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Arjun Mehta

Developer Advocate & Technical Writer

Arjun Mehta is a developer advocate and technical writer who specialises in making complex AI concepts accessible to working developers. He has spent the last five years building and documenting integrations between AI tools and enterprise software stacks.

His background in enterprise SaaS gives him a unique perspective on what developers actually need when adopting AI tools — not theoretical introductions, but concrete walkthroughs with real error handling, cost estimates, and deployment considerations.

At AI Agents Directory, Arjun covers AI tools, tutorials, and industry news. His articles consistently focus on practical applicability: what you can build today, with what tools, and at what cost.

AI Tools Tutorials Industry News No-Code AI Workflow Automation

Articles by Arjun Mehta (75 total)

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Industry News

Accelerating AI Deployment: The Practical Edge of Transfer Learning

The ambition to deploy highly capable AI models often confronts the stark reality of computational demands. Training a state-of-the-art large language model like OpenAI's GPT-4 can consume millions of

Arjun · May 28, 2026 · 14 min read
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AI Tools

Architecting Adaptive Learning Systems with AI Agents for Personalized Education

The promise of personalized education, tailored precisely to an individual's learning pace, style, and prior knowledge, has long been a pedagogical ideal.

Arjun · May 28, 2026 · 14 min read
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Tutorials

Integrating AI into Applications: A Deep Dive into Microsoft Semantic Kernel

The integration of artificial intelligence into enterprise applications is no longer an aspiration but a strategic imperative.

Arjun · May 28, 2026 · 14 min read
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Industry News

Intelligent Automation: Streamlining Repetitive Tasks with AI Agents

Repetitive, high-volume tasks are a pervasive drain on productivity across nearly every industry, from customer service to financial operations.

Arjun · May 28, 2026 · 13 min read
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Tutorials

Mastering LLM Reinforcement Learning from Human Feedback (RLHF) for Agent Development

The promise of truly intelligent AI agents hinges not just on their raw capabilities, but on their ability to understand and align with human intentions, preferences, and ethical boundaries.

Arjun · May 28, 2026 · 15 min read
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AI Tools

Scaling Python for AI: A Developer's Guide to Dask Parallel Computing

Modern AI initiatives frequently encounter a significant bottleneck: the sheer volume of data involved.

Arjun · May 28, 2026 · 14 min read
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AI Tools

AI Agents for Predictive Database Performance Tuning

Database performance issues can cripple applications, leading to sluggish user experiences and significant operational costs. For instance, a major e-commerce platform recently reported a 15% drop in

Arjun · May 26, 2026 · 13 min read
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AI Tools

Architecting Robust RAG Systems for Enterprise Knowledge Bases

Enterprise knowledge bases, often vast and disparate, present a significant challenge for traditional search and information retrieval systems.

Arjun · May 26, 2026 · 16 min read
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AI Tools

Chroma Vs Qdrant: A Vector Database Showdown for AI Engineers

As AI agents grow in complexity, their ability to remember and contextualize information becomes paramount.

Arjun · May 26, 2026 · 11 min read
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Tutorials

Understanding the Trajectory: Current Progress Towards Artificial General Intelligence (AGI)

The quest for Artificial General Intelligence (AGI) represents the pinnacle of AI research: creating machines capable of understanding, learning, and applying intelligence across a wide range of tasks

Arjun · May 26, 2026 · 11 min read
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AI Tools

Architecting Intelligent Systems: A Deep Dive into Vector Databases for AI Applications

Large Language Models (LLMs) like OpenAI's GPT-4 and Anthropic's Claude 3 have redefined what's possible in AI, yet their inherent knowledge cutoff and hallucination tendencies present significant cha

Arjun · May 24, 2026 · 13 min read
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AI Tools

Building Intelligent Agents for Sports Performance Analytics: A Deep Dive for Engineers

The pursuit of peak human performance in sports has always been a complex challenge, with marginal gains often making the difference between victory and defeat. Traditional performance analysis relies

Arjun · May 24, 2026 · 13 min read