AI LANDSCAPE EVOLUTION
2023	2024	2025
Core Themes - Foundational Model Scaling - Prompt Engineering - Transfer Learning - Explainability Begins	Core Themes - Prompt Tuning & RLHF - LLMOps Maturity - Multi-agent Coordination - Open-weight Models	Core Themes - DPO - Self-Reflection - Human-in-the-Loop - Long-Horizon Reasoning
Tooling Focus - Hugging Face Transformers - OpenAI API - Weights & Biases - Early LangChain	Tooling Focus - LangChain, AutoGPT - MLflow, Ray Serve - OpenLLM, BentoML	Tooling Focus - trl.eval, Chatbot Arena - Agent Toolchains - LangGraph, CrewAI, AutoGen
Risks & Concerns - Hallucination - Bias & Fairness - Data Leakage - Regulatory Uncertainty	Risks & Concerns - Explainability - Jailbreaks & Misuse - Dataset Provenance	Risks & Concerns - Alignment & Observability - Causality Limits - Model Autonomy - Overfine-tuning Collapse
Learning Modes - Few-shot - Zero-shot - Self-supervised	Learning Modes - Instruction Tuning - RLHF Loops - Dataset Curation	Learning Modes - Active Learning - Self-Reflective Training - Multi-Agent Eval
Takeaway Accessibility and capability via large models and prompts	Takeaway Customization & optimization for task-specific utility	Takeaway Governance, trust, and structured evaluation at scale