns, audience behavior, and conversion patterns. It doesn't start from zero—it starts from your operational DNA.
Output of Step 4: A trained, calibrated AI system tested in a controlled environment, ready for live deployment.
Step 5: Soft Launch & Monitoring (Week 4)
The Goal: Deploy to production and monitor obsessively.
We don't flip a switch and pray. We:
- Gradual Rollout — Deploy to 10% of volume first. Monitor for 48 hours.
- Real-Time Dashboards — Track every decision, every error, every escalation
- A/B Testing — Compare AI vs. human performance on the same tasks
- Daily Optimization — Adjust thresholds, rules, and models based on live data
By day 30, the system is handling the full load with measurable, documented results.
Real example: When we deployed HeroBistro for a 40-restaurant chain, day 1 handled 15% of orders. By day 7, 85%. By day 30, 98% (the remaining 2% required human judgment). The result:
- Order accuracy improved from 92% to 99.2%
- Labor costs in the ordering process dropped 73%
- Customer satisfaction scores increased 18% (fewer mistakes, faster service)
All within 30 days. All measurable.
Step 6: Operate, Learn, Evolve (Ongoing)
The Goal: The system continuously improves.
This is where AI operation automation scales. Your system isn't a static piece of software—it's a learning organism. Every interaction teaches it something new.
- Weekly Optimization Calls — We review data, identify patterns, suggest improvements
- Quarterly Model Updates — Incorporate new operational knowledge, handle seasonal patterns
- Expansion Planning — Once one process is automated, we layer in the next
The Numbers: Why Get Shit Done™ Works
Let's be concrete. Companies using Get Shit Done™ see:
- 30-day deployment vs. 18-month cycles — 600% faster to value
- Labor cost reduction: 40-70% on automated processes
- Accuracy improvement: 8-18% (AI beats tired humans at repetitive tasks)
- Customer experience improvement: 12-25% (faster, more consistent)
- Payback period: 3-6 months in most cases
We're not selling optimism. We're selling operations that work.
How Rhodium Solves This: Meet the H.E.R.O. Line
Rhodium is not an agency. We're your AI operating partner.
We orchestrate best-in-class AI components into H.E.R.O. systems (Human Enhanced Robotics Optimization) for specific verticals:
- HeroDoc — Clinical operations (patient triage, appointment management, medical Q&A)
- HeroBistro — Restaurant operations (ordering, inventory, kitchen coordination)
- HeroSocial — Demand generation (organic social growth, content strategy)
- HeroHotels — Hospitality operations (reservations, guest services, housekeeping)
- HeroEnergy — Energy sector operations (monitoring, forecasting, compliance)
Each system follows the Get Shit Done™ methodology: Design → Assemble → Operate.
We also offer H.E.R.M.E.S. (Human Enhanced Metrics Engine Systems) for government and corporate intelligence—operational dashboards that turn raw data into decisions.
The Get Shit Done™ Guarantee
When you work with Rhodium:
- Week 1: You have a diagnostic and a clear problem statement
- Week 2-3: The AI system is designed, data is prepared, integration is underway
- Week 4: Live in production, measurable results, continuous optimization begins
No vaporware. No consultant decks gathering dust on your shelf. No "transformation roadmap" that takes three years.
Just operational results.
¿Ready to Operate with AI?
In Grupo Rhodium, we design, assemble, and operate AI systems that transform company operations. We don't sell off-the-shelf software—we build bespoke systems with the Get Shit Done™ methodology.
Let's talk on WhatsApp and discuss your operational challenge.
And if you want to dive deeper, check out more articles on our blog about operational AI, Super Agents, and automation at scale.