Blog
Filter by tags:AILLMData EngineeringPythonThinking Toolsdeep learningmachine learningneural networkspytorchAI AgentsAPI IntegrationBackendCRMComputer VisionCreativityDeep LearningEmbeddingsEvaluationJIRAMachine LearningProductivitySalesforceSecurityStorageWeb DevelopmentWritingtrainingAI ApplicationsAI EngineeringAI GatewayAPIAPI ManagementASGIAgent ArchitectureAgent SkillsAgentic SystemsAgentsAnalyticsAnthropicAuthenticationAuthorizationAutomationBackend EngineeringBest PracticesCDCCNNChatbotClaudeCloud StorageCognitionDOCXData IngestionData ModelingData PipelinesData SystemsDebuggingDocument ParsingFastAPIFastHTMLFile ProcessingFile UploadFile UploadsFrameworkFundamentalsGeminiHTMXIndustrial AutomationInfrastructureJudgingKnowledge DistillationLLM JudgeLinear RegressionManufacturingModel CompressionMulti-Step ReasoningNLPNestJSOpenTelemetryPDFPerformanceProduction SystemsPrompt EngineeringPruningPydanticPydantic AIQualityQuality ControlQuantizationRAGREST APISOQLSemantic SearchSpeechStatisticsSteel IndustryTechnical ArticlesText ProcessingTool-Based AIUXValidationVector Searchactivation layerloss functions
-
Building a JIRA Chatbot: The AI-Powered Way
I spent two weeks building a JIRA chatbot that answers any question in plain English. Here's what I learned about combining JIRA's REST API withGemini, the mistakes I made, and what actually works in production.
by Harshith Rao
Subscribe via RSS or enter your email to get notified of new posts directly in your inbox