Stop Writing Boilerplate. Start Building: Introducing app-generator-cli
Author(s): Rajendra Kumar Yadav, M.Sc (CS) Originally published on Towards AI. Scaffold production-ready FastAPI, LangChain, and full-stack Python projects in seconds — powered by uv. You have a great idea. You open your terminal, create a new folder, and then… you spend …
Data Mining
Author(s): Sefa Bilicier Originally published on Towards AI. Introduction In today’s digital economy, data has become the new oil. But unlike oil, which requires drilling and refining, data requires a different kind of extraction: data mining. Everyday, organizations generate massive amounts of …
This Model Completely Crashed Computer Vision.
Author(s): Julia Originally published on Towards AI. Why is everyone obsessed with YOLO? And no I don’t talk about the 2012 mantra “You Only Live Once”. For years, computers struggled to “see” the world. Object detection, the task of finding and identifying …
From Interface to Behavior: The New UX Engineering
Author(s): Yelpin Sergey Originally published on Towards AI. Agentic UX is the next step in the evolution of interfaces. Services are learning to listen to the user, understand intent, and act on their own — moving beyond familiar buttons and forms. This …
Part 16: Data Manipulation in Data Validation and Quality Control
Author(s): Raj kumar Originally published on Towards AI. Data quality issues are the silent killers of production systems. A single malformed record can crash your pipeline. A gradual drift in data distributions can slowly degrade model performance. Missing values that sneak through …
A Plateau Plan to Become AI-Native
Author(s): Bram Nauts Originally published on Towards AI. AI will not transform because it’s deployed – it will transform because the way of operating is redesigned. The tricky part? Transformations rarely fail at the start, they fail in the middle – when …
AgentOps: Your AI Agent Is Already Failing in Production. You Just Can’t See It
Author(s): Divy Yadav Originally published on Towards AI. The practical guide to monitoring, debugging, and governing AI agents before they become a liability You shipped an AI agent. It worked in staging. Photo by authorFollowing the introduction, the article delves into the …
Calling the Anthropic API: 4 Lines to Your First LLM Response
Author(s): Nagaraj Originally published on Towards AI. No boilerplate here. No DI container, nothing-no middleware whatsoever. Just results I have dedicated several months to developing artificial intelligence backends using C# which includes building Semantic Kernel and HttpClient and custom middleware and dependency …
How AI Agents Work: The OpenClaw Case
Author(s): CreateMoMo Originally published on Towards AI. How AI Agents Work: The OpenClaw Case This note uses OpenClaw as an example to explain how AI Agents work. While technology is evolving rapidly — and some details may differ from the latest developments, …
A Very Fine Untuning
Author(s): Alexandra Rusina Originally published on Towards AI. How fine-tuning made my chatbot worse (and broke my RAG pipeline) I spent weeks trying to improve my personal chatbot, Virtual Alexandra, with fine-tuning. Instead I got increased hallucination rate and broken retrieval in …
Crack ML Interviews with Confidence: Anomaly Detection (20 Q&A)
Author(s): Shahidullah Kawsar Originally published on Towards AI. Data Scientist & Machine Learning Interview Preparation Different types of anomaly detection techniques: Source: Image is generated by ChatGPTThis article discusses various anomaly detection techniques relevant for data scientists and machine learning practitioners, outlining …
Hate Speech Detection Still Cooks (Even in 2026)
Author(s): Saif Rathod Originally published on Towards AI. The failure case you didn’t see coming In late 2025, a major social platform quietly rolled back parts of its LLM-based moderation pipeline after internal audits revealed a systematic pattern: posts in African American …
Reliable Agentic Development on a €40 Budget: Dependency-Aware Orchestration for Claude, Codex, and Human-in-the-Loop
Author(s): Akash Acharya Originally published on Towards AI. Most agentic coding demos show the happy path: AI gets task, AI writes code, done. What they don’t show is who decides what the tasks are. Or what happens when a task is marked …
Why System Behaviour Must Be Designed, Not Improvised
Author(s): Muhammad Ejaz Ameer Originally published on Towards AI. By Muhammad Ejaz Ameer, Product & Decision Architecture Lead There is a moment in the life of almost every digital product when the team realises something uncomfortable: the system does not actually know …
The Loop: How an AI Swarm Surfaced a Governance Limitation, Then Tested the Fix
Author(s): Selfradiance Originally published on Towards AI. AgentGate is a runtime accountability layer for AI agents: before an agent can execute a high-impact action, it must lock a bond as collateral. Good outcomes release the bond. Bad outcomes slash it. The mechanism …
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