Production-tested patterns, product stories from Blink AI, Nexia Academy and Wallnetic, and the trade-offs we hit shipping real software. Written by senior engineers, not marketing.
How to abstract LLM providers behind a single interface, the differences that bite at production scale, and what we learned switching Blink AI between Claude and GPT.
SCORM 2004, xAPI and cmi5 compared for 2026: tracking capabilities, LMS support, mobile, and production gotchas from a senior engineering team running Nexia Academy.
The engineering story behind Nexia Academy — moving from single-tenant to multi-tenant, white-label theming, SCORM/xAPI ingestion at scale, and what we would do differently starting over.
A practical comparison of Articulate Storyline 360, Adobe Captivate and Articulate Rise — when each is the right tool, where they hide costs, and how their SCORM/xAPI output differs.
Why hallucinations in corporate training products are worse than in consumer chatbots, and the specific guardrails we put in place across Blink AI and Nexia Academy to catch them.
How to ship multi-language e-learning content cleanly — packaging strategies, manifest design, content-author workflow, and the gotchas that show up when SCORM meets i18n.
The system architecture behind Blink AI — prompt orchestration, session state, memory isolation, evaluation pipeline and how the GROW methodology maps to a production AI service.
A practical engineering checklist for shipping SaaS that meets both Turkey’s KVKK and the EU’s GDPR — data flows, consent, retention, subject access requests and the differences that matter in code.
Why Blink AI uses Socratic questioning instead of advice generation — how we built prompts that guide users to their own insights, the failure modes we hit, and what the GROW methodology adds.
Six failure modes we hit running RAG in production — chunking gone wrong, embedding drift, retrieval recall, prompt bloat, hallucination on missing context, and how to detect them before users do.
