Alex | Apetech | Jira Expert

Jira For Scrum Masters -> apetech.me/scrumMasters.h…

Anthropic just launched the Claude Architect Certification! You’ll have to complete 60 multiple-choice questions across five competency areas in a single session. No external resources or breaks. Here’s how I’m planning to prepare for it (steal my roadmap): Week 1 Complete the recommended courses: - Building with the Claude API - Introduction to Model Context Protocol - Claude Code in Action - Claude 101 Week 2 Build real projects with: - Claude Code - Agent SDK - Anthropic API - MCP Week 3 Get familiar with the exam structure and guide: - Go through the six exam scenarios - Get familiar with the five competency areas / domains - Learn the skills needed for each task assessment Week 4 Do the preparation exercises from the exam guide: - Build a Multi-Tool Agent with Escalation Logic - Configure Claude Code for a Team Development Workflow - Build a Structured Data Extraction Pipeline - Design and Debug a Multi-Agent Research Pipeline Week 5 - Take the practice exam - Aim for a score greater than 850 / 1000 Week 6 - Take the real exam - Only one attempt allowed NOTES: - At this point the certification is exclusive for Anthropic Partners and early access is free for first 5,000 partner company employees. - Your mileage may vary depending on your skill level. E.g. It may take 2 weeks for some but 10 weeks for others. If you are eligible, register here → lnkd.in/eEYwUGV5

Probably one of the best "from scratch" AI series out there.

Google just dropped a FREE AI Agents course. And almost no one is talking about it. 10+ code samples, whitepapers, hands-on projects... all in one place. Here’s the full breakdown (5 days): Day 1: Foundations of AI Agents Learn how agents actually work: • Architecture • Capabilities • How they differ from LLMs → Build systems that can perceive, plan, act Whitepaper: lnkd.in/grYivvCW Code: lnkd.in/gcDruAx7 Day 2: Tools & MCP (Model Context Protocol) Agents don’t work alone. Learn: • Tool usage & APIs • MCP architecture • Human-in-the-loop workflows Whitepaper: lnkd.in/gnU9yqqW Code: lnkd.in/g5ZQHGzg Day 3: Context Engineering (Memory) This is where agents become powerful. • Sessions → short-term memory • Persistent memory → long-term learning Whitepaper: lnkd.in/g9WztfuP Code: lnkd.in/g4mQEtPE Day 4: Agent Quality Production-ready systems need reliability. Learn: • Logs, traces, metrics • Evaluation frameworks • LLM-as-a-judge Whitepaper: lnkd.in/g-SAMSpV Code: lnkd.in/gJxMN46g Day 5: From Prototype → Production Where most people fail. • Deployment strategies • Scaling agents • Agent-to-Agent communication • Vertex AI ecosystem Whitepaper: lnkd.in/gnUAscjM Code: lnkd.in/gnikixYA This is basically a complete roadmap to building AI agents in 2026. And it’s 100% free. Save this. You’ll need it later 💾 Like 👍 • Repost ♻️ Follow for no-BS AI insights 🚀

A senior Google engineer just dropped a 421-page doc called Agentic Design Patterns. Every chapter is code-backed and covers the frontier of AI systems: → Prompt chaining, routing, memory → MCP & multi-agent coordination → Guardrails, reasoning, planning This isn’t a blog post. It’s a curriculum. And it’s free.

10 FREE AI Courses to try in 2026: 1. Google AI Essentials coursera.org/learn/google-a… 2. Meta Generative AI Fundamentals coursera.org/learn/generati… 3. Stanford Machine Learning (Andrew Ng) coursera.org/learn/machine-… 4. IBM AI Engineering Foundations coursera.org/professional-c… 5. Open-Source LLMs with Hugging Face huggingface.co/learn 6. LangChain for LLM App Development deeplearning.ai/short-courses/… 7. Claude code in action anthropic.skilljar.com/claude-code-in… 8. AI for Everyone (Non-Technical) coursera.org/learn/ai-for-e… 9. MLOps Fundamentals madewithml.com 10. Introduction to Generative AI with Google skills.google/paths/118/cour…

20 Must Known AI Concepts 📘📚

AI is replacing people without the right skills. Build AI skills to future-proof your career. Knowing AI tools isn’t enough. It’s critical to learn the right AI skills. These 9 skills outline how professionals work with AI, from basic interaction to system-level execution. Building a few of them will expand your career options and opportunities. Here’s the full breakdown of each skill: [ 🔖 bookmark this post for later ] 1️⃣ Prompt Engineering Write clear instructions that produce consistent, useful AI results. Most people type one prompt and fix the output later. Professionals structured prompts that deliver repeatable outcomes across tools and tasks. Tools: Claude, ChatGPT 2️⃣ Workflow Automation Link platforms together to let AI handle your repetitive work. This is how teams eliminate manual handoffs and turn routine processes into background systems. Tools: n8n, Zapier 3️⃣ AI Image Generation Produce professional-grade visuals for ads and products via text. Instead of waiting on designers or stock assets, teams generate visuals on demand and iterate instantly. Tools: NanoBanana (Gemini), Recraft 4️⃣ Vibe Coding Ship working prototypes rapidly without deep manual code knowledge. The technical wall is gone; founders are now launching functional products by describing their ideas instead of hiring expensive developers. Tools: Lovable, Replit 5️⃣ Custom GPTs Create tailored AI assistants for specific tasks without code. This turns AI from a general tool into a system that understands your workflows, tone, and use cases. Tools: OpenAI GPT Builder, Poe 6️⃣ AI Video Generation Turn concepts into cinematic video content without editing expertise. Scale video marketing and training at lower costs by generating polished scenes from text scripts. Tools: Synthesia, Runway 7️⃣ AI-Assisted Development Write and debug code faster using real-time AI guidance. Developers focus on logic and architecture while AI handles syntax, errors, and refactoring. Tools: Cursor, Google Antigravity 8️⃣ Agentic Coding Assign full coding tasks to AI agents that strategize and execute. Instead of guiding every step, you define goals and let agents plan and complete the work. Tools: OpenAI Codex, Claude Code 9️⃣ RAG Systems Link AI to your internal data for relevant, business-specific responses. This replaces generic outputs with answers grounded in your documents, systems, and knowledge base. Tools: LangChain, Haystack AI tools aren’t enough. It’s critical to build AI skills. Use this roadmap to: ➟ Identify which AI skills support your role or team ➟ Start with one skill and apply it in real work ➟ Expand only after you see results That’s how AI becomes a long-term asset, not a distraction. 📌 Get Advanced ChatGPT Guide (free): bit.ly/3StIB3z 👉 Follow me @AndrewBolis for more and 🔄 Repost this to help others use AI

How to Master Claude Code 📚📘

Most people buy $997 AI courses... I built 13 AI Agents using $0 paid courses. Now I’m giving away the entire blueprint for FREE. This is not theory. This is the exact roadmap I used to: • Understand LLMs from scratch • Learn agent frameworks • Build production-ready AI agents • Use real repos & whitepapers • Skip expensive “guru” courses You’ll get: 📂 Curated learning path (videos + repos) 📘 Agent design guides 📚 Must-read books 🧠 Execution framework ⚙️ Practical build roadmap No fluff. No hype. Just implementation. If you use this properly, you can: • Build AI tools • Launch micro-SaaS • Freelance AI solutions • Create automation systems • Turn skills into income This is easily a $2,500+ roadmap if packaged as a course. But I’m dropping it free. How to get it: 1️⃣ Follow me 2️⃣ Like + Repost 3️⃣ Comment “Blueprint” I’ll send it to everyone who follow.

EVERY VIBE CODER NEEDS TO READ THIS BEFORE SHIPPING TO PRODUCTION:

🚨 BREAKING: Someone wrote a 200+ page book on mastering Claude Code and put it on GitHub for free. No paywall. No email signup. No Gumroad checkout. Here is what is inside: → Templates and prompts you can use immediately → Real project workflows from start to finish → Quizzes and exercises that actually test your understanding → Practical examples built around how Claude Code works in production → 200+ pages of structured content that reads like a proper course This is the Claude Code resource the community has been waiting for. No upsells. No drip content. No checkout page. Just the full guide, open source, free forever.

10 Completely FREE AI Courses for 2026: 1. Anthropic: anthropic.skilljar.com 2. Google: grow.google/ai 3. Meta: ai.meta.com/resources 4. NVIDIA: developer.nvidia.com/training 5. Microsoft: learn.microsoft.com/training 6. OpenAI: academy.openai.com 7. IBM: skillsbuild.org 8. AWS: skillbuilder.aws 9. DeepLearningAI: deeplearning.ai 10. Hugging Face: huggingface.co/learn

I created a GitHub Repository to learn AI Engineering, and I'm excited to share that it crossed 4500 stars recently. It contains some of the best free courses, articles, tutorials, and videos to learn: - Mathematical Foundations - AI & ML Fundamentals - Deep Learning and Specializations - Generative AI - Large Language Models (LLMs) - Prompt Engineering Guides - RAG, Agents and MCP Check it out here: github.com/ashishps1/lear… If you find the repo valuable, consider giving it a⭐ and share with others.

DevOps Roadmap 2026: 🔥 1) Linux 2)Git 3) Networking 4) Bash/Python 5)CI/CD 6) Docker 7) Kubernetes 8) Cloud (AWS/Azure/GCP) 9) Terraform/Ansible 10) Prometheus/ELK 11) Automate all 12) Stay updated DevOps Engineer unlocked!

Mark Cuban dropped one of the most practical pieces of career advice we've heard in a while. Cuban told students that the single biggest job opportunity right now is learning how to walk into a business and show them how to actually use AI. Not studying AI theory or not building models from scratch. But implementing it inside real companies that have no idea where to start.​ There are roughly 33 million businesses in the United States, and about 30 million of those are one person operations. Millions more are small companies with 5 to 100 employees that don't have AI budgets, don't have IT departments, and definitely don't have a machine learning engineer on payroll. Every single one of them is going to need to figure out AI if they want to survive the next decade. That's the gap Cuban is pointing to.​ He draws a direct parallel to his own career. When he was 24, he was walking into businesses that had never seen a personal computer before. The owner would point at his receptionist and say "I don't need that machine." Cuban's job was to show them how a PC could transform their workflow and he made serious money doing it. He's saying AI is that exact same moment, just on a much bigger scale.​ The data backs this up. Only about 8.8% of small businesses were actively using AI as of mid 2025. A Goldman Sachs survey found that while 68% of small business owners say they're using AI. About 60% of those struggling with it say the core issue is a lack of expertise in applying it to their specific operations. And an MIT study from 2025 found that 95% of enterprise AI pilot projects failed to deliver any measurable return on investment. Companies poured $30 to $40 billion into generative AI and the overwhelming majority saw zero P&L impact. The problem wasn't the models, it was implementation. That bridge person who can connect AI to real business needs is exactly what Cuban is describing.​ His advice to his own kids ages 15, 19, and 21 is dead simple. Don't chase a job at Google or Microsoft where your AI skills get buried under a 200 person IT team. Instead, go to the small and medium sized companies where you'll be one of the only people who understands these tools. Spend your spare time learning the differences between tools like Sora and Veo, learn how to customize AI models. And then walk into a shoe store or a local logistics company and say "here's how AI can help your specific business." The last time something like this happened at scale was the PC revolution in the 1980s and the internet boom in the late 1990s. Both times, young people who understood the new technology walked into businesses and became indispensable. The same playbook is running again right now. Cuban isn't saying AI is going to replace everyone's jobs. He's saying there's a massive wave of new jobs coming but they look different than what most people expect. It's not about being an AI researcher at a lab. It's about being the person who can translate AI into real business value for the millions of companies that need it but can't figure it out on their own. That's the next gold rush and it's hiding in plain sight at your local small business.

🚨BREAKING: Google just launched CodeWiki, and it might be the biggest upgrade GitHub has had in years. You paste your GitHub repo in, and it turns your entire project into an interactive guide. It also generates diagrams, explanations, walkthroughs, everything you could ever want, and even a chatbot that knows the code better than anyone else.

Mark Cuban on the next job wave. Customized AI integration for small to mid-sized companies. "Software is dead because everything's gonna be customized to your unique utilization. Who's gonna do it for them... And there are 33 mn companies in the US."

10 Completely FREE AI Courses for 2026: 1. DeepLearning AI coursera.org/learn/ai-for-e… 2. Introduction to Generative AI skills.google/paths/118 3. AI and Algorithms ocw.mit.edu/courses/res-tl… 4. Machine Learning Crash Course developers.google.com/machine-learni… 5. CS50’s Introduction to AI with Python cs50.harvard.edu/ai/ 6. Introduction to Deep Learning introtodeeplearning.com 7. Foundation Models & Generative AI youtube.com/watch?v=y1fGlA… 8. ChatGPT Prompt Engineering for Developers deeplearning.ai/short-courses/… 9. Generative AI for Everyone coursera.org/learn/generati… 10. Building RAG Agents with LLMs learn.nvidia.com/courses/course…

If you want to become a better software engineer (in 2026), read these 12 engineering blogs: 1. Meta Engineering ↳ engineering.fb.com 2. Netflix TechBlog ↳ netflixtechblog.com 3. AWS Architecture ↳ aws.amazon.com/blogs/architec… 4. Microsoft Engineering ↳ devblogs.microsoft.com/engineering-at… 5. Google Research ↳ research.google/blog 6. Slack Engineering ↳ slack.engineering 7. Discord Engineering ↳ discord.com/category/engin… 8. NVIDIA Developer ↳ developer.nvidia.com/blog 9. Stripe Engineering ↳ stripe.com/blog/engineeri… 10. Uber Engineering ↳ uber.com/en-AU/blog/per… 11. Cloudflare Blog ↳ blog.cloudflare.com/tag/engineering 12. GitHub Engineering ↳ github.blog/engineering What other blogs should be on this list? -- 👋 PS: Want my System Design Handbook for free? Want my Architecture Patterns Playbook for free? Join my newsletter with 26,501+ software engineers: lucode.co/luc-newsletter… -- 📌 Save for later. ♻️ Repost to help others grow. ➕ Follow Nikki Siapno + turn on notifications.