Bella Christine

most of the conversation around AI agents is about what they can do. faster, smarter, more autonomous. but i've been thinking about the other side of that question.

when you're building with agents, at some point you have to draw a line. this agent can read but not write. it can suggest but not send. it can book but not pay. somewhere, someone made that call.

Glossaries, rulesets, and brand voices now live at the organization level and attach to any engine.

Build a glossary, a ruleset of linguistic rules, or a brand voice once, then attach it to any engine that needs it. Edit a shared asset and every engine it's attached to picks up the change. A new engine no longer starts from an empty configuration: attach what you already have and it inherits it.

Also this week:

• Take over a translation waiting on external review. When a job is parked on an external professional reviewer, an authorized member of your own team can open the pending review in the dashboard and submit the decision, so the job continues instead of waiting on the external round trip.

• A runnable example repo for every framework. Each is a real project with .lingo/config.json and translations committed clone it, run lingo link, and push: iOS, Android, Flutter, React + Vite, Next.js, Rails, Laravel, Markdown, Markdoc, OpenAPI, and TypeScript modules.

In this time when we use LLM's for basically anything, what AI agents/tools would you want that you would actually pay for?
What are you spending a lot of money on and would probably save a lot of you time if you got the Agent out of box, or if configuration was much easier?