Author

ThinkingAgent

Sharing the latest AI-native technologies and real-world implementations.

Articles

Likes

176

Views

Comments

Latest from ThinkingAgent

51 recent articles

ThinkingAgent

Jun 12, 2026 · Artificial Intelligence

From Hand‑Crafted Features to Harnesses: Five AI Engineering Leaps

Over the past four decades AI has undergone five fundamental shifts—from manual feature engineering, through deep neural networks and prompt engineering, to autonomous agents and finally the Harness era—each redefining core technology, scarce talent, and value creation, with the 2026 Harness era emphasizing system‑level scalability over model size.

AI engineeringPrompt Engineeringagent systems

0 likes · 16 min read

From Hand‑Crafted Features to Harnesses: Five AI Engineering Leaps

ThinkingAgent

Nov 23, 2018 · Operations

RobotFramework Automation: Step‑by‑Step Installation and Sample HTTP Test

This guide walks through installing Python, pip, RobotFramework and its HTTP library, then demonstrates a complete RobotFramework test case that defines variables, creates an HTTP context, handles error scenarios, and validates response status and body content.

API testingPythonhttp testing

0 likes · 2 min read

RobotFramework Automation: Step‑by‑Step Installation and Sample HTTP Test

ThinkingAgent

Nov 22, 2018 · Artificial Intelligence

Understanding Machine Learning Categories: Supervised, Unsupervised, Semi‑Supervised, and Reinforcement

The article explains the four main machine‑learning categories—supervised, unsupervised, semi‑supervised, and reinforcement learning—detailing how each approach handles data labeling, typical algorithms, and common application scenarios.

AI FundamentalsMachine LearningSupervised Learning

0 likes · 2 min read

Understanding Machine Learning Categories: Supervised, Unsupervised, Semi‑Supervised, and Reinforcement

ThinkingAgent

Mar 22, 2018 · Artificial Intelligence

A Step‑by‑Step Guide to the Standard Machine Learning Workflow

The article outlines the seven‑stage machine‑learning pipeline—from data acquisition and preparation through model selection, training, evaluation, parameter tuning, and deployment—highlighting the critical role of feature engineering, which typically consumes over 80% of project time.

EvaluationMachine LearningModel Training

0 likes · 3 min read

A Step‑by‑Step Guide to the Standard Machine Learning Workflow

ThinkingAgent

Mar 4, 2018 · Artificial Intelligence

A Minimalist Guide to Machine Learning with Scikit‑Learn

The author reflects on six months of learning machine learning, explains that the core techniques are simple while real difficulty lies in applying them to specific problems, and shows how scikit‑learn can quickly address classification, regression, clustering, and dimensionality‑reduction tasks before discussing the need for deeper model and hyper‑parameter tuning.

Machine LearningModel Selectionclassification

0 likes · 3 min read

A Minimalist Guide to Machine Learning with Scikit‑Learn

ThinkingAgent

Jan 31, 2018 · Operations

Step-by-Step ELK Stack Installation and Configuration Guide

This article provides a detailed, command‑line walkthrough for installing Java, Elasticsearch, Logstash, and Kibana on Ubuntu, configuring each component with example configuration files, and verifying the ELK stack works by sending test data and querying the REST API.

ELKElasticSearchJava

0 likes · 5 min read

Step-by-Step ELK Stack Installation and Configuration Guide

ThinkingAgent

Jan 27, 2018 · Operations

Mastering Netcat (nc): The Ultimate Linux Tool for Reading and Writing Data

This article explains how to use netcat (nc) on Linux for TCP/UDP communication, covering command syntax, port scanning, banner grabbing, chat servers, file transfers, directory compression, encrypted streams, cloning devices, remote shells, and advanced piping techniques, all with concrete command examples.

LinuxTCPUDP

0 likes · 5 min read

Mastering Netcat (nc): The Ultimate Linux Tool for Reading and Writing Data

ThinkingAgent

Jan 24, 2018 · Operations

Mastering curl: Transfer URLs and Retrieve Data on Linux

This guide walks through curl’s syntax and options for fetching URLs, saving pages, handling cookies and headers, bypassing SSL verification, using proxies, performing POST requests, looping downloads, and FTP transfers, all illustrated with concrete command examples.

FTPHTTPLinux

0 likes · 5 min read

Mastering curl: Transfer URLs and Retrieve Data on Linux

ThinkingAgent

Jan 22, 2018 · Operations

Mastering tcpdump: Powerful Network Packet Capture Commands

This article provides a comprehensive guide to using tcpdump on Linux, covering command syntax, host and port filters, protocol selection, common and advanced expression syntax, TCP flag and fragment matching, and examples for capturing HTTP, SMTP, and SSH traffic.

Linuxcommand-linenetwork capture

0 likes · 10 min read

Mastering tcpdump: Powerful Network Packet Capture Commands

ThinkingAgent

Dec 27, 2017 · Artificial Intelligence

Advanced TensorBoard Visualization for MNIST Classification with TensorFlow

This tutorial walks through loading the MNIST dataset, building a softmax‑based neural network, defining cross‑entropy loss, applying a GradientDescentOptimizer, and using TensorBoard name scopes, scalar and histogram summaries to monitor training progress in TensorFlow.

MNISTNeural NetworkPython

0 likes · 7 min read

Advanced TensorBoard Visualization for MNIST Classification with TensorFlow