EXPERT COURSE

AI Agents for Localization

From Prompts to Workflows to Agents

Practical Agentic Automation for Real Localization Teams

Most localization professionals already use AI tools for writing, translation, or brainstorming. But a new generation of AI systems is changing how localization work gets done: AI agents that can plan, use tools, and execute multi-step tasks on their own.

AI agents introduce a new way of interacting with localization workflows. Rather than running one prompt at a time, agents combine memory, tools, planning, and protocols such as MCP to carry out structured work — editing files, comparing translations, checking placeholders, or preparing reports — across folders, localization files, spreadsheets, and repositories.

Designed for Localization Professionals

This course focuses on practical execution rather than theoretical AI discussions. Participants will learn how AI agents — including coding agents such as Claude Code and no-code agent platforms — can assist with localization workflows using mostly natural language and beginner-friendly examples.

The course is designed specifically for localization professionals who want to understand how AI agents can support their workflows without needing to become software engineers. Through hands-on demonstrations and realistic localization scenarios, participants will explore how agentic automation can reduce repetitive work, improve consistency, and support scalable localization operations.

Why Agentic Automation Matters Now

The Opportunity: According to Nimdzi Insights, the language services industry continues to evolve toward increasingly technology-driven multilingual operations. Localization teams are expected to manage more content, more languages, and faster release cycles with limited resources. Many repetitive tasks — file validation, terminology checks, format conversion, placeholder QA, semantic QA, and release preparation — can now be handled by single agents or coordinated multi-agent workflows, without requiring deep engineering expertise.


Conditions: Please read our course and subscription plans terms and conditions carefully. With your registration, you confirm that you have read, understood and accepted our conditions and agree with them. 

If you have any questions, please visit the FAQ section (for courses or subscription plans) or get in touch with us.

Add to Calendar

Apple Google Office 365 Outlook Outlook.com Yahoo

  • This webinar includes:
  •     Expert tutor: Andrés Romero, AI Specialist at Acolad Group
  •  Lifetime access to the course and extra contents
  •  In English
  •  TranslaStars Certificate of Completion
  •  Course duration: 4 h (approximately)
  •  When: 18 June - 16.00 to 20.00 CEST
Course created in collaboration with:

Free for Crowdin Enterprise Users

AI agents for localization

Learn how AI agents and agentic workflows automate localization tasks, from core concepts, MCP, memory, and tools to multi-agent systems and no-code orchestration.

Sessions Breakdown

01 Session

Core Concepts and Applied Use Cases

  • ▸ Introduction to agents: the evolution from prompts to workflows to agents
  • ▸ Workflow-based vs. agent-based systems (deterministic vs. agentic)
  • ▸ Anatomy of a modern agent
  • ▸ Core concepts: memory, tools, and MCP
  • ▸ Planning and evaluation in agentic systems
  • ▸ Claude Code: capabilities and limitations of coding agents
  • ▸ Applied localization use cases with Claude Code
02 Session

Agent Workflows and Automation for Localization

  • ▸ Workflow orchestration fundamentals
  • ▸ Deterministic vs. agentic workflows
  • ▸ Multi-agent systems and architectures
  • ▸ Where agents fit into localization workflows
  • ▸ No-code ecosystem and implementation approaches
  • ▸ Adoption, governance, and limitations
  • ▸ Localization use cases and live demonstrations

Course Program

This course introduces localization professionals to AI agents and agentic workflows through practical localization scenarios and hands-on demonstrations.

Participants will learn the core concepts behind modern AI agents — the evolution from prompts to workflows to agents, memory, tools, MCP, planning, and evaluation — and how single agents, coding agents such as Claude Code, multi-agent systems, and no-code platforms can support localization QA, validation, reporting, and workflow automation. The course focuses on realistic localization examples designed for non-engineering audiences.

By the end of the course, participants will understand how AI agents and agentic workflows can support localization, how to orchestrate multi-agent and no-code workflows, and how to approach governance and adoption within their own teams.

01 Session

Core Concepts and Applied Use Cases

Block 1. From Prompts to Workflows to Agents

  • ▸ Introduction to agents
  • ▸ The evolution from prompts to workflows to agents
  • ▸ Workflow-based vs. agent-based systems
  • ▸ Deterministic workflows vs. agentic systems

Block 2. Anatomy of a Modern Agent

  • ▸ Core components of a modern agent
  • ▸ Memory and tools
  • ▸ MCP (Model Context Protocol)
  • ▸ Planning and evaluation

Block 3. Coding Agents and Localization

  • ▸ Claude Code: capabilities and limitations
  • ▸ Where agents fit into localization workflows
  • ▸ Applied localization use cases with Claude Code
  • ▸ Hands-on demonstration
02 Session

Agent Workflows and Automation for Localization

Block 4. Workflow Orchestration and Multi-Agent Systems

  • ▸ Workflow orchestration
  • ▸ Deterministic vs. agentic workflows
  • ▸ Multi-agent systems and architectures
  • ▸ Coordinating agents across localization tasks

Block 5. No-Code Ecosystem

  • ▸ No-code implementation approaches
  • ▸ No-code agent platforms and orchestration tools
  • ▸ Building practical localization workflows without code

Block 6. Adoption, Governance, and Use Cases

  • ▸ Adoption and governance
  • ▸ Limitations and risk management
  • ▸ Localization use cases and demonstrations

What You Will Learn

This practical course introduces AI agents as a new operational layer for localization workflows and automation. The course progresses from foundational concepts — the evolution from prompts to workflows to agents, and the anatomy of a modern agent — to applied multi-agent and no-code workflows.

✓

Understand the evolution from prompts to workflows to agents

✓

Distinguish deterministic workflows from agentic systems

✓

Learn the anatomy of a modern agent: memory, tools, planning, evaluation

✓

Master core concepts: MCP, memory, and tools

✓

Explore coding agents such as Claude Code and their localization use cases

✓

Understand workflow orchestration and multi-agent architectures

✓

Discover no-code implementation approaches for agents

✓

Address governance, adoption, and limitations

Practical Focus: This course avoids unnecessary engineering complexity and focuses on realistic scenarios that localization professionals encounter daily. From core concepts to multi-agent workflows to no-code automation, you will walk away with immediately applicable knowledge.

Who Is This For?

🧰

Localization Project Managers

Who want to automate repetitive operational tasks and QA workflows.

🤖

Localization Specialists

Interested in AI-assisted workflows without deep coding knowledge.

💻

Localization Engineers

Looking to accelerate scripting and repetitive operations using AI.

🌍

Freelance Professionals

Managing multilingual assets and file-heavy workflows.

🏢

LSP Professionals

Handling multilingual delivery pipelines and reporting.

🔍

Terminologists & QA Specialists

Working with structured localization content and quality validation.

⚙️

Operations Teams

Interested in workflow automation and process optimisation.

💬

AI-Curious Professionals

Anyone curious about how AI coding agents can support localization operations in practical ways.

If you work with localization content and want to understand how AI agents can reduce repetitive work, improve consistency, and support scalable operations — without needing to become a software engineer — this course is designed for you.

What You Will Need

📚

Requirements

  • ▸ Computer with stable internet connection
  • ▸ Claude subscription with Claude Code access
  • ▸ Visual Studio Code installed
  • ▸ Basic familiarity with localization workflows and file formats
  • ▸ Good level of English to follow live demos and explanations
  • ▸ Zoom installed
⏳

Format & Duration

  • ▸ 4 hours total (2 live sessions of 2 hours each)
  • ▸ Live online format with Q&A
  • ▸ Microphone and speakers/headset for participation
  • ▸ Webcam recommended but not mandatory

Recommended (optional)

  • ▸ Basic familiarity with JSON or localization file structures
  • ▸ Sample localization files for experimentation
  • ▸ GitHub account (optional)
  • ▸ Google Sheets or Excel access for reporting demos
  • ▸ Make account (optional, for automation demonstrations)

Andrés Romero Arcas

| Language Technology Expert
| Linguistic Engineer
| Machine Translation and AI Specialist at Acolad Group
About ANDRÉS
Andrés is a proficient language technology expert with over a decade of experience in the Localization Industry.
Throughout his career, he has held diverse roles, such as CAT Tool Specialist, Localization Engineer and Operations Technology Coordinator, where he led a team of localization engineers.
Currently at Acolad, Andrés focuses on machine translation evaluation and engine training. He is also deeply involved in prompt engineering and Generative AI, proposing AI-driven driven solutions to deliver tailored, customer-centric solutions and to tackle challenges in Production.
Andrés is passionate about automating and optimizing processes to enhance productivity and efficiency, improving quality and integrating innovation into localization workflows.