The NxtFruit blog
AI Development
Articles from the NxtFruit team on this topic.
AI Development
When AI Coding Agents Skip Their Own Tests
A viral engineering essay reminded us how easily an AI coding agent can "pass" a test by skipping it. We audited our own platform, found the gap, and fixed it.
· 7 min read
AI Development
Agentic Workflow Platform vs. Autonomous Code Generation
Dify is a strong agentic workflow platform — but it solves a different problem than autonomous code generation. Here's how we evaluated both and how to choose.
· 5 min read
AI Development
AI Coding Token Costs: Why Cutting Tokens Can Cost You Quality
Token-reduction tools promise 60–90% fewer tokens on AI coding, but cutting tokens isn't the same as saving money. Here's why signal per token — not raw token count — is the metric that actually protects quality.
· 7 min read
AI Development
Can AI-Generated Code Leak Your Secrets? The Fail-Open Gap We Found
Our AI development platform once pushed a live API key - despite having a secret scanner. The fail-open gap we found, and the fail-closed fix any AI pipeline can copy.
· 7 min read
AI Development
Multi-Agent AI: How Super-Agent Systems Actually Work
Multi-agent AI systems split work across a lead and sub-agents with isolated context. We build software this way — here's how super-agent harnesses really work and where the design choices matter.
· 5 min read
AI Development
Real-Time RAG: Keeping Your AI’s Knowledge Current
Real-time RAG keeps an AI's knowledge current by indexing changes as they happen. We evaluated live-data indexing, hybrid retrieval, and reranking against how we build it.
· 5 min read