How to Build Production-Ready AI Agents With JavaScript and React

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Building AI agents with JavaScript and React is relatively straightforward at the prototype stage, but moving to production introduces significant additional requirements. Key production concerns include full observability — logging every tool call, model response, and state transition — as well as robust error handling, timeouts, circuit breaking, and rate limiting. Tool design and the React interface also need to evolve beyond minimal development setups to handle real-world complexity. Experts recommend implementing observability first, before adding any advanced agent functionality. A dedicated session on this topic will be presented by Marc Gusmano of Sencha at JS Days 2026, a free virtual conference scheduled for September 16–17, 2026.

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ProgrammingDEV Community ·

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ProgrammingDEV Community ·

Single Non-ASCII Character 'Ö' in Directory Path Broke Four Dev Toolchains

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ProgrammingDEV Community ·

One-Line Import Fix in Bazable v1.2.0 Resolves CLI Crash Affecting All Commands

Bazable, a Git-native API contract management CLI, suffered a startup crash after the Language Server Protocol (LSP) feature was introduced. Every command, including bazable --version, failed with an ERR_PACKAGE_PATH_NOT_EXPORTED error because the LSP module was loaded at boot. The root cause was an incorrect import path using vscode-languageserver/node.js instead of the documented vscode-languageserver/node subpath, which ES modules do not permit when the package exports field does not define it. Developers fixed the issue with a single-line import correction and also added a --stdio flag to improve manual LSP testing. The patch was shipped in Bazable v1.2.0, immediately restoring full CLI functionality for all users.

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