Prompt Repetition: The Overlooked Hack for Better LLM Results
Have you ever asked an LLM a question, changed the wording a few times, and still felt the answer wasn’t quite right? If you’ve worked with tools like ChatGPT or Gemini, you’ve probably rewritten prompts, added more context, or used phrases like “be concise” or “think step by step” to improve result...
The Reality of Vibe Coding: AI Agents and the Security Debt Crisis
Why optimizing for speed over safety is leaving applications vulnerable, and how to fix it.
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Multi-tenancy, scheduling, and cost modeling on Kubernetes
The post Architecting GPUaaS for Enterprise AI On-Prem appeared first on Towards Data Science.
Building a Self-Improving AI Support Agent with Langfuse
Building an LLM prototype is quick. A few lines of Python, a prompt, and it works. But Production is a different game altogether. You start seeing vague answers, hallucinations, latency spikes, and strange failures where the model clearly “knows” something but still gets it wrong. Since everything r...
Gemini 3.1 Pro: A Hands-On Test of Google’s Newest AI
Just 3 months after the release of their state-of-the-art model Gemini 3 Pro, Google DeepMind is here with its latest iteration: Gemini 3.1 Pro. A radical upgrade in terms of capabilities and safety, Gemini 3.1 Pro model strives to be accessible and operable by all. Regardless of your preference, pl...
The Missing Curriculum: Essential Concepts For Data Scientists in the Age of AI Coding Agents
AI can write the code, but you have to steer the ship. Master the knowledge to keep you relevant in the age of AI.
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FastMCP: The Pythonic Way to Build MCP Servers and Clients
Learn how to build MCP servers and clients using FastMCP, which is comprehensive, complete with error handling, best practices, and deployment strategies, making it ideal for both beginners and intermediate developers.
Building Production-Ready AI Agents with Agent Development Kit
ADK from Google addresses a critical gap in the agentic AI ecosystem by providing a framework that simplifies the construction and deployment of multi-agent systems. Learn more.
DBMS Data Models Explained: Types, Abstraction Levels, and SQL Examples
Modern applications rely on structured storage systems that can scale, stay reliable, and keep data consistent. At the heart of all of it sits the data model. It defines how information is organized, stored, and retrieved. Get the model wrong and performance suffers, integrity breaks down, and futur...
AlpamayoR1: Large Causal Reasoning Models for Autonomous Driving
All you need to know about Chain of Causation reasoning and the current state of Autonomous Driving!
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Have you ever tried connecting a language model to your own data or tools? If so, you know it often means writing custom integrations, managing API schemas, and wrestling with authentication.
When your warehouse and transportation teams blame each other for late deliveries, who's right? We can ask an agent connected to the data settle the debate.
The post Can AI Solve Failures in Your Supply Chain? appeared first on Towards Data Science.
Building Cost-Efficient Agentic RAG on Long-Text Documents in SQL Tables
Designing a hybrid SQL + vector retrieval system without schema changes, data migration, or performance trade-offs
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Agentic AI for Modern Deep Learning Experimentation
Stop babysitting training runs. Start shipping research. Autonomous experiment management built for/by deep learning engineers.
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Just two weeks after the launch of the frontier-grade Claude Opus 4.6, Anthropic has dropped its latest powerhouse: Claude Sonnet 4.6. But don’t let the Sonnet label fool you. Sonnet 4.6 is being hailed as the “Better-Opus” by developers in early access. For the first time, we are seeing a Sonnet-cl...
Iron Triangles: Powerful Tools for Analyzing Trade-Offs in AI Product Development
Conceptual overview and practical guidance
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Meet PaperBanana: Google’s AI That Auto-Generates Research Diagrams
Researchers today can draft entire papers with AI assistance, run experiments faster than ever, and summarise literature in minutes. Yet one stubborn bottleneck remains: creating clear, publication-ready diagrams. Poor diagrams look unprofessional and can obscure ideas and weaken a paper’s impact. G...