Master Context Engineering!! : Let’s Talk Prompting and DSPy
Author(s): Gaurav Shrivastav Originally published on Towards AI. Let’s learn context engineering in this course!! So, Large Language Models (LLMs) are everywhere. We all know it. But actually building something useful and reliable with them? That’s a whole different story. It often …
TAI #170: Why Are So Many of the AI Success Stories AI for Coding?
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, OpenAI released a significant upgrade to its coding platform with GPT-5-Codex, a specialized version of GPT-5 fine-tuned for agentic software engineering. This …
AutoGen vs CrewAI: Two Approaches to Multi-Agent Orchestration
Author(s): Neha Manna Originally published on Towards AI. Table of Contents Overview AutoGen2.1 History & Evolution2.2 Why AutoGen Matters2.3 How AutoGen Works2.4 AutoGen Examples2.5 Architecture (v0.4) with analogies CrewAI3.1 History & Evolution3.2 Why CrewAI3.3 How CrewAI Operates3.4 CrewAI Examples3.5 Architecture with analogies …
Can Recursion Make LLMs Smarter and More Efficient?
Author(s): Arthur Lagacherie Originally published on Towards AI. Recursion could reshape how LLMs scale. A major problem with current LLM architectures is the difficulty of adapting their computational power to match the performance requirements of specific tasks (low performance requirements should use …
15 n8n Workflows Every Lazy SEO Needs
Author(s): Shauvik Kumar Originally published on Towards AI. “Don’t be a robot. Build the robot.” — Wade Foster You’re not alone. Most digital marketers want results, not hours spent in spreadsheets or dashboards. 15 n8n Workflows Every Lazy SEO NeedsThis article presents …
Unlock True AI Understanding: Beyond RAG with Knowledge-Augmented Generation (KAG)
Author(s): Sai Bhargav Rallapalli Originally published on Towards AI. Tired of AI Hallucinations? Discover How KAG Delivers Professional-Grade Accuracy for Your Domain. In the rapidly evolving world of AI, we’re constantly seeking ways to make our systems smarter, more reliable, and truly …
Review of Multimodal Technologies: ViT Series (ViT, Pix2Struct, FlexiViT, NaViT)
Author(s): tangbasky Originally published on Towards AI. In the computer vision domain, CNNs have long been the dominant framework for understanding visual features. In contrast, the transformer framework has achieved great success in the NLP domain, which has encouraged some researchers to …
5 Tool Design Secrets That AI Agents Actually Love
Author(s): Richard Warepam Originally published on Towards AI. LLMs don’t need more tools — they need smarter ones. Here’s how to build ergonomic tools that boost clarity, save tokens, and keep your agents sharp. If you are not a member, read the …
Building Advanced RAG Pipelines with Neo4j and LangChain: A Complete Guide to Knowledge Graph-Powered AI
Author(s): GenAI Lab Originally published on Towards AI. Learn how to combine Neo4j knowledge graphs with LangChain to build accurate, explainable, and production-ready Retrieval-Augmented Generation (RAG) systems. Retrieval-Augmented Generation (RAG) has quickly become the go-to architecture for making Large Language Models (LLMs) …
Stop Chasing Perfect Prompts. Build Context Systems That Actually Scale.
Author(s): Mayank Bohra Originally published on Towards AI. Stop Chasing Perfect Prompts. Build Context Systems That Actually Scale. Everyone’s obsessed with prompt engineering templates and formulas. But after 1–2 months building systematic AI workflows that generate authentic content across blogs, emails, and …
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