Agentic AI in 2026: From Pilot Programs to Production Reality
Gartner predicts 40% of enterprise apps will feature AI agents by 2026. Why 2025's pilots failed, what's different now, and how to build production-ready agentic systems.
Articles, tutorials, and thoughts on web development, tech, and building cool things.
Gartner predicts 40% of enterprise apps will feature AI agents by 2026. Why 2025's pilots failed, what's different now, and how to build production-ready agentic systems.
Why 'good enough' AI beats bleeding-edge for most use cases. The shift from AI hype to practical ROI, and what actually drives value in enterprise AI deployments.
Comprehensive comparison of the top AI coding assistants in 2026. Features, pricing, agent capabilities, and which tool is best for your workflow.
Hyperscalers will spend $602 billion on CapEx in 2026, with 75% for AI. Analysis of the power crisis, network design challenges, and the infrastructure defining AI's future.
Four frontier AI models launched in 25 days - Grok 4.1, Gemini 3, Claude Opus 4.5, and GPT-5.2. Analysis of capabilities, benchmarks, and what this unprecedented competition means for developers.
Apple delayed its LLM-powered Siri to spring 2026, but its cautious approach may pay off. Analysis of Apple Intelligence, on-device AI, and why restraint might be competitive advantage.
CES 2026 highlights from NVIDIA's Jensen Huang keynote, Hyundai's Atlas humanoid, and the explosion of AI-powered robotics. What developers need to know about embodied AI.
DeepSeek trained its V3 model for just $6 million vs $100M+ for GPT-4, then open-sourced it. How they achieved this efficiency despite US chip sanctions, and what it means for AI economics.
High-risk AI system rules take effect August 2, 2026. Practical compliance guide covering risk tiers, documentation requirements, and the proposed Digital Omnibus changes.
India AI Impact Summit 2026 brings Bill Gates, Dario Amodei, and 100+ global CEOs. Deep dive into BharatGen, the $240M IndiaAI Mission, and India's path to AI leadership.
Microsoft, Google, AWS, and Indian giants are investing $50B+ in Indian data centers. Analysis of the AI infrastructure buildout, power challenges, and opportunities.
How India's 1,700+ Global Capability Centers are transforming from back-office operations to strategic innovation hubs, with 30 billion-dollar GCCs expected by 2025 and a $90 billion market by 2028.
TCS, Infosys, and Wipro cut 25,000-30,000 jobs in 2025, but fresher hiring is returning. Analysis of the skill gap crisis, reskilling strategies, and the new IT career playbook.
Model Context Protocol went from Anthropic's November 2024 release to 97 million monthly SDK downloads and adoption by ChatGPT, Gemini, and VS Code. Technical deep-dive and getting started guide.
NVIDIA acquires Groq for $20 billion in its largest deal ever. Analysis of LPU vs GPU technology, what this means for AI inference, and the future of AI chip competition.
Linux Foundation and Meta report reveals 89% of organizations using AI leverage open-source models, with 25% higher ROI. Comparing Llama, Mistral, and DeepSeek for enterprise adoption.
A realistic assessment of India's position in the global AI and infrastructure race, examining data sovereignty, cloud dependency, and the path to tech independence.
Complete guide to FLUX AI image generation models - comparing FLUX.1 Pro, Dev, Schnell and the new FLUX.2 with multi-reference support and 32B parameters.
Analysis of AI's impact on India's IT industry: 80,000 job cuts, automation risks by segment, and strategic recommendations for professionals and companies.
100% of Claude Code's recent codebase was written by Claude Code itself. Industry leaders from Shopify to Google are stunned. Here's what's really happening—and why you might already be behind.
Discover how Meta's Vision-Language Joint Embedding Architecture (VLJA) is challenging the foundation of modern AI by predicting meaning instead of tokens, potentially ushering in a post-LLM era.
A comprehensive guide to Low-Rank Adaptation (LoRA) and Retrieval Augmented Generation (RAG) - two powerful approaches to enhancing large language models. Learn when to use each and how to combine them.