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As generative AI models grow their context windows, a hidden problem emerges: more information often leads to worse answers. Known as context rot, this phenomenon reveals a U-shaped performance curve where accuracy peaks at moderate context sizes, then degrades as signal is buried in noise. Bigger memory doesn’t guarantee better reasoning—effective context does.

Is your AI chatbot a sleek machine or a Frankenstein monster? Too many RAG pipelines are built on "vibes," stitching together complex features without proof they actually work. It’s time to replace the guesswork with science. Learn how to forge a "Golden Dataset," deploy LLM-as-a-Judge metrics, and ruthlessly prune your bloated architecture. Stop engineering monsters and start building lean, accurate systems backed by hard data.

raditional JSON tool calling is fragile. "Code Mode" changes the game: convert MCP tools to TypeScript APIs and let AI agents write executable code. It’s faster, handles complex logic, and uses secure sandboxes. Get the full code demo here.

Is JSON bloating your LLM costs? Discover TOON (Token-Oriented Object Notation), the high-efficiency alternative designed specifically for Generative AI. By decoupling schema from data, TOON can slash token usage by nearly 50% compared to standard JSON. Perfect for RAG pipelines, lowering API latency, and maximizing context windows. Check out our head-to-head code benchmark to see exactly how much syntax overhead you can eliminate today.

Nano Banana brings precision, speed, and coherence to AI image editing like never before. Its power lies in natural-language edits—one-shot, context-aware, and visually consistent. Though still experimental, platforms like LMArena and FluxProWeb offer rare glimpses. For now, creators and AI watchers alike are eagerly following every update and sharing discoveries as they emerge.

Agriculture Meets AI: Precision Crop Planning and Sustainable Farming Using GenAI

dots.ocr: A compact 1.7B AI model transforming multilingual document scanning into lightning-fast accuracy.

GPT-5 marks a transformative leap in AI, delivering unmatched reasoning, speed, and scalability. With up to 400K context tokens, adaptive routing between fast and deep-thinking models, and improved developer controls, it redefines what’s possible in large language model applications. From enterprise-scale analytics to intelligent agents, GPT-5 is engineered for context-rich, reasoning-heavy solutions of the future.

OpenAI’s Model Spec, first released in May 2024, sets out a three-tier framework for guiding how AI assistants like ChatGPT should behave.Published in May 2024, the Spec introduced a three-layer hierarchy: Objectives, Rules, and Defaults .

GenAI is reshaping CRM by enabling personalized, proactive, and scalable customer experiences across industries.

Letta's new .af format standardizes AI agent portability, memory, and sharing—powering the next-gen agent ecosystem.

Explore the rise of language models from GPT-2 to GPT-4 and their game-changing impact on AI and industry.

1. What is Agent File (.af)? The Agent File (.af)  is a new file format designed to store, share, and reproduce AI agents  — especially...