🧠 Beyond the Spreadsheet: How I Built My Translator’s Second Brain in Notion

As a translator, my life revolves around words. But for years, the words that defined my work were a chaotic mess. I’m talking about my glossaries. I started with Word documents, which quickly became unwieldy. I graduated to Excel spreadsheets, which were better for sorting but felt lifeless and disconnected. They were just lists, that is, static, devoid of context, and a pain to maintain.

I knew there had to be a better way. I needed a tool that was as dynamic and interconnected as language itself. That’s when I found Notion. And let me be clear: using Notion to manage my terminology wasn't just an upgrade; it was a complete paradigm shift. I stopped just listing terms and started building a true “second brain”, that is, a living, breathing ecosystem for my linguistic knowledge.

Today, I want to show you exactly how I did it, and how you can too. If you're a translator or terminologist tired of wrestling with outdated tools, this guide is for you.

Why Your Excel Glossary is Holding You Back

For a long time, I thought a simple two-column spreadsheet was enough. Source term, target term. Done. But I was wrong. That system fails to capture the most critical element in translation: context.

• Where did this term come from?
• Is it formal or informal?
• What are some real-world examples of its use?
• How does it relate to other terms in the project?

A spreadsheet can't answer these questions effectively. It's a flat world. Notion, on the other hand, is three-dimensional. As noted in a guide on Notion for Translators, its power lies in its database functionality, which allows you to create a truly customized and interconnected workspace.

The Foundation: Building Your Glossary Database

The heart of this system is a Notion database. Think of it as a spreadsheet on steroids. Each entry isn't just a row; it's its own full-fledged page, ready to be filled with rich context.

Here’s how I set up my bilingual Ukrainian-English glossary, step-by-step.

1. Create the Database:

First, I create a new page in Notion and choose the Database - Full Page option. I call it “Ukrainian-English Glossary.”

2. Set Up the Properties (The Columns):

This is where the magic begins. Properties are the data fields for each term. I go beyond just “source” and “target” to capture a 360-degree view of every entry.

• Ukrainian Term (Property Type: Title): This is the main field for my source term.
• English Translation (Property Type: Text): The corresponding target term.
• Status (Property Type: Select): This is crucial for my workflow. I create options like “New,” “In Review,” and “Verified.” It lets me see the state of my terminology at a glance.
• Category (Property Type: Multi-select): I work across different domains, so I add tags like “Legal,” “IT,” “Medical,” and “General.” This allows me to filter my glossary for specific projects instantly.
• Related Terms (Property Type: Relation): This is the superstar property. It lets me link glossary entries to each other. For example, I can link the term “місто Київ” (city of Kyiv) directly to the page for “Київська область” (Kyiv region). This creates a web of knowledge, not just a list.
• Date Created (Property Type: Created time): This is automatic. It tells me when I first added the term.
• Last Updated (Property Type: Last edited time): This is my favorite property. It automatically updates whenever I make a change. It proves my glossary is a living document and helps me identify which terms might need a review.

My basic database structure now looks clean, powerful, and ready for action.

The Ultimate Time-Saver: The Glossary Template

I don't want to manually add the same structural elements every time I create a new entry. This is where Notion's templates come in. I created a template that pre-populates the body of every new glossary page, ensuring consistency and prompting me to add the right information.

Here’s how I built my “New Glossary Term” template:

1. Next to the blue “New” button in my database, I click the dropdown arrow and select + New template.
2. I design the page body with the following sections:

Context & Usage Notes

Here, I prompt myself to add notes on tone, register, and when to use (or not use) the term. E.g., "Formal term used in legal contracts. Avoid in casual conversation."

Examples in Sentences

Ukrainian Example:

[I leave a space to paste a source sentence.]

English Translation:

[I leave a space for the corresponding translation.]

Quality Checklist

• [ ] Terminology verified against official sources.
• [ ] Translation aligns with the Style Guide.
• [ ] Checked for related terms and linked if necessary.

---

Remember to consult the main @Translation Style Guide

The final step is to set this template as the default. Now, every time I click “New,” this entire structure appears instantly. It's a simple feature that has a massive impact on my efficiency and the quality of my work.

Best Practices for a Thriving Glossary

Building the structure is just the beginning. Maintaining a glossary is an ongoing process, and Notion's features encourage best practices that keep it valuable.

1. Make it a Living Document: I regularly sort my glossary by the “Last Updated” date to see which terms are getting stale. I schedule a quarterly review to go through terms that haven't been touched in six months.
2. Context is King: I force myself to fill out the template for every single term. The “Examples in Sentences” section is non-negotiable. A term without an example is only half-defined.
3. Create a Style Guide: I have a separate page in Notion called “Translation Style Guide” where I outline rules on tone, formatting, and handling proper nouns. I use the @ symbol to link to it from my glossary template, so my rules are always just one click away.
4. Embrace the Web of Knowledge: I actively use the Relation property. Building connections between terms has been a game-changer, helping me understand and explain the subtle relationships between words.

Your Turn to Build Your Second Brain

Switching to Notion has transformed my glossary from a simple reference list into the central hub of my professional knowledge. It's a tool that saves me time, improves my consistency, and ultimately makes me a better translator.

If you're ready to move beyond the limitations of spreadsheets, I encourage you to give this a try. Start small. Don't try to import your entire life's work at once. Begin with your very next project and add terms as you go. You'll quickly see how a well-structured glossary in Notion can become one of the most valuable assets in your translation business.

How Translators Can Integrate AI Tools

Leveraging the Machine: How Translators Can Strategically Integrate AI Tools

Let's be honest: the buzz around Artificial Intelligence (AI) and Machine Translation (MT) in our industry can feel overwhelming. We hear everything from pie-in-the-sky promises to dire warnings about the future of our profession. As a working translator, figuring out where you stand amidst all this noise can be confusing, maybe even a bit unsettling. Is this tech a partner, a rival, or just the next tool in our ever-evolving kit?

The truth, as usual, isn't black and white. While AI certainly won't replicate the deep understanding, cultural sensitivity, and critical judgment a skilled human brings to the table (at least not anytime soon!), simply ignoring its potential wouldn't be smart either. These AI-powered tools, especially MT, can be incredibly useful if we approach them strategically. It’s not about blindly trusting the machine or rejecting it outright; it's about learning how to make it work for us. So, let's dig into some practical ways translators are actually using these tools right now to work smarter, not just harder.

 

The Main Player: Getting Friendly with Post-Editing (MTPE)

Machine Translation Post-Editing (MTPE) is probably the most common way translators interact with AI today. Instead of translating everything from scratch, you start with the machine's output and refine it. This isn't just copy-editing, though. It demands your full linguistic expertise to fix errors, smooth out awkward phrasing, guarantee accuracy, and make sure the text truly speaks to the intended audience in the right way.

Think of MTPE as a spectrum. On one end, you have Light Post-Editing (LPE), where the main goal is just to make the text understandable and accurate – perfect for internal memos or getting the basic gist. Style isn't the top priority here. On the other end is Full Post-Editing (FPE), which aims for quality that's indistinguishable from a top-notch human translation. This means diving deep into accuracy, terminology, grammar, style, and cultural nuances. It takes real effort and skill, sometimes nearly as much time as translating from scratch, but for certain kinds of text, it can still offer a speed advantage.

Whether MTPE makes sense really depends on the project: things like highly structured technical manuals often work well, while more creative texts usually don't. The quality of the MT engine itself, the language pair, and what the client actually needs are all big factors. Honing your post-editing skills – spotting common MT mistakes, fixing them efficiently, and crucially, knowing when the MT output is just not good enough to use – is definitely becoming a smart career move.

Working Smarter: Terminology and Quality Checks 

AI's usefulness doesn't stop at generating draft translations. It can also help streamline some of those time-consuming related tasks:

Managing Terminology: Need to build a glossary or ensure consistency? AI tools can help by suggesting potential terms pulled from source texts or translation memories. You still need to validate them, of course, but it can speed up the initial legwork. Many CAT tools now integrate features that automatically flag or suggest terms from your TMs or termbases, cutting down on manual lookups.
Automated Quality Assurance (QA): Forget basic spell-check. Modern QA tools, often built right into CAT environments, use AI to spot trickier issues. They can flag inconsistent terminology or numbers, check if you're following a specific style guide, find segments that might have been missed, and even perform sophisticated grammar checks. This acts like a second pair of eyes, catching potential slip-ups early and letting you focus your final review on the subtleties that really matter. 

Quick Understanding: Gisting and Research 

Ever need to quickly figure out what a document is about, maybe for a quote or some initial research, but it's in a language you don't speak fluently? MT is fantastic for this. You'd never deliver raw MT to a client, obviously, but using it to get a fast overview of source files, project briefs, or reference materials can be a major time-saver. It’s especially handy when you're faced with huge amounts of text or an unfamiliar subject area and just need a starting point.

Handling the Load: Boosting Productivity on Repetitive Content

For certain projects – think repetitive technical manuals, endless software updates, or internal documents where speed trumps stylistic perfection – weaving MT into your workflow (usually through MTPE) can genuinely make you more productive. The machine can churn through the predictable sentences or segments that closely match previous translations, leaving you more time and energy for the new, complex, or creatively demanding parts. Tools like Adaptive MT, which learn from your edits as you work within your CAT tool, take this a step further by gradually tailoring their suggestions to your style and the project's needs.

 

Hold On Though: The Human Factor is Still Crucial

Using these tools effectively means keeping a critical eye:

Your Expertise is Irreplaceable: Let's be crystal clear: AI is a tool. Your judgment on accuracy, tone, cultural appropriateness, and style is what clients pay for. Relying blindly on MT is a recipe for poor quality and potential embarrassment.
Know Its Limits: MT is notoriously bad with humor, poetry, clever wordplay, ambiguity, slang, and deeply embedded cultural references. Knowing when not to use MT is just as vital as knowing how to use it.
Guard That Data: Be incredibly careful about confidentiality, especially with free online MT platforms. Never paste sensitive client information into tools unless you're certain they are secure and covered by your agreements. Often, this means using enterprise-level or private, custom-trained systems.
Talk to Your Clients: Honesty is the best policy. Discuss your use of AI tools, especially MTPE, upfront. Set clear expectations about the process and agree on the quality standards required.
Choose Wisely: MT engines aren't all the same. Performance can vary wildly depending on the language pair, subject matter, and whether it's a generic engine or one trained on specific data. Test and choose the right tool for the job.

Wrapping Up: The Translator, Amplified

Ultimately, this isn't about “human vs. machine.” It's about “human with machine.” AI and MT offer powerful assistance that, when used thoughtfully by skilled professionals like you, can help us work more efficiently, keep consistency tight, and free us up to focus on the truly complex, high-value parts of our job: deep linguistic insight, cultural bridging, subject expertise, and crafting words that truly connect.

By learning to integrate these technologies smartly and critically, we're not just adapting to change; we're enhancing our own capabilities. We're solidifying our role as indispensable language experts in a world that needs clear communication more than ever. The future likely belongs to translators who learn to work with the machine, harnessing its power without losing sight of their own essential craft.

Stop Paying for Empty Promises: Why Mass CV Mailings Don't Work for Translators

Andrey Yasharov · Paying Someone to Spam Translation Agencies

Are You Paying Someone to Spam Translation Agencies?

There seems to be a cottage industry popping up that offers to blast translator CVs out to translation agencies, promising exposure and job opportunities. We're seeing the receiving end of this: daily floods of unsolicited resumes hitting our inbox, often appearing to be scraped from freelancer platforms like Proz. Let's be crystal clear: these emails go straight to the trash, unread.

If you're a translator considering paying for such a service, or if you know someone who is, let me offer a blunt piece of advice: save your money. You're likely paying someone to annoy potential clients on your behalf.

Think about it from the agency's perspective. Reputable agencies have established recruitment processes. We look for specific skills, language pairs, and specializations for particular projects. We might post targeted calls for linguists, search our internal databases of vetted professionals, or actively scout talent based on known expertise and referrals. What we don't do is wade through a daily deluge of generic, unsolicited applications sent en masse. It's inefficient, impractical, and frankly, irritating.

The fact that these services seem to be harvesting contact information, potentially from platforms where translators list their profiles, adds another layer of concern. It's unclear if this operates within the terms of service of those platforms, but the result is noise, not opportunity. It clogs inboxes and wastes the time of agency staff who have to delete these messages.

More importantly, it's a disservice to the translators who pay for this. It creates a false sense of proactive marketing while achieving the opposite – associating their name with spam. It’s hard enough to stand out in the competitive translation market; the last thing you need is for your introduction to a potential client to be an unwelcome, impersonal email blast.

So, what does work?

• Targeted Applications: Research agencies that align with your specializations and language pairs. Address your application to the specific vendor manager if possible. Tailor your CV and cover letter to their needs.
• Networking: Engage in industry forums (constructively!), attend (virtual or physical) conferences, and build genuine connections.
• Platform Profiles: Maintain a professional, detailed, and up-to-date profile on reputable platforms like Proz, LinkedIn, etc. Agencies do search these platforms, but they're looking for specific qualifications, not waiting for a bulk email drop.
• Direct Outreach (Personalized): If you identify an agency you genuinely want to work with, a polite, personalized email introducing yourself and explaining why you are a good fit for them is far more effective than being part of a mass mailing.

The bottom line is that shortcuts rarely work in building a sustainable freelance career. Paying someone to spam agencies with your CV is not just ineffective; it's likely counterproductive. Focus on targeted, professional outreach and building a strong reputation. Don't let anyone convince you to pay for a service that ultimately sends your credentials straight to the digital recycling bin.