Blog

Explore the latest trends in AI application development, learn practical technical tutorials, and discover the latest features and success stories of the JitAI platform

Breakthrough in Software Development: From Programming to Orchestration

Over the past decades, development tools have continuously evolved in programming capabilities, yet orchestration abilities remain absent. Business systems comprise modules like portals, pages, components, models, and services—their organizational relationships determine architecture quality. Traditional tools lack visual orchestration support, hiding system structures within code and making maintenance difficult. Software development is undergoing a shift from programming-centric to balanced programming and orchestration, where orchestration-oriented architectures, frameworks, and tools deliver both improved development efficiency and sustained architectural elegance.

9 hours ago

On-Premises vs. Public Cloud: Why Private Infrastructure Wins

The public cloud SaaS era promised convenience, but at what cost? Modern deployment technology has flipped the equation. On-premises infrastructure now offers superior data sovereignty, lower TCO, and freedom from vendor lock-in—without the operational complexity. It's time enterprises reconsidered the on-premises advantage.

9 hours ago

Mission-Critical Systems: Why Lightweight Platforms Like Coze/n8n Fall Short

Enterprises need systems that deliver fast, customize rapidly, and evolve with business needs. However, lightweight apps built on database-UI paradigms (like Notion, Airtable) and AI applications deployed in isolation from business systems (like Coze, Dify, n8n) are products of short-termism that fail to gain traction in large enterprises.

1 day ago

Forward Deployed Engineers: The Bridge Between AI Innovation and Real-World Enterprise Solutions

Discover the role of Forward Deployed Engineers (FDEs) in AI enterprise transformation. Learn how low-code platforms like JitAI empower AI-powered automation at scale.

2 days ago

What Is the Ultimate Vision of Low-Code/Visual Development?

Traditional low-code/visual development platforms rely on black-box rule engines, fundamentally limiting application extensibility. They sacrifice expressive power for simplicity, inevitably failing in complex enterprise scenarios. True visual development shouldn't constrain capabilities—it should enable developers to orchestrate system modules and technical capabilities visually, transitioning from closed DSL (Domain Specific Language) engines to open orchestration protocols, from limited expression to unlimited integration.

2 days ago

JitAi's Distinct AI Coding Paradigm Contrasted with Cursor

Discover how JitAi's innovative AI coding approach addresses the key limitations of tools like Cursor through high accuracy, low barrier to entry, and cost efficiency for enterprise business application development.

3 days ago

Why Isn't AI Scaling in Enterprises?

Production-grade AI applications face inherent complexity. Unlike traditional enterprise apps that record transactions, AI apps execute tasks—requiring deep integration with unique business processes and knowledge systems. While custom development is inevitable, it remains costly and ineffective. Traditional paradigms fall short; the market urgently needs AI-native engineering practices and methodologies.

3 days ago

What is AI Native Application Architecture?

AI-native application architecture must address not only how AI modules are designed and integrated, but also how traditional technical modules are perceived, driven, and orchestrated by AI. Attempting to integrate AI capabilities into legacy event-driven architectures is like putting an internal combustion engine on a horse cart—foolish and inefficient. Traditional enterprise applications like ERP, CRM, and OA systems will inevitably be reshaped by new AI-native architectures and development paradigms.

4 days ago

What is Production-Grade AI Application?

The industry is exploring how to deploy enterprise AI applications, but many attempts have gone astray. Inability to make partial adjustments to outputs, deployment isolated from business systems, standalone UIs that can't collaborate with humans, and claims of being universal products—none of these represent what production-grade AI applications should be.

5 days ago

What is MCP? The Seamless Connection Revolution Between AI and Development Tools

In today's rapidly evolving AI landscape, Large Language Models demonstrate impressive capabilities, yet they often operate as isolated "intelligent islands," unable to directly access our file systems, databases, or API services. This is the core problem that the Model Context Protocol aims to solve.

1 week ago