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Provides a 1-hour-per-day schedule, starting from prerequisites and API setup, then progressing through prompt engineering, structured outputs, first AI agents, tool use and workflows, RAG, multi-modal vision, and multi-provider evaluation and security. 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Each week specifies how to split time across watching, reading, and building.","Answer",{"name":114,"@type":109,"acceptedAnswer":115},"Which model is suggested as the default for most tasks?",{"text":116,"@type":112},"Use gpt-5-mini as the default model for learning and most tasks unless a different model is specified.",{"name":118,"@type":109,"acceptedAnswer":119},"What is the main project goal of Week 1?",{"text":120,"@type":112},"Build an “Explain Like I'm 5” chatbot that lets users select a GPT-5 model tier and adjust response complexity, then streams the output in real time.","https://schema.org",{"og:url":83,"og:type":123,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":125,"canonical":83},"index,follow",{"doc_id":127,"site_id":62},672793,1793608168,{"code":4,"msg":5,"data":130},{"doc_id":127,"user_id":131,"nickname":92,"user_avatar":132,"doc_module":4,"category_id":29,"category_name":30,"doc_title":65,"doc_description":67,"doc_content":133,"file_id":134,"file_url":135,"file_type":136,"file_size":137,"view_count":8,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":138,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":128,"read_time":143},34359740700684,"https://ap-avatar.wpscdn.com/avatar/1f400023980c374ae676?_k=1777273430885731487","PRANEETH KALLURI  \npresents  \n LLM  Engineering   \nRoadmap 2026  \n8-Week Practical Guide to Building with Large Language Models  \nPRANEETH KALLURI  \nInstagram: @praneeth_kalluri | @praneethkalluri | LinkedIn  \nNext.js • Vercel AI SDK v6 • GPT-5 Family • Multi-Provider For working professionals & students | 1 hour/day | All free resources  \n2  \n1  \n3  \n4  \n5  \n8  \n7  \n6  \nHow to Use This Roadmap  \n• 1 hour/day is enough. Each week tells you exactly how to split your time across watching, reading, and building.  \n• Build every project. Tutorials teach theory. Projects teach skills. Every week ends with a real project for this reason.  \n• One API key is enough. Get OpenAI, set $5-10/month budget, use gpt-5-mini for everything unless specified.  \n• Watch first, then build. Videos build understanding. Docs are reference while coding.  \n• Push everything to GitHub. 8 weeks = 8 projects = a portfolio that proves your skills.  \n• Share your progress. Post on LinkedIn, Twitter, Instagram. Teaching accelerates learning.  \nAPI Setup—Do This Before Week 1  \n• Get an OpenAI API key → [https://platform.openai.com/api-keys](https://platform.openai.com/api-keys)  \n• Set budget limit ($5-10/month) → [https://platform.openai.com/settings/organization/l](https://platform.openai.com/settings/organization/l)imits  \n• Default model: gpt-5-mini—cheapest, fastest, great for learning  \n• Understand model tiers → OpenAI Models Page  \nGPT-5 Model Tiers (March 2026)  \n\n| Model | Best For | Speed | Cost |\n| --- | --- | --- | --- |\n| gpt-5-mini | Most tasks, learning, prototyping | Fastest | Cheapest |\n| gpt-5 | Complex reasoning, vision, agents | Medium | Medium |\n| gpt-5.4 | Flagship—hardest tasks, agentic | Slower | Premium |\n\nGPT-5 has built-in reasoning via reasoning.effort (none/low/medium/high) . Adjust effort instead of switching models.  \nInstagram: @praneeth_kalluri | YouTube: @praneethkalluri | LinkedIn: /in/praneethkalluri  \nRoadmap Overview  \nWeek 0 Prerequisites  \n\n| Week 1 | Understand LLMs |\n| --- | --- |\n| Week 2 | Prompt Engineering & Structured Outputs |\n| Week 3 | AI Agents—Concepts & First Agent |\n| Week 4 | Tool Use, Function Calling & Workflows |\n| Week 5 | RAG—Retrieval Augmented Generation |\n| Week 6 | Multi-Modal—Vision & Beyond Text |\n| Week 7 | Multi-Provider, Evaluation & Security |\n| Week 8 | Ship It—Full Product (Capstone) |\n\nBonus Build Your Own LLM + Courses  \nWEEK 0  \nPrerequisites  \nMake sure you're comfortable with these before starting. Working developers can skip to Week 1.  \n• JavaScript / TypeScript basics  \n• React fundamentals  \n• Git & GitHub  \n• Terminal / CLI basics  \n• REST APIs & [HTTP](HTTP)  \n• Next.js basics (Vercel AI SDK v6 runs on Next.js)  \n\n| WEEK 1\u003Cbr>Understand LLMs\u003Cbr>Pace: Days 1-3: Watch videos | Days 4-5: Read docs + set up | Days 6-7: Build project | \u003Cbr>Beginner Friendly |\n| --- | --- |\n| By the end of this week, you will:\u003Cbr>✓ Explain how LLMs work (tokens, context windows, training) to a non-technical person\u003Cbr>✓ Set up a Next.js project with Vercel AI SDK v6 and connect to OpenAI\u003Cbr>✓ Build a working streaming chatbot from scratch\u003Cbr>✓ Understand the difference between GPT-5 model tiers\u003Cbr>Watch\u003Cbr>• Andrej Karpathy—Intro to Large Language Models (1hr) → [https://www.youtube.com/watch?v=zjkBMFhNj_g](https://www.youtube.com/watch?v=zjkBMFhNj_g)\u003Cbr>• Andrej Karpathy—Software in the Era of AI → [https://www.youtube.com/watch?v=LCEmiRjPEtQ](https://www.youtube.com/watch?v=LCEmiRjPEtQ)\u003Cbr>• 3Blue1Brown—Neural Networks + LLM Series → [https://www.3blue1brown.com/topics/neural-networks](https://www.3blue1brown.com/topics/neural-networks)\u003Cbr>Read / Study\u003Cbr>• Vercel AI SDK v6—Introduction → [https://ai-sdk.dev/docs/introduction](https://ai-sdk.dev/docs/introduction)\u003Cbr>• Vercel AI SDK v6—Next.js App Router → [https://ai-sdk.dev/docs/getting-started/nextjs-app-router](https://ai-sdk.dev/docs/getting-started/nextjs-app-router)\u003Cbr>• OpenAI Models (GPT-5 family) → [https://developers.openai.com/api/docs","cbCailiWtoNvUV6G","https://ap.wps.com/l/cbCailiWtoNvUV6G","pdf",104069,22,"English","# How to Use This Roadmap\n## API Setup—Do This Before Week 1\n# Roadmap Overview\n## Week 0 Prerequisites\n## Week 1 Understand LLMs\n## Week 2 Prompt Engineering & Structured Outputs\n## Week 3 AI Agents—Concepts & First Agent\n## Week 4 Tool Use, Function Calling & Workflows\n## Week 5 RAG—Retrieval Augmented Generation\n## Week 6 Multi-Modal—Vision & Beyond Text\n## Week 7 Multi-Provider, Evaluation & Security\n## Week 8 Ship It—Full Product (Capstone)\n# Bonus Build Your Own LLM + Courses\n## Week 1 Project: \"Explain Like I'm 5\" Bot","[{\"question\":\"How much time is recommended each day to follow the roadmap?\",\"answer\":\"The roadmap recommends 1 hour per day. Each week specifies how to split time across watching, reading, and building.\"},{\"question\":\"Which model is suggested as the default for most tasks?\",\"answer\":\"Use gpt-5-mini as the default model for learning and most tasks unless a different model is specified.\"},{\"question\":\"What is the main project goal of Week 1?\",\"answer\":\"Build an “Explain Like I'm 5” chatbot that lets users select a GPT-5 model tier and adjust response complexity, then streams the output in real time.\"}]","LLM Engineering Roadmap 2026 - 8-Week Practical Guide to Building with Large Language Models | PDF",55]