Replaced a vendor translation contract with a GitHub Actions and OpenAI pipeline in 6 weeks.
Translation was a recurring vendor line item with multi-week turnaround that slowed every release. Cost scaled with the number of locales and strings. Product waited on an external gatekeeper for every new string.
I designed and shipped a pipeline on GitHub Actions and the OpenAI API: locale-specific prompts, glossary enforcement, and automated evaluation against the old vendor output. It hooks into the PR flow, so new strings translate on merge. Shipped in 6 weeks. Over 12,000 key-value pairs translated since January 2024 with negligible regression.
The eval harness sold the project, not the model. I compared LLM output with vendor output on real strings before I asked anyone to switch. Quality held, turnaround dropped from weeks to a PR, and the pipeline paid for itself many times over.
Forward deployed engineer is the hottest title in AI. If you want it, aim at the part that never goes stale: owning the outcome. Advice for aspiring FDEs from someone about to wear the badge.
A map of the 12 memory and RAG tools building the AI brain layer. Why temporal knowledge graphs beat vector-only RAG, and how to pick the right stack for your agents in production.
Towards AI A rep told me I had built half the product. So the agent now drafts the full 10-touch sequence and drops it into Outreach, ready for the rep to review and send. Nothing goes out on its own.