@daraladje Design Thinking Process is as follows:
Frame a Question
Gather Inspiration
Generate Ideas
Make Ideas Tangible
Test to Learn
Share the Story
https://t.co/YloCSmzBKH
For people who keep asking what to build in AI Engineering
> Build your own Reasoner (Chain of Thought implementation)
> Build your own Agent loop (ReAct pattern)
> Build your own Inference Server (in C++/Rust)
> Build your own Transformer from scratch (Attention is all you need)
> Build your own Vector Database (HNSW index)
> Build your own RAG pipeline
> Build your own Flash Attention kernel (CUDA)
> Build your own Quantization library (Int8/FP4 implementation)
> Build your own Mixture of Experts (MoE) routing layer
> Build your own Distributed training loop (FSDP/Tensor Parallelism)
> Build your own KV Cache paging system (like vLLM)
> Build your own Speculative Decoding system
> Build your own State Space Model (Mamba implementation)
> Build your own RLHF pipeline (PPO implementation)
> Build your own Small Language Model (SLM)
> Build your own Matrix Multiplication kernel
> Build your own LoRA (Low-Rank Adaptation) trainer
> Build your own Code interpreter sandbox
> Build your own DPO (Direct Preference Optimization) loss function
> Build your own Graph RAG system
> Build your own Model merger (Model Soups/Spherical Linear Interpolation)
> Build your own Interpretability tool (SAE - Sparse Autoencoders)
> Build your own Synthetic data generator
> Build your own Function Calling router
> Build your own Structured Output parser (Context Free Grammars)
> Build your own Multi-modal projector (CLIP implementation)
> Build your own LLM Eval harness
> Build your own Guardrails system (Input/Output filtering)
> Build your own Prompt caching mechanism
> Build your own Tokenizer (BPE implementation)
> Build your own Autograd engine (like Micrograd)
> Build your own Diffusion model (UNet + Scheduler)
> Build your own Vision Transformer (ViT)
> Build your own Whisper-style ASR model
> Build your own Text-to-Speech pipeline
> Build your own Semantic Router
> Build your own Knowledge Graph builder
> Build your own Data curation pipeline (MinHash/Deduplication)
> Build your own AI Gateway (Load balancing/Failover)
> Build your own Parameter Efficient Fine-Tuning (PEFT) library
> Build your own Text-to-SQL engine
> Build your own Recommendation system (Two-tower architecture)
> Build your own Embedding model
> Build your own Logit Processor
> Build your own Softmax kernel optimization
> Build your own Adversarial attack generator
> Build your own Audio Spectrogram transformer
> Build your own Neural Architecture Search
> Build your own Model Distillation pipeline
> Build your own Feature Store
> Build your own Database driver (for Vectors)