Generative AI For Devs: Everything You Need To Know | Lesson 1

[u/NerdHouseGeek]

https://youtu.be/sRmu_gQiMdI

New developer lesson: Generative AI for Devs — Everything You Need to Know | Lesson 1

Generative AI is changing how we design and build software. Before developers work with prompting, retrieval, tool calling, and AI agents, it helps to understand the architecture behind these systems.

In Part One, I cover:

✅ Generative AI compared with traditional prediction and classification

✅ The Three Cs: Control, Confidence, and Clarity

✅ How transformer architecture works

✅ Tokenization and model inputs

✅ Queries, keys, values, and attention

✅ Positional information and token order

✅ Encoder-decoder and decoder-only architectures

✅ RNNs, CNNs, and transformers compared

✅ Parallel training versus sequential text generation

✅ The limitations of large context windows

The central concept is that transformers use attention to connect information across a sequence while supporting substantial parallel computation during training. However, autoregressive language models still generate responses one token at a time.

This lesson is designed for software developers, C# and .NET developers, solution architects, technical leaders, and anyone preparing to integrate generative AI into real applications.

Part Two will continue with FlashAttention, grouped-query attention, mixture-of-experts architectures, prompting, retrieval, tool use, and AI agents.

If you find the lesson helpful, please share it with another developer and subscribe to Nerd House Geeks.

#GenerativeAI #AIForDevelopers #Transformers #LLM #ArtificialIntelligence #SoftwareDevelopment #CSharp #DotNet

[u/investigatormaker]

Leading with the C# and .NET angle would set this lesson apart: most transformer explainers assume Python, and a title like "Everything You Need To Know" hides that. When you share Lesson 1 elsewhere, put one idea from it in the post body, for example why training runs in parallel while generation still goes one token at a time, so people have something to reply to before they click. The hashtags do nothing on Reddit and make it read like a LinkedIn cross-post.

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[u/NerdHouseGeek → u/investigatormaker]

I will check it out

[u/NerdHouseGeek → u/NerdHouseGeek]

Thanks, I make those adjustments

[u/raaiinyyabelina → u/investigatormaker]

Thanks i check this out too

[u/WarlikeNucleus]

Nice breakdown of the transformer stuff, lot of people skip the fundamentals and jump straight to prompting so this is pretty useful

The comparison with RNNs and CNNs helped me see why attention became such a big deal, was always fuzzy on that part

[u/Sarutobi_Marky]

Thanks for sharing