<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Engineering Playbook — Gen AI</title><description>Generative AI Essentials: foundations, model architectures, the foundation-model lifecycle, applications, and forward-looking reflections.</description><link>http://localhost:4321/</link><item><title>AI Safety and Alignment</title><link>http://localhost:4321/gen-ai/ai-safety-and-alignment/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/ai-safety-and-alignment/</guid><description>RLHF, constitutional AI, red-teaming, refusal training. The engineering practices behind not-shipping-something-harmful.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Intermediate</category><category>reflection</category><category>Future &amp; Ethics</category><category>safety</category><category>alignment</category><category>rlhf</category></item><item><title>Attention Is All You Need (Transformer)</title><link>http://localhost:4321/gen-ai/attention-is-all-you-need/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/attention-is-all-you-need/</guid><description>The 2017 paper that rebuilt the field. Self-attention, positional encoding, parallel training, and why this killed RNNs for language.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Advanced</category><category>architecture</category><category>Architectures</category><category>architecture</category><category>transformer</category><category>attention</category><category>foundational-paper</category></item><item><title>Audio and Music Generation</title><link>http://localhost:4321/gen-ai/audio-and-music-generation/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/audio-and-music-generation/</guid><description>Raw-waveform vs spectrogram vs token-based audio models. How MusicLM, Suno, and Udio actually produce sound.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Intermediate</category><category>application</category><category>Applications</category><category>applications</category><category>audio-generation</category><category>music</category><category>codecs</category></item><item><title>Autonomous AI Agents</title><link>http://localhost:4321/gen-ai/autonomous-ai-agents/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/autonomous-ai-agents/</guid><description>Tool use, planning, memory, multi-step loops. What&apos;s hard about turning a language model into something that takes actions.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Advanced</category><category>application</category><category>Applications</category><category>applications</category><category>agents</category><category>tool-use</category><category>planning</category></item><item><title>Bidirectional Transformers (BERT)</title><link>http://localhost:4321/gen-ai/bidirectional-transformers-bert/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/bidirectional-transformers-bert/</guid><description>Masked language modeling. How BERT became the encoder of choice for classification, retrieval, and ranking.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Advanced</category><category>architecture</category><category>Architectures</category><category>architecture</category><category>bert</category><category>masked-language-modeling</category><category>encoder-only</category><category>pretraining</category></item><item><title>Diffusion Models</title><link>http://localhost:4321/gen-ai/diffusion-models/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/diffusion-models/</guid><description>Iterative denoising as a generative process. The architecture under Stable Diffusion, DALL·E 2, and Sora.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Advanced</category><category>architecture</category><category>Architectures</category><category>architecture</category><category>diffusion</category><category>generative-modeling</category><category>denoising</category><category>latent-diffusion</category></item><item><title>The Emergence of Generative AI</title><link>http://localhost:4321/gen-ai/emergence-of-generative-ai/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/emergence-of-generative-ai/</guid><description>What changed in 2017 (attention), 2018 (GPT-1/BERT), 2020 (GPT-3 scale), and 2022 (ChatGPT, productization).</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Foundational</category><category>concept</category><category>Foundations</category><category>foundations</category><category>history</category><category>generative-models</category></item><item><title>Building Context with Neurons (RNNs)</title><link>http://localhost:4321/gen-ai/building-context-with-neurons/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/building-context-with-neurons/</guid><description>Vanilla recurrent networks: sequential context, the gradient problem, why they fail past ~50 tokens.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Intermediate</category><category>architecture</category><category>Architectures</category><category>architecture</category><category>rnn</category><category>sequence-models</category><category>foundational-paper</category></item><item><title>Encoder-Decoder Framework</title><link>http://localhost:4321/gen-ai/encoder-decoder/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/encoder-decoder/</guid><description>Sequence-to-sequence: an encoder compresses input to a fixed vector; a decoder generates output token-by-token. Translation&apos;s first real shot.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Intermediate</category><category>architecture</category><category>Architectures</category><category>architecture</category><category>encoder-decoder</category><category>seq2seq</category><category>attention</category><category>translation</category></item><item><title>The Emergence of NLP</title><link>http://localhost:4321/gen-ai/emergence-of-nlp/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/emergence-of-nlp/</guid><description>From rule-based parsers to statistical methods to neural language models — the four decades that led to ChatGPT.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Foundational</category><category>concept</category><category>Foundations</category><category>foundations</category><category>history</category><category>nlp</category></item><item><title>Evaluating Large Language Models</title><link>http://localhost:4321/gen-ai/evaluating-llms/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/evaluating-llms/</guid><description>Perplexity, MMLU, HumanEval, helpfulness ratings, holistic evals. Why every benchmark is wrong and you still need them.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Intermediate</category><category>concept</category><category>Foundation Models</category><category>evaluation</category><category>benchmarks</category><category>eval-harness</category><category>llm-as-judge</category></item><item><title>Generative Pretraining (GPT)</title><link>http://localhost:4321/gen-ai/generative-pretraining-gpt/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/generative-pretraining-gpt/</guid><description>Causal language modeling at scale. The architectural choice that turned a language model into a general-purpose tool.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Advanced</category><category>architecture</category><category>Architectures</category><category>architecture</category><category>gpt</category><category>decoder-only</category><category>causal-lm</category><category>pretraining</category></item><item><title>The Future of Generative AI</title><link>http://localhost:4321/gen-ai/future-of-generative-ai/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/future-of-generative-ai/</guid><description>Where the field is heading in 2026 — agents, reasoning, on-device, multimodality, and the compute wall everyone is staring at.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Foundational</category><category>reflection</category><category>Future &amp; Ethics</category><category>future</category><category>trends</category><category>reflection</category></item><item><title>Hallucinations and the Evaluation Problem</title><link>http://localhost:4321/gen-ai/hallucinations-and-evaluation/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/hallucinations-and-evaluation/</guid><description>Why models confidently make things up, what causes it, what reduces it, and how to measure progress on a moving target.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Intermediate</category><category>reflection</category><category>Future &amp; Ethics</category><category>hallucination</category><category>evaluation</category><category>reliability</category></item><item><title>Large Language Models at Scale</title><link>http://localhost:4321/gen-ai/llms-at-scale/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/llms-at-scale/</guid><description>Scaling laws, compute budgets, emergent capabilities, and the cost shape that determines who can train frontier models.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Advanced</category><category>concept</category><category>Foundation Models</category><category>scaling-laws</category><category>compute</category><category>emergent-capabilities</category><category>training-cost</category></item><item><title>How Do Models Learn?</title><link>http://localhost:4321/gen-ai/how-do-models-learn/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/how-do-models-learn/</guid><description>Gradient descent, backpropagation, loss functions, and the optimization loop. The engine under every neural network.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Foundational</category><category>concept</category><category>Foundation Models</category><category>optimization</category><category>gradient-descent</category><category>backpropagation</category><category>training-loop</category></item><item><title>Multimodal Models</title><link>http://localhost:4321/gen-ai/multimodal-models/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/multimodal-models/</guid><description>Text + image + audio in one model. CLIP, Flamingo, Gemini, GPT-4o — how cross-modal alignment actually works.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Intermediate</category><category>concept</category><category>Foundation Models</category><category>multimodal</category><category>vision-language</category><category>cross-modal</category><category>clip</category></item><item><title>Post-Training, Fine-Tuning, and Adaptation</title><link>http://localhost:4321/gen-ai/post-training-fine-tuning/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/post-training-fine-tuning/</guid><description>Supervised fine-tuning, RLHF, DPO, LoRA, prompt-tuning. How a pretrained model becomes a product.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Intermediate</category><category>concept</category><category>Foundation Models</category><category>fine-tuning</category><category>rlhf</category><category>dpo</category><category>lora</category><category>post-training</category></item><item><title>Model Optimization for Deployment</title><link>http://localhost:4321/gen-ai/model-optimization-for-deployment/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/model-optimization-for-deployment/</guid><description>Quantization, distillation, pruning, KV-cache reuse, speculative decoding. The serving-cost levers that decide unit economics.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Advanced</category><category>concept</category><category>Foundation Models</category><category>inference</category><category>quantization</category><category>distillation</category><category>kv-cache</category><category>speculative-decoding</category></item><item><title>Pretraining Paradigms</title><link>http://localhost:4321/gen-ai/pretraining-paradigms/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/pretraining-paradigms/</guid><description>Causal vs masked vs contrastive vs span-corruption. The objective you pick determines what the model is good at.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Intermediate</category><category>concept</category><category>Foundation Models</category><category>pretraining</category><category>objectives</category><category>self-supervised</category><category>transfer-learning</category></item><item><title>Prompt Engineering</title><link>http://localhost:4321/gen-ai/prompt-engineering/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/prompt-engineering/</guid><description>Templates, role / system prompts, few-shot, chain-of-thought, and the prompt patterns that survive contact with production.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Foundational</category><category>application</category><category>Applications</category><category>applications</category><category>prompting</category><category>llm-patterns</category></item><item><title>Text Preprocessing Essentials</title><link>http://localhost:4321/gen-ai/text-preprocessing-essentials/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/text-preprocessing-essentials/</guid><description>Tokenization, stemming, lemmatization, normalization. The unglamorous foundation under every text model.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Foundational</category><category>concept</category><category>Foundations</category><category>foundations</category><category>preprocessing</category><category>tokenization</category></item><item><title>Reconstructing Context with Sequence Models (LSTM / GRU)</title><link>http://localhost:4321/gen-ai/reconstructing-context-with-sequence-models/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/reconstructing-context-with-sequence-models/</guid><description>Gated memory cells. How LSTMs and GRUs extended the useful context window from tens to hundreds of tokens.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Intermediate</category><category>architecture</category><category>Architectures</category><category>architecture</category><category>lstm</category><category>gru</category><category>sequence-models</category><category>gated-rnn</category></item><item><title>Retrieval-Augmented Generation (RAG)</title><link>http://localhost:4321/gen-ai/retrieval-augmented-generation/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/retrieval-augmented-generation/</guid><description>Vector stores, chunking, hybrid retrieval, reranking, and the eval harness that tells you whether your RAG actually works.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Intermediate</category><category>application</category><category>Applications</category><category>applications</category><category>rag</category><category>retrieval</category><category>vector-search</category></item><item><title>Text-to-Image Generation Systems</title><link>http://localhost:4321/gen-ai/text-to-image-systems/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/text-to-image-systems/</guid><description>From prompt to pixels: CLIP-guided diffusion, latent diffusion, ControlNet, the prompt-to-output pipeline at production scale.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Intermediate</category><category>application</category><category>Applications</category><category>applications</category><category>image-generation</category><category>diffusion</category><category>controlnet</category></item><item><title>Text-to-Speech Generation Systems</title><link>http://localhost:4321/gen-ai/text-to-speech-systems/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/text-to-speech-systems/</guid><description>Neural TTS, voice cloning, prosody, the streaming-audio pipeline. What real-time voice products are actually doing.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Intermediate</category><category>application</category><category>Applications</category><category>applications</category><category>tts</category><category>speech</category><category>voice-cloning</category></item><item><title>Text-to-Text Generation Systems</title><link>http://localhost:4321/gen-ai/text-to-text-systems/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/text-to-text-systems/</guid><description>Summarization, translation, rewriting, structured extraction. The bread-and-butter applications and how they&apos;re served.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Foundational</category><category>application</category><category>Applications</category><category>applications</category><category>text-generation</category><category>summarization</category><category>translation</category></item><item><title>Text-to-Video Generation Systems</title><link>http://localhost:4321/gen-ai/text-to-video-systems/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/text-to-video-systems/</guid><description>Frame coherence, motion priors, and the compute shape that makes video generation orders-of-magnitude harder than images.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Advanced</category><category>application</category><category>Applications</category><category>applications</category><category>video-generation</category><category>diffusion</category><category>motion-priors</category></item><item><title>The Way Forward</title><link>http://localhost:4321/gen-ai/the-way-forward/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/the-way-forward/</guid><description>What to learn next, in what order, and how to keep up when the field reinvents itself every six months.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Foundational</category><category>reflection</category><category>Future &amp; Ethics</category><category>future</category><category>career</category><category>learning</category></item><item><title>Vectorizing Language</title><link>http://localhost:4321/gen-ai/vectorizing-language/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/vectorizing-language/</guid><description>From bag-of-words to word2vec to contextual embeddings. How text becomes math a model can manipulate.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Foundational</category><category>concept</category><category>Foundations</category><category>foundations</category><category>embeddings</category><category>representations</category></item><item><title>Vision Models (CNN → ViT)</title><link>http://localhost:4321/gen-ai/vision-models/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/vision-models/</guid><description>From convolutional layers to vision transformers. How images became sequences and joined the transformer party.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Intermediate</category><category>architecture</category><category>Architectures</category><category>architecture</category><category>cnn</category><category>vit</category><category>vision-transformer</category><category>image-models</category></item><item><title>What Are Foundation Models?</title><link>http://localhost:4321/gen-ai/what-are-foundation-models/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/what-are-foundation-models/</guid><description>Large, broadly-pretrained models that serve as starting points for many downstream tasks. The reusable substrate of modern AI.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Foundational</category><category>concept</category><category>Foundation Models</category><category>foundation-models</category><category>pretraining</category><category>transfer-learning</category><category>scale</category></item><item><title>What Is Generative AI?</title><link>http://localhost:4321/gen-ai/what-is-generative-ai/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/what-is-generative-ai/</guid><description>The shift from discriminative to generative models — what changed between 2017&apos;s transformer paper and today&apos;s foundation-model era.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Foundational</category><category>concept</category><category>Foundations</category><category>foundations</category><category>generative-models</category><category>history</category></item><item><title>Why Learn Generative AI</title><link>http://localhost:4321/gen-ai/why-learn-gen-ai/</link><guid isPermaLink="true">http://localhost:4321/gen-ai/why-learn-gen-ai/</guid><description>The engineer-shaped case for understanding generative models from first principles, not just calling APIs.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><category>Foundational</category><category>concept</category><category>Foundations</category><category>foundations</category><category>career</category><category>mental-models</category></item></channel></rss>