We need re-learn what AI agent development tools are in 2026

In 2025, the landscape of AI agent development underwent significant changes with the commoditization of key capabilities such as RAG, memory, and evaluations, and the integration of document context into most vendors' offerings, signaling a shift in industry expectations. OpenClaw caused a stir by adopting and later discarding the MCP security strategy, highlighting the volatility in AI security measures. Large language models (LLMs) like ChatGPT and Claude have incorporated features like web search and project management, which once required explicit orchestration but are now standard in LLM services. The evaluation framework for AI agent builders is due for a revamp, focusing on 'enterprisiness' and codability while dropping integrability as an axis, reflecting a move toward enterprise-ready deployments with enhanced security and reliability measures. Vendors have been adapting to this rapidly evolving market by acquiring certifications and expanding their feature sets, with large providers entering the visual no-code agent development space, pushing both startups and established companies to innovate quickly to remain competitive.

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