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You know the type: long ponytail, oval glasses, been at the company longer than the version control. Ask him for 50 lines and he writes one. It works. Ponytail makes AI agents (Claude Code, Codex & more) stop over-engineering. Before writing code, it climbs a 7-rung ladder — does this even need to exist? does the stdlib do it? does the browser already have it? — and stops at the first rung that holds. 📉 The results on real sessions: • −54% code (up to −94% where agents over-build) • −20% cost • −27% time • 100% of safety guards kept — validation, security, accessibility never cut. Lazy, not negligent. ⚙️ Install in Claude Code (two prompts, he insists): /plugin marketplace add DietrichGebert/ponytail /plugin install ponytail@ponytail 🔧 Commands: /ponytail-review · /ponytail-audit · /ponytail-debt · /ponytail-gain · /ponytail ultra ⭐ Repo (MIT): https://github.com/DietrichGebert/ponytail He'd be proud. He won't say it. #AI #Coding #ClaudeCode #DevTools #AIagents #SoftwareEngineering #OpenSource #Programming My Linkedin: https://www.linkedin.com/in/jacinthp/ --------------------------------------------- Github: https://github.com/jacinthpaul --------------------------------------------- Website: https://www.programstrategyhq.com/ ---------------------------------------------

AI Podcast - How Large Language Models LLMs Are Built - Inside Claude or ChatGPT Curious about how ChatGPT, Claude, Gemini, and other Large Language Models (LLMs) are actually built? In this deep-dive podcast, we break down the complete lifecycle of building an LLM—from data collection and tokenization to transformer architecture, pre-training, fine-tuning, inference, and deployment. Whether you're a software developer, AI engineer, architect, technical program manager, or engineering leader, this episode will give you a solid mental model of modern LLM systems. In this episode you'll learn: • What Large Language Models (LLMs) are • How transformer models work • Tokens, embeddings, and attention explained • Pre-training vs Fine-tuning vs Instruction Tuning • RLHF (Reinforcement Learning from Human Feedback) • Retrieval-Augmented Generation (RAG) • AI Agents and Model Context Protocol (MCP) • GPU infrastructure and distributed training • Model evaluation, alignment, and safety • Inference, optimization, and deployment • Build vs Fine-tune vs Use Foundation Models • Industry best practices for building production AI systems This episode is designed for learning on the go—perfect for your commute, workout, or study session. **Disclaimer:** This podcast was AI-generated using Google NotebookLM, which synthesized insights from multiple reputable sources on Large Language Models. The content has been curated to provide a cohesive, educational overview. If you're interested in AI engineering, Generative AI, LLM architecture, prompt engineering, agentic AI, and modern software development, consider subscribing for more technical deep dives. #LLM #GenerativeAI #ArtificialIntelligence #MachineLearning #Transformer #ChatGPT #ClaudeAI #AIEngineering #SoftwareArchitecture #PromptEngineering #RAG #MCP #AIAgents #Developers #TechPodcast My Linkedin: https://www.linkedin.com/in/jacinthp/ --------------------------------------------- Github: https://github.com/jacinthpaul --------------------------------------------- Website: https://www.programstrategyhq.com/ ---------------------------------------------

🔥 Anthropic has expanded its Claude Learning Portfolio with Three New Certifications! 🎓🎓🎓 When the Claude Certified Architect – Foundations certification launched early this year, it quickly became one of the most sought-after AI certifications for practitioners building production AI systems. These certifications are currently available for employees of Anthropic Partner organizations. Here's the complete lineup: 🟢 1. Claude Certified Associate – Foundations (New) Designed for client-facing and delivery professionals who use Claude in day-to-day business scenarios. Covers prompt refinement, model selection, responsible AI, and applying Claude effectively in business workflows. 🔗 Register: https://lnkd.in/dWAe6w2y⁠� 💻 2. Claude Certified Developer – Foundations (New) Built for developers creating AI-powered applications. Topics include the Claude API, Claude Code, MCP servers, custom tools, and building production-ready AI agents. 🔗 Register: https://lnkd.in/dt58mcgx⁠� 🏗️ 3. Claude Certified Architect – Foundations (Existing) The original certification focused on architecting production AI systems using Claude. It covers agentic architectures, orchestration, prompt engineering, structured outputs, evaluations, and best practices for building enterprise AI solutions. 🔗 Register: https://lnkd.in/dCArPDmJ⁠� 🌍 4. Claude Certified Architect – Professional (New) Targeted at experienced solution architects designing enterprise-scale AI deployments. Covers architecture, governance, integrations, optimization, and scaling AI systems across organizations. 🔗 Register: https://lnkd.in/d79s3GqX⁠ It's great to see Anthropic creating role-specific learning paths instead of having everyone follow the same certification. Whether you're a consultant, developer, or architect, there's now a certification tailored to your role. If you're part of an Anthropic Partner organization, these are definitely worth checking out. Video resource to help you clear Claude Architect Foundations - https://lnkd.in/d3eqwJiS. #Anthropic #ClaudeAI #GenerativeAI #ArtificialIntelligence #Certification #AIEngineering #SolutionArchitecture #ClaudeCode #MCP #Developers #Learning #TechCareer Anthropic Claude Code

New Claude Certifications Released | Associate vs Developer vs Architect #Claude #certification Confused about the Claude certification path? Here's a quick breakdown of all three certifications: 🟠 Claude Certified Associate – Perfect for consultants, business users, and non-technical professionals. 🟠 Claude Certified Developer – Designed for engineers building with the Claude API, Claude Code, and MCP. 🟠 Claude Certified Architect – Advanced certification focused on designing end-to-end AI solutions. Follow for more Claude AI tips, certification guides, and exam preparation content. #ClaudeAI #ClaudeCertification #AI #GenerativeAI #AIEngineer #AIArchitect #MCP #ClaudeCode #Anthropic #TechCareers #AITutorial #Shorts

Google has released 5 outstanding white papers on Kaggle covering the shift from traditional software engineering to Agentic Engineering. Together they're over 250 pages of practical guidance—not just on AI coding tools, but on how engineering teams, workflows, and software delivery are evolving. 📚 The collection includes: 🔹 The New SDLC With Vibe Coding From ad-hoc prompting to Agentic Engineering. A great introduction to how the software development lifecycle is changing. https://lnkd.in/dVPevtpS 🔹 Agent Tools & Interoperability Learn how AI agents communicate, use tools, integrate with MCP, and work together in production systems. https://lnkd.in/dNSK79sd 🔹 Agent Skills Covers the essential capabilities every AI agent needs, including planning, reasoning, memory, collaboration, and tool use. https://lnkd.in/dRYyyR8D 🔹 Vibe Coding Agent Security and Evaluation Explains how to evaluate AI agents, secure AI-powered applications, and introduce governance and responsible AI practices. https://lnkd.in/dRhxxMFk 🔹 Spec-Driven Production Grade Development in the Age of Vibe Coding My personal favorite. It explains how to move from AI-generated prototypes to production-grade software using specification-driven engineering. https://lnkd.in/dHqnF2jJ This is a must-read for anyone in Software Engineering—including Technical Program Managers. Understanding AI isn't enough anymore. We also need to understand how engineering practices, team structures, and delivery models are evolving alongside it. If you've already read any of these, I'd love to know which one was your favorite. Addy Osmani, Shubham Saboo #AI #ArtificialIntelligence #SoftwareEngineering #TechnicalProgramManager #AIEngineering #AgenticAI #VibeCoding #LLM #GoogleAI #Kaggle #EngineeringLeadership

Vibe Coding Without a Process with and Agile transformation explanation.. #aifunny