EXPERT COURSE

AI Agents for Localization

From Prompts to Workflows to Agents

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.

Localization Workflows Are Full of Automation Opportunities

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 operational resources. This creates a major opportunity for agentic automation. Many repetitive localization 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.

Practical Agentic Automation for Real Localization Teams

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.


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.

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  • 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: 10 h (approximately)
  •  When: 23-27 November 2026 (18.00 CET)
Course created in collaboration with:

Free for Crowdin Enterprise Users

AI agents for localization - FROM PROMPTS TO WORKFLOWS TO AGENTS

Learn how AI agents automate localization tasks, from MCP, memory and tools to Claude Code, multi-agent systems and no-code orchestration.

Session Breakdown

1 Session

Foundations: From Prompts to Agents

2 hours
  • ▸ Introduction to agents and the evolution from prompts to workflows to agents
  • ▸ Workflow-based vs. agent-based and deterministic vs. agentic systems
  • ▸ Where agents fit into localization workflows
2 Session

Anatomy of a Modern Agent

2 hours
  • ▸ Core components of a modern agent
  • ▸ Memory (short-term and long-term), tools, and MCP (Model Context Protocol)
  • ▸ Planning and evaluation in agentic systems
3 Session

Coding Agents: Claude Code for Localization (I)

2 hours
  • ▸ Claude Code capabilities and limitations for localization
  • ▸ Setting up Claude Code with Visual Studio Code
  • ▸ Applied use case: batch file validation and placeholder QA
  • ▸ Applied use case: terminology and glossary consistency checks
4 Session

Coding Agents: Claude Code for Localization (II)

2 hours
  • ▸ Applied use case: format and encoding conversion (XLIFF, JSON, CSV, PO)
  • ▸ Applied use case: tag and markup integrity validation
  • ▸ Applied use case: pseudo-localisation, string-length checks, and automated QA reports
5 Session

Multi-Agent Workflows, No-Code and Governance

2 hours
  • ▸ Workflow orchestration and multi-agent architectures
  • ▸ No-code platforms for localization: Make and Flowsie
  • ▸ Adoption, governance, limitations, and building a practical pathway for your team

Course Description

What Is This Course About

This practical course introduces AI agents as a new operational layer for localization workflows and automation. Participants will learn how AI agents - from coding agents such as Claude Code to no-code agent platforms - can support localization work through practical demonstrations focused on core concepts, agentic workflows, multi-agent systems, QA, validation, and orchestration.

The course avoids unnecessary engineering complexity and focuses on realistic scenarios that localization professionals encounter daily. It progresses from foundational concepts to applied multi-agent and no-code workflows.

Topics Covered

▸ The evolution from prompts to workflows to agents
▸ Deterministic workflows vs. agentic systems
▸ Anatomy of a modern agent: memory, tools, planning, evaluation
▸ Core concepts: MCP, memory, and tools
▸ Coding agents such as Claude Code and their localization use cases
▸ Workflow orchestration and multi-agent architectures
▸ No-code implementation approaches for agents
▸ Governance, adoption, and limitations
▸ Applied localization use cases and demonstrations

Course Format

Five live sessions of 2 hours each (10 hours total), one session per day from Monday to Friday. Each session includes hands-on demonstrations and live Q&A.

By the end of this course, participants will understand how AI agents can support localization workflows and be able to identify opportunities for agentic automation in their own teams.

Who Is This For

👨‍💻

Localization PMs

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 Operations Teams

Handling multilingual delivery pipelines and reporting.

🔍

Terminologists & QA

QA specialists working with structured localization content and quality checks.

Note: This course is for anyone curious about how AI coding agents can support localization operations in practical ways - no software engineering background required.

What You Will Learn

✓

Understand the evolution from prompts to workflows to agents

✓

Distinguish deterministic workflows from agentic systems

✓

Master core components of modern AI agents: memory, tools, MCP, planning & evaluation

✓

Understand where AI agents fit into localization workflows

✓

Explore Claude Code capabilities and limitations for localization

✓

Build multi-agent systems and no-code agent workflows

✓

Apply workflow orchestration and multi-agent architectures

✓

Understand governance, adoption strategies, and limitations of AI agents

Requirements & Setup

Essential 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 (latest version recommended)

Recommended (Optional)

  • ▸ Basic familiarity with JSON or localization file structures
  • ▸ Sample localization files for experimentation after the course
  • ▸ GitHub account (optional)
  • ▸ Make account (optional, for automation demonstrations)

Tip: No software engineering background is required. The course is designed for localization professionals who want to understand AI agents through practical demonstrations and beginner-friendly examples.

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.