AI agents

Important Developer Trends for 2023 (View Older or Newer)

Rank	Trend	Score	Change	Components	Recent scores
#1	LLM Large language models are the core reasoning and interaction layer for most AI-agent products and runtimes.	79.3	+4	Strategic 85 Adoption 42 · Attention 100 · Momentum 100	54 · 56 · 56 · 56 · 59 · 59 · 56 · 79
#2	AI Agents AI-powered autonomous agents and agentic frameworks are the core product category of this space, directly shaping runtime, orchestration, tooling, security, and deployment decisions.	76.7	-1	Strategic 84 Adoption 33 · Attention 100 · Momentum 92	67 · 63 · 67 · 59 · 69 · 71 · 68 · 77
#3	RAG Retrieval-augmented generation is a core pattern for giving agents grounded access to private, changing, and domain-specific knowledge.	75.1	+10	Strategic 78 Adoption 42 · Attention 100 · Momentum 100	49 · 49 · 49 · 49 · 52 · 56 · 50 · 75
#4	Observability Observability and distributed tracing are core to developing, debugging, evaluating, and operating agentic workflows, especially when agents invoke tools, models, and other services across multiple steps.	70.6	—	Strategic 76 Adoption 25 · Attention 100 · Momentum 100	48 · 51 · 46 · 51 · 46 · 51 · 57 · 71
#5	Vector Search Vector search is a durable building block for agent memory, retrieval-augmented generation, semantic tool and document discovery, and context management.	69.1	—	Strategic 68 Adoption 42 · Attention 100 · Momentum 100	46 · 48 · 46 · 46 · 50 · 49 · 45 · 69

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