This topic covers the practical frameworks, SDKs and platform APIs used to build, run and operate LLM-powered developer agents and integrations in production. It focuses on agent frameworks that standardize model access, orchestration, observability and governance so teams can move from prototypes to reliable services. Key approaches include developer-first SDKs (LangChain) for composing agent pipelines and tooling; IDE-embedded assistants and agent workflows (GitHub Copilot, Cursor, Windsurf) that keep AI in the developer loop; enterprise, private or self-hosted coding assistants (Tabnine) for data governance and security; no-code/low-code agent builders (MindStudio) to accelerate iteration; web-native platforms with hosting and agents (Replit); and quality- and SDLC-focused tools (Qodo) for review, test generation and compliance. Relevance in 2026 stems from two converging needs: teams adopting multi-model and agentic architectures in production, and enterprises demanding observability, access controls and testable workflows. Successful production integrations now prioritize standardized model interfaces, multi-agent orchestration, CI/CD-friendly testing, and the ability to run models or toolchains in private environments. Trends reflected across the tools include increased support for multi-model stacks and cascade agents (Windsurf), deeper IDE and CLI integration for developer productivity (Copilot, Cursor), visual agent design and operational controls for non-engineering stakeholders (MindStudio), and automated code-quality and governance checks across repositories (Qodo, Tabnine). For practitioners, this topic helps compare where to invest: open SDKs and orchestration frameworks when customizability matters, managed IDE/assistant products for day-to-day developer productivity, and specialist platforms for governance, testing and self-hosting when compliance and scale are priorities.