Guidely

For anyone who's ever felt overwhelmed or lost in the fast moving AI space... Welcome to Guidely!

Trying to break into AI engineering in 2026, but not sure where to start? We’ve put together a clear, practical roadmap based on how AI engineering is actually done in the real world. We hope it gives you the direction you need. Link to full roadmap: guidely.tech/blog/ai-vs-mac…

Every powerful AI model today is built on this simple learning loop! 👇🏾 It starts with random guesses. Then repeats: → Input → Predict → Compare → Measure error → Adjust weights Again and again, millions of times. Tiny updates → better predictions → patterns emerge.

Correct link: guidely.tech/blog/ai-engine…

The biggest misconception about Generative AI(ChatGPT, Claude, etc.)? People think it's creating, but that's not true! In reality, it’s just predicting the next thing. Here is how: Link to the full video: youtube.com/watch?v=72yyLA…

What we call AI today didn't just appear overnight. It's been in the works for years, evolving over time: From Classical AI (Think expert systems) → Machine Learning → Neural Networks → Deep Learning → Generative AI → And now Agentic AI. What do you think is next?

You’ve probably used ChatGPT quite a bit by now. But OpenAI has built a broader ecosystem of tools. So we put together a quick overview of a few interesting ones. What they do, and where you can use them. Which OpenAI tool do you find yourself using the most? #LLMs

How do you explain neurons in neural networks to a five-year-old? Think of a neuron as a chef in a restaurant. - Ingredients come in. These are the inputs. - The chef mixes them in specific quantities. These are the weights. - The chef adds a personal touch. That is the bias.

Full video out now! Watch and please share with anyone who might find it useful. Thank you! youtube.com/watch?v=72yyLA… #ArtificialInteligence #machinelearning #LLMs #GenerativeAI

Hiiii! 🤩 As promised, we've worked on a little surprise YT video for you. The longer version of this video is dropping tomorrow! Are you as excited as we are for the main release? Please don't forget to engage and subscribe! 🙏🏾 youtube.com/watch?v=rUtAiU…

What does a weight do in a neural network? It decides how much an input matters. → Big positive weight = push output up → Big negative weight = push it down → Near zero = ignore it Read the blog here: guidely.tech/guides/neural-… #machinelearning #neuralnetwork

A teaser for you! Full video drops on the 27th, 7 days from today! #ArtificialIntelligence #machinelearning

Hiii! 😁 👋🏾 We've been working really hard on our debut long-form YouTube video, and we've made significant progress. The project release date will be announced by the end of the week. In the meantime, can you guess what the video will be about from these random frames?

@Akasheth_ Depends on the use-case

Which do you prefer for backend? Node js Django

@BharukaShraddha Thank you for sharing! Additionally, I recommend going back to the beginning and starting with Math: Linear Algebra & Calculus. Followed by Neural networks, then transformers.

Most people use LLMs. Very few actually understand how they work under the hood. If you want to go from prompt user → real AI engineer, study these 9 concepts in order: 1️⃣ Transformers — attention, tokens, self-attention basics t.co/5YmBhXQrpu 2️⃣ Transformer tricks — what makes them stable & scalable t.co/QFvPbLVuMt 3️⃣ From Transformers → LLMs — how scale changes behavior t.co/1mbXcogTGF 4️⃣ LLM training — where “intelligence” actually emerges t.co/4PnlOTPjbT 5️⃣ Instruction tuning & alignment — why fine-tuning matters t.co/r5XbxsJvpu 6️⃣ LLM reasoning — why models fail + what improves them t.co/0wzxbMtIIk 7️⃣ Agentic LLMs — models that plan, call tools, and act t.co/oG0VaEWqp0 8️⃣ LLM evaluation — measure beyond demos & vibes t.co/nLtvJW4n6W 9️⃣ What’s next — trends that actually matter Bookmark this. Study step-by-step. Your prompts will level up — and so will your builds. CC: Author

Given the success of the data-engineer-handbook, we’ve released a brand new open source GitHub repo called the ai-engineer-handbook! This repo has all the projects, newsletters, and creators you need to follow to stay up to date in AI! If there’s anything missing, please open a pull request and we will review it! Let’s crowd source this material together to stay up to date! Link: lnkd.in/gVkWyCp9 Make sure to join our free vibe coding challenge on February 21st and 22nd. We will be building a full fledged SaaS product: learn.dataexpert.io

@EcZachly Very useful! Thank you for sharing!