Expert profile
Founder & AI Product Leader
Yash Thakker is a Generative AI expert with over 12 years of experience in product leadership and technical strategy. As the founder of explainx.ai, he has taught over 300,000 learners and built AI platforms serving millions of users globally. He specializes in Agentic AI, Multimodal RAG, and the intersection of LLMs with consumer hardware.
A practical, step-by-step guide to learning AI in 2026. Real prompts, real commands, real exercises — from your first Claude conversation to building...
LoginWithChatGPT lets users run Codex on their ChatGPT plan inside your site. Device auth flow, TOS risk, vs API, OpenClaw, and usemysub explained.
Complete MCP security guide — threat models, OAuth authentication, prompt injection defense, audit logging, least privilege design, and a production security checklist for Model Context Protocol deployments in 2026.
Complete guide to Meta Llama 4 in 2026: model family explained, Mixture of Experts architecture, running locally with Ollama, fine-tuning with LoRA, benchmarks vs GPT and Claude, and when open weights win.
Learn the five core multi-agent orchestration patterns — orchestrator/worker, pipeline, fan-out, debate, and routing — with architecture diagrams, code, cost analysis, and framework recommendations.
Commerce Secretary Lutnick’s June 26 letter to Anthropic COO Tom Brown: Mythos 5 restored only for Annex A US trusted partners, Anthropic foreign-national...
OpenMontage GitHub guide: 12 pipelines, zero-key path, real-footage montages, costs, AGPL, vs ViMax/Runway, Claude Code setup, and known limitations.
Install Python, choose the right interpreter, create a virtual environment, and debug your first script with practical beginner exercises.
Understand ReAct prompting, write tool-action loops, handle failures, enforce action permissions, and log real observations without inventing results.
Deep technical guide to scalable oversight: RLHF mechanics, reward hacking, DPO, RLAIF, Constitutional AI step by step, weak-to-strong generalization, debate, and practical takeaways for AI teams building in 2026.
Compare CLAUDE.md, SKILL.md agent skills, and hooks in Claude Code. A practical decision guide for when to use each customization primitive and how to combine them.
Get reliable JSON from any LLM. Covers native JSON mode, prompt-based instructions, tool calling schemas, Pydantic validation, and retry patterns for production pipelines.
