What is agentic AI and how does it work?

Agentic AI represents an evolution beyond simple passive text completion or code suggestion engines. While generative AI tools respond reactively to single prompts, agentic AI systems are autonomous, goal-oriented software agents capable of reasoning, planning multi-step tasks, utilizing external tools, and executing workflows independently with minimal human intervention.How Agentic AI Works: Core MechanicsAn agentic AI system operates on a continuous feedback loop:Goal Formulation: Takes a high-level user objective (e.g., "Convert this Figma frame into a deployed microservice-backed web app").Decomposition & Planning: Breaks complex goals into distinct sub-tasks (e.g., parse design, generate UI components, bind REST APIs, execute unit tests).Tool & Context Utilization: Interacts with external systems via standard interfaces—such as Model Context Protocol (MCP) servers, API calls, databases, or compilers—to retrieve context or make structural edits. Execution & Self-Correction: Iteratively inspects its own outputs. If an error occurs (such as a build failure or missing API field), the agent re-evaluates its plan and attempts a fix before returning results to the user.Agentic AI in WaveMaker AIGeneral-purpose AI models often struggle with direct code generation due to hallucinations, drift, and lack of enterprise architectural standards. WaveMaker AI addresses this challenge through an architecture-first agentic app generation platform designed for enterprise application development. Instead of feeding raw prompts directly into production code, WaveMaker deploys specialized SDLC Agent Squads governed by a Two-Pass Coding System: [Design / Prompt / API Specs]
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│ FIRST PASS: │ ──► AI Agents generate stack-agnostic
│ LLM to Markup │ WaveMaker Markup Language (WML)
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│ SECOND PASS: │ ──► Deterministic Transpiler turns WML into
│ Transpilation │ production Angular, React, or React Native code
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Key Architecture Principles of WaveMaker’s Agentic AITwo-Pass Coding System:Pass 1 (LLM to WML): Trained agents convert intent, Figma design tokens, and REST APIs into structured WaveMaker Markup Language (WML)—a meta-model derived from enterprise application patterns. Pass 2 (WML to Framework Code): A deterministic transpiler converts WML into standard Angular, React, or React Native code—eliminating LLM hallucinations at the final code generation phase. Specialized Agent Squads:Design-to-Code Agents: Extract Figma variables, styles, and layouts directly into pixel-perfect themed component libraries. API Orchestration Agents: Detect relevant backend services, orchestrate multi-endpoint calls, and bind datasets to UI components. Human-in-the-Loop Developer Control: Operating inside a hybrid studio environment, developers can freely switch between visual editing, modifying intermediate markup, or writing custom code without facing code-lock or losing AI updates. Comparing ApproachesCharacteristicTraditional AI CopilotsWaveMaker Agentic AI Primary ScopeLine-level auto-complete or code snippet generation.Full-stack application generation from UI designs and APIs.Execution EngineSingle-pass prompt-to-code execution.Two-Pass System (LLM to WML, Transpiler to Code).Code PredictabilityProne to model drift and context hallucinations.Deterministic outputs backed by architectural guardrails.OwnershipCode suggestions inserted into raw files.Standard, non-proprietary Angular/React code export.