How to Set Up an Agentic Coding Workflow: A Step-by-Step Guide
Everyone is talking about agentic coding. Fewer people explain how to actually set it up. Not the theory — the actual steps, from a blank terminal to a fully functioning agentic workflow where an AI agent builds features, remembers your project, and works across sessions without losing context.
This is that guide. Practical, step-by-step, no hand-waving. By the end, you will have a repeatable workflow that makes you significantly faster.
What You Will Need
Before you start, make sure you have:
- macOS (this guide assumes Mac, but the concepts apply anywhere)
- Claude Code installed — run
npm install -g @anthropic-ai/claude-codeif you have not already - A project to work on — an existing codebase works best for learning the workflow
- Beam (optional but recommended) — for organizing your terminal sessions and persisting project memory
That is it. No complex infrastructure, no Docker containers, no cloud setup. The entire workflow runs locally.
Step 1: Create Your Project Workspace
The foundation of an agentic workflow is a clean, organized workspace. Open Beam and create a new project:
1Press ⌘N to create a new workspace. Name it after your project.
2Set the working directory to your project root. This tells every new terminal tab to start in the right place.
3Configure the memory file path — this is where your project context will live between sessions (more on this in Step 2).
Step 2: Initialize Project Memory
This is the step most developers skip — and it is the most important one. Project memory is what separates “using Claude Code” from “having an agentic workflow.”
Create a markdown file at ~/YourProjectName.md and fill it with everything an agent needs to know about your project:
Project Memory Template
# Project Name
## Architecture
- Language/Framework: [e.g., Next.js 14 + TypeScript]
- Database: [e.g., PostgreSQL via Prisma]
- Key directories: src/app (routes), src/lib (utilities), src/components
## Build Commands
- Dev: npm run dev
- Build: npm run build
- Test: npm run test
- Lint: npm run lint
## Conventions
- Use named exports, not default exports
- All API routes return { data, error } shape
- Components use .tsx, utilities use .ts
- Tests live next to source files (Component.test.tsx)
## Key Decisions
- Chose server components by default, client only when needed
- Auth via NextAuth with GitHub provider
- Deployed on Vercel, preview deploys on every PR
## Current Work
- [Update this section as you work]This file is your project’s brain. Every time Claude starts a new session, it reads this file and immediately understands your architecture, your conventions, and your current priorities. Without it, the agent starts from zero every single time.
Step 3: Install Memory on Agent Startup
With your memory file created, you need to load it into Claude’s context at the start of every session. In Beam, click the “Install Project Memory” button in the toolbar. This writes the memory file contents into Claude’s .claude/ project configuration so the agent loads it automatically.
What happens behind the scenes: Beam reads your memory markdown file and installs it as a CLAUDE.md file in your project’s .claude/ directory. Claude Code automatically reads this file when starting a session in that directory.
Without Beam
If you are not using Beam, you can manually create a CLAUDE.md file in your project root. Claude Code reads it automatically on startup. The key is to keep it updated — stale memory is worse than no memory.
Step 4: Organize Your Terminal Layout
An agentic workflow involves more than just one terminal. Set up tabs for each concern:
- Tab 1: “Agent” — your Claude Code session, where the AI does its work
- Tab 2: “Dev Server” — your local development server running (
npm run dev) - Tab 3: “Git” — for reviewing changes, staging commits, pushing code
- Tab 4: “Tests” — run your test suite here to verify the agent’s work
Once your tabs are arranged, save the layout with ⌘S. Tomorrow, when you sit down to work, load the layout and everything is exactly where you left it.
Step 5: The Agentic Workflow Loop
Now the real work begins. The agentic workflow follows a five-phase loop. Once you internalize this pattern, it becomes second nature.
Phase 1: Intent
Tell the agent what you want, not how to do it. Be specific about the outcome, not the implementation. Example: “Add a user settings page where users can update their display name and email. Include form validation and a success toast.”
Phase 2: Spec
The agent creates a plan. It will outline which files to create or modify, what the approach will be, and any questions it has. Review this carefully — catching a wrong direction here saves 10 minutes of wasted implementation.
Phase 3: Implement
The agent writes the code. It reads existing files, understands patterns from your memory file, and generates code that follows your conventions. Let it work. Resist the urge to micromanage individual lines.
Phase 4: Verify
The agent tests its own work. It runs your test suite, checks for lint errors, and verifies the build passes. If something fails, it fixes it automatically. This is where the “agentic” part really shows — the agent iterates without you.
Phase 5: Review
You review the result. Switch to your Git tab, run git diff, and read through the changes. Check the dev server to see the feature in action. This is your quality gate — the agent proposes, you approve.
This loop repeats for every feature, bug fix, or refactor. Intent, Spec, Implement, Verify, Review. The agent does 80% of the work. You do 20% — the critical 20% that ensures quality.
Step 6: Save Context Back to Memory
After a productive session, your project has changed. New components, new API routes, new architectural decisions. If you do not save this context, the next session starts without knowing what happened.
In Beam, click the “Save Project Memory” toolbar button. This updates your memory file with the current state of the project — new files, recent decisions, and anything the agent learned during the session.
If you are doing this manually, open your ~/YourProjectName.md file and update the “Current Work” and “Key Decisions” sections. Add any new conventions that emerged. Note any architectural changes.
Step 7: Multi-Agent Scaling
Once you are comfortable with the single-agent workflow, you can scale up. Here is when to add more agents:
- Separate concerns — one agent works on the frontend while another handles the backend API
- Parallel features — two independent features that do not touch the same files
- Code + tests — one agent writes implementation, another writes comprehensive tests
Coordination is key. Give each agent its own Beam workspace tab. Make sure their memory files include which areas of the codebase they own. And always have one agent finish before another touches the same files — merge conflicts between AI agents are no fun.
Common Mistakes
Pitfalls to Avoid
- No memory file — the agent starts from scratch every session, wasting the first 5 minutes rediscovering your project. Always maintain a memory file.
- No terminal organization — 8 tabs all named “zsh” with no way to find anything. Use named workspaces and tabs, or you will spend more time searching than coding.
- Micromanaging the agent — telling Claude exactly which lines to change defeats the purpose. Describe the outcome and let the agent figure out the implementation.
- Skipping the review phase — trusting agent output blindly leads to subtle bugs and technical debt. Always review the diff before committing.
- Never updating memory — stale memory is almost worse than no memory. The agent makes decisions based on outdated information. Keep it current.
- Running multiple agents on the same files — guaranteed merge conflicts and wasted work. Divide the codebase into clear ownership zones.
Ready to Build? Start with the Right Workflow.
Beam gives you workspaces, project memory, and terminal organization built for agentic coding. Set up once, build faster forever.
Download Beam FreeSummary
An agentic coding workflow is not magic — it is a system. The seven steps:
- Create a project workspace — isolate your project in a clean environment
- Initialize project memory — give the agent everything it needs to understand your codebase
- Install memory on startup — so every session begins with full context
- Organize your terminal layout — separate concerns into dedicated tabs
- Follow the workflow loop — Intent, Spec, Implement, Verify, Review
- Save context back to memory — so the next session picks up where you left off
- Scale to multiple agents — when you are ready for parallel execution
The developers who are shipping the fastest in 2026 are not the ones writing the most code. They are the ones with the best systems. Set up your workflow once, refine it over time, and let the agents do the heavy lifting.