# The RL3 AI-First Playbook

Source: https://rl3.dev/en/methodology

Seven steps to decide which work stays with your team, which moves to AI, how much autonomy it gets and within what limits. Each step leaves a deliverable your company keeps.

> We redesign the process before we automate it.

### Seven steps, repeated as a cycle

- MAP. Map how the work is done today: We sit down with the people who do the work and walk through it: where information gets stuck, who has to remember what, and how long each handoff waits. (Deliverable: Current-state flow map)
- DECOMPOSE. Break it into tasks: We split each block of work into small tasks and sort them: mechanical, analytical, judgement calls, or work with people. (Deliverable: Classified task inventory)
- REDESIGN. Redesign the process: We remove redundant steps, duplicate approvals and hand-copied data, and draw the new process with AI already in it. (Deliverable: Redesigned process)
- DELEGATE. Split the work: We give each task an autonomy level and write down what the AI receives, which tools it may use and what it must hand back. (Deliverable: Spec for each AI workflow)
- GUARD. Set the limits: We define the worst case, which actions need approval, and how everything stops if something goes wrong. (Deliverable: Safeguard matrix and stop button)
- EVALUATE. Measure: We test with everyday cases and edge cases, and measure quality and cost before every change. (Deliverable: Test suite)
- LEARN. Learn from every correction: Every correction or rejection from your team is logged, and we use it to fine-tune the AI. (Deliverable: Correction log)

### Five levels of autonomy

- L0 A person does it: 100% human work. AI stays out of it.
- L1 AI assists: The person does the work and asks the AI when they need to.
- L2 AI prepares, a person reviews: AI prepares a draft and a person edits it and signs it off.
- L3 AI executes: AI does the task and only asks for approval at the agreed checkpoints.
- L4 AI coordinates: Several agents run a whole process and your team deals with the exceptions.

### RL3 Guard

Each workflow has a risk level from R0 to R4 that caps how much autonomy the AI gets. Tasks start at the most cautious level and move up when testing supports it. If something fails, a stop button hands the work back to your team without taking the service down.

- Input: We filter what comes in, including hidden instructions meant to manipulate the AI.
- Model and tools: The AI only uses the tools and data it has been cleared for.
- Output: We check what the AI is about to say or do before it reaches a customer or your systems.
- Human oversight: Sensitive or irreversible actions go through a person and are logged.

### Reference frameworks

- EU AI Act, including AI literacy (Art. 4)
- ISO/IEC 42001
- NIST AI Risk Management Framework

### Why we start with the process

Put AI on top of a badly designed process and you automate its flaws too. That's why our engineers work inside your company, next to the people doing the work, and redesign the process before automating it. The model is called Forward Deployed Engineering.

### Reference frameworks

The method is aligned with the EU AI Act, including the Article 4 AI literacy duty, with ISO/IEC 42001 for AI management systems, and with the NIST AI Risk Management Framework. In practice, every workflow has its own risk inventory, documented human oversight, an audit log and a team trained to use it.

### In our projects

At Efímero Clinic, Sofía confirms date, time and practitioner with the patient before saving an appointment in Flowww, and passes any urgent symptom to staff. In Compliance Brain, a true screening match stops the case the same day, and every onboarding needs the MLRO's second approval.

### Where to start

Every project starts with a free assessment. We talk through one process that costs you time or money and tell you whether AI fits, at what level, and where we'd start.

## How we start

- Tell us what you want to hand off: Through the contact form or on WhatsApp.
- Free assessment: A call to understand the process. We tell you whether AI fits and where to start.
- Written proposal: Scope, timeline and price, before any work begins.
- Built in phases: We start with what you'll notice first and work in short cycles your team tests as we go.