Archive
All Posts
Browse every article, guide, product review, and analysis piece in one place.
What is React? A developer's guide to building web applications
A plain-English developer guide to React, covering components, JSX, props, state, hooks, tooling, frameworks, React 19, Server Components and how React fits into real web applications.
The Claude Mythos 5 and Fable 5 US government ban is messier than it first looks
Anthropic launched Claude Fable 5 and Claude Mythos 5, then pulled access after a US export control directive. The practical result looked like a ban, but the policy story is more complicated.
Claude Fable 5 and Mythos 5 Released: Anthropic's new models explained
Anthropic has released Claude Fable 5 for general use and Claude Mythos 5 for vetted high-risk research partners. They share the same underlying Mythos-class model, but differ in safeguards, access and risk handling.
OpenClaw vs Hermes: Which AI Agent Framework Should You Use?
OpenClaw is stronger as a Gateway-first personal assistant for chat surfaces, while Hermes Agent is stronger as a self-improving workflow agent built around memory, skills, provider choice and scheduled automation.
What Is Perplexity Used For? AI Search, Answers and Computer Explained
A plain-English guide to Perplexity AI: what the answer engine does, how Search, Deep Research and Perplexity Computer work, how it compares with Google and ChatGPT, and where its cited answers and agentic workflows still need checking.
Codex vs Claude Code: the ultimate 2026 guide for developers
A practical, source-backed comparison of OpenAI Codex and Anthropic Claude Code, covering local CLI versus cloud-worker architecture, workflow feel, cost/token efficiency and Codex OAuth advantages for OpenClaw and Hermes.
Claude Opus 4.8 launches with stronger agentic coding capabilities
Anthropic has launched Claude Opus 4.8 with stronger coding and agentic workflow claims, unchanged standard API pricing, cheaper fast mode and new controls for how much effort Claude applies to a task.
What Is Claude Mythos? Anthropic's Cybersecurity Agent Explained
Claude Mythos Preview is Anthropic's restricted frontier model for AI-assisted cybersecurity. This explainer breaks down what it is, how Project Glasswing works, what the reported data shows and why the bottleneck is shifting from finding vulnerabilities to fixing them.
Anthropic says Claude Mythos found 10,000 severe software vulnerabilities. Now comes the hard part
Anthropic says Project Glasswing and Claude Mythos Preview have surfaced more than 10,000 high- or critical-severity vulnerabilities across critical software. The signal is serious, but the bottleneck is shifting from finding bugs to validating, disclosing and patching them safely.
ChatGPT personal finance explained: what OpenAI's bank-linked money assistant does
OpenAI's ChatGPT personal finance experience is a U.S. Pro preview that connects financial accounts through Plaid, creates a money dashboard and lets users ask ChatGPT questions grounded in their own financial context. The useful part is personalised insight. The hard part is trust, privacy and knowing where AI stops short of professional advice.
Andrej Karpathy joins Anthropic: why the Claude hire matters
Andrej Karpathy says he has joined Anthropic, giving the Claude maker one of the field's best-known AI researchers at a moment when frontier labs are fighting for pre-training talent, research judgement and ways to make model development more efficient.
What is Gemini Omni? Google's any-input AI video model, explained
Google Gemini Omni is a new multimodal model family that starts with video: it can take text, images, audio and video as input, then create or edit video through natural language. The first release, Gemini Omni Flash, is rolling out through Gemini, Google Flow and YouTube Shorts, with API access planned later.
DeepSeek Reportedly Building Claude Code and Codex Competitor
DeepSeek is reportedly hiring a Beijing-based Code Harness team, pointing to a possible Claude Code and Codex rival. The product has not launched, and key details remain unconfirmed.
Google I/O 2026 Gemini Announcements: Gemini Is Becoming Google's Agent Layer
Google used I/O 2026 to push Gemini beyond a chatbot and into a cross-product agent layer, led by Gemini 3.5 Flash, Gemini Omni Flash, Gemini Spark, Antigravity and Gemini-powered product launches.
What Is Vibe Coding? Meaning, Tools, Examples and Risks
Vibe coding is a style of AI-assisted software development where you describe what you want in plain language and an AI tool writes or edits the code. It is useful for prototypes, MVPs and learning, but generated code still needs review, testing and security checks.
What is an AI Agent Harness? Definition, Components and Examples
An AI agent harness is the runtime and control layer around an AI agent. It connects the agent to tools, context, memory, permissions, workflows, logging, evaluation and human approval so the agent can complete tasks safely and reliably.
What Is Tokenmaxxing? The AI Productivity Trend Explained
Tokenmaxxing is the habit of pushing AI token usage as high as possible, often through long prompts, coding agents, parallel workflows and internal usage leaderboards. Used well, it can encourage serious AI experimentation. Used badly, it turns productivity into an expensive token bonfire.
What Is a Transformer Model? The AI Architecture Behind Modern LLMs Explained
A transformer model is an attention-based neural network architecture behind many modern LLMs. It helps models weigh relationships between tokens in context, which is why GPT-style systems, BERT-style systems and other AI tools can handle prompts, examples and language patterns so flexibly.
What Is AI Model Training? How Models Learn Patterns From Data
A beginner-friendly explainer of AI model training, datasets, training examples, pattern learning, and why model quality depends so heavily on data quality.
What Is RAG in AI? How Retrieval-Augmented Generation Makes AI Answers More Useful
RAG connects an AI model to external documents, databases, files, or knowledge bases so it can retrieve relevant context before generating a more useful answer.
What Is an AI Agent? How Agentic AI Can Plan, Use Tools and Complete Tasks
A plain-English guide to AI agents, including how agentic AI can plan steps, use tools, observe results, complete tasks, and differ from a chatbot that mainly responds in conversation.
What Is a Prompt in AI? How to Write Better Instructions for ChatGPT, Claude and Gemini
A beginner-friendly explainer of AI prompts as the instructions, context, examples, constraints, and output format given to tools like ChatGPT, Claude, Gemini, and other AI assistants.
Codex mobile is now in ChatGPT: key features explained
OpenAI has brought Codex remote access to the ChatGPT mobile app in preview, giving users a mobile way to start threads, approve actions, review outputs, and supervise coding-agent work from iOS and Android while execution continues on the connected host.
AI vs Machine Learning vs Deep Learning vs Generative AI: What's the Difference?
A clear practical guide to the hierarchy of AI, machine learning, deep learning, and generative AI, with examples, comparisons, limitations, and common misconceptions.
What Is RLHF? How Human Feedback Helps Improve AI Responses
A beginner-friendly explainer of reinforcement learning from human feedback, how reward models work, and why human preference data can improve AI model behaviour.
What Are AI Evals? How Teams Test Whether an AI Model Is Working Properly
A beginner-friendly explainer of AI evals, test cases, grading methods, and the pre-deployment measurement habits teams use to make AI systems more reliable.
How Do AI Image Generators Work? Text-to-Image AI Explained for Beginners
A beginner-friendly explainer of how AI image generators turn prompts into images, how diffusion-style generation and editing work, and where text-to-image AI is useful or limited.
What Is GPT in AI? What Generative Pre-Trained Transformer Actually Means
GPT stands for Generative Pre-Trained Transformer: a transformer-based language model style that is broadly trained before use and generates text from context. GPT is usually an LLM, but it is not the same as all AI, all generative AI, or every transformer model.
Open Source AI vs Closed AI Models: What Is the Difference and Why Does It Matter?
A practical guide to open source AI versus closed AI models, including open weights, proprietary models, transparency, cost, safety, and business control.
What Is AI Inference? The Difference Between Training an AI Model and Using One
AI inference is the process of using a trained model to generate answers, predictions, labels, images, recommendations or other outputs from new input.
What Is Machine Learning? How AI Learns From Data Instead of Fixed Rules
A beginner-friendly explainer of machine learning as pattern learning from data, including how ML differs from fixed-rule software, how models train on examples, common use cases, main types, benefits and limitations.
What Is Multimodal AI? How AI Understands Text, Images, Audio and Video Together
A plain-English guide to multimodal AI, including how models process text, images, audio and video together, where multimodal systems are useful, and why high-stakes outputs still need human review.
What Is a Context Window in AI? Why ChatGPT Can Forget Parts of Long Conversations
A context window is the active token budget an AI model can use for a request or turn. It explains why ChatGPT can seem to forget details in long conversations and why large documents need careful context management.
What Is a Vector Database? Why AI Apps Store Meaning as Searchable Numbers
A vector database stores embeddings as searchable numerical representations so AI apps can retrieve related documents, products, images, or knowledge base chunks by similarity rather than exact keywords.
What Is Temperature in AI? How Randomness Changes ChatGPT Responses
Temperature in AI controls how much randomness a model uses when generating responses. It affects why ChatGPT outputs vary, how creative or consistent answers feel, and how much risk a workflow accepts.
What Is Prompt Engineering? Beginner Examples, Best Practices and Common Mistakes
Prompt engineering is the practical skill of writing clearer AI instructions. This beginner explainer defines the concept, shows examples, explains best practices, and flags common mistakes that lead to weak or risky AI responses.
What Is MCP in AI? The Model Context Protocol Explained for Beginners
A beginner-friendly explainer of MCP as the open standard that connects AI assistants to tools, files, data sources, systems and workflows, with practical examples and security caveats.
What Is a Token in AI? A Beginner's Guide to AI Tokens, Costs and Context Windows
AI tokens are the small units of text or data that models process. They matter because token counts shape AI pricing, context windows, memory-like working context, output length, latency, and usage limits.
What Is Grounding in AI? How to Make AI Answers Use Trusted Sources
A beginner-friendly explainer of AI grounding, source-backed answers, RAG, citations, and the practical habits that help reduce unsupported AI claims.
What Is Tool Calling in AI? How Models Use APIs, Apps and External Data
A clear beginner-friendly explainer of tool calling in AI, including how models request functions, APIs, apps and external data, plus practical examples and safety guidance.
What Is AI Bias? How Training Data Can Create Unfair AI Outcomes
A plain-English explainer of AI bias, how training data can create unfair outcomes, and why biased AI systems matter for business, search, hiring, finance, and public services.
AI Chatbot vs AI Agent: What's the Difference for Beginners?
A beginner-friendly comparison of AI chatbots and AI agents, including reactive chat, goal-oriented planning, tool use, autonomy, examples, risks, and when to choose each one.
Why Does AI Hallucinate? What AI Hallucinations Are and How to Reduce Them
A practical explainer of AI hallucinations, why generative AI can produce false or unsupported answers, and how to reduce risk with grounding, citations, verification, and human review.
What Is a Foundation Model? Why Modern AI Models Can Be Reused for Many Tasks
A plain-English explainer of foundation models as large reusable AI base models, covering how they work, how they are adapted, where they appear in real products, and why their strengths and weaknesses travel downstream.
What Are AI Model Parameters? The Difference Between Model Size, Settings and Controls
AI model parameters are learned internal values, often weights and biases. This explainer separates model size from user settings like temperature, top_p and max output tokens.
What Is Generative AI? A Simple Guide to AI That Creates Text, Images, Code and Video
Generative AI is artificial intelligence that creates new content, including text, images, audio, video and code. It differs from traditional AI because traditional AI usually predicts, classifies, detects, ranks or recommends, while generative AI produces new outputs from learned patterns and prompts.
What Is Responsible AI? A Beginner's Guide to Safe, Fair and Transparent AI
A beginner-friendly explainer of responsible AI principles, governance, transparency, bias, fairness, and the practical controls teams use to manage AI risk.
What Is a Large Language Model? How LLMs Power ChatGPT, Claude and Gemini
A plain-English explainer of large language models, including training data, token prediction, how LLM-powered products work, common use cases, benefits, limitations and practical review habits.
What Is a Neural Network in AI? A Simple Explanation for Beginners
A beginner-friendly explainer of artificial neural networks as layered pattern-learning models, including how neurons, layers, weights, biases, training, examples, benefits, and limitations fit together.
What Is Deep Learning? How Neural Networks Help AI Understand Complex Data
A beginner-friendly explainer of deep learning as machine learning with layered neural networks, including how deep learning works, why layers matter for complex data, real-world examples, benefits, limits and related AI terms.
What Is Artificial Intelligence? A Beginner's Guide to AI in Everyday Life
A complete beginner guide to artificial intelligence, with a plain-English definition, everyday examples, common use cases, key terms, benefits, limitations, and FAQs.
What Is Fine-Tuning in AI? When Should You Train a Custom AI Model?
Fine-tuning adapts an existing AI model for a narrower task or domain, but it is only worth using when prompting, RAG, tools, and evals are not enough.