Search: “story” Category: Code and Tech — 10 articles.
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10 articles in Code and Tech · matching “story”
Agentic AI is revolutionizing software development by automating complex, multi-step tasks. Discover how these intelligent tools enhance efficiency while emphasizing the indispensable role of human oversight in ensuring quality and ethical outcomes.
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Discover how to build a powerful AI coding agent by assembling multiple layers, from orchestration to reflection, to handle complex, real-world development sessions effectively.
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Explore how agentic AI is transforming software development by autonomously writing, testing, and shipping code, leading to more efficient and robust build pipelines. Discover the impact and future of AI agents in your development workflow.
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In tech, there’s an old assumption that marketing and software engineering exist in two separate universes. Product managers and engineers write the code; marketers write the slogans and launch the campaigns. That boundary has officially dissolved. As software products become more technical—ranging from API-first platforms to developer tools and AI models—the way we market them has fundamentally shifted. Modern product marketing isn't just about compelling messaging anymore; it's about code, developer experience (DX), and technical empathy. Whether you're marketing a developer-focused platform like Stripe or leveraging data to drive growth in a SaaS business, understanding the coding side of product marketing is quickly becoming a cheat code for growth.
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Here is a quick breakdown of what the article covers: * **The Shift:** Traditional RAG follows a rigid, linear pipeline (`Retrieve -> Generate`). **Agentic RAG** introduces dynamic, self-correcting loops using the LLM as a reasoning engine within a state machine. * **Why LangGraph:** Unlike standard DAG (Directed Acyclic Graph) pipelines, LangGraph supports **cyclic workflows** (loops), enabling self-evaluation, error handling, and tool re-invocations. * **Core Architecture:** Built around three elements: * **State:** A shared dictionary (`AgentState`) tracking history and variables across steps. * **Nodes:** Python functions that execute steps (agent reasoning, evaluation, web search). * **Edges:** Conditional routes that direct execution flow based on state evaluation. * **Production Best Practices:** Always enforce **iteration limits** to prevent infinite loops, use **lightweight models** for evaluators to reduce latency, and keep evaluation separate from tool execution.
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Learn from our mistakes as we recount a critical incident caused by a misstep with Terraform, highlighting key lessons for robust Infrastructure as Code practices.
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If you are reading this article on an Android phone, accessing a website hosted on a cloud server, or watching a movie on a smart TV, you are interacting with the invisible, foundational work of one programmer: Linus Torvalds.
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Unlock peak productivity in AI development with this curated list of essential VS Code extensions. From intelligent code completion to seamless notebook integration, discover the tools that will transform your machine learning and data science projects.
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Discover what AI agents are, how they work, and their potential applications in a clear, beginner-friendly explanation. Understand the core components that drive these intelligent systems.
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Explore the evolving landscape of AI-powered and human-centric products. Discover which approaches are dominating the market and why, with key insights for product development.
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