Agentic Workflows
Agentic workflows are multi-step processes where an AI system plans, executes, and iterates on tasks with minimal human intervention between steps. Unlike a single prompt-response exchange, an agentic workflow might involve the AI researching a topic, drafting a document, reviewing it against criteria, revising, and publishing—each step informed by the results of the previous one. The appeal is obvious: you describe the outcome and the system figures out the steps. The risk is equally obvious: errors compound across steps, and the system may confidently execute a plan that was wrong from step two. Production agentic workflows in 2025 tend to be narrowly scoped with clear checkpoints—processing invoices, triaging support tickets, generating reports from structured data. The fully autonomous AI employee that handles ambiguous, high-stakes work without oversight remains aspirational. Building reliable agentic workflows is less about model capability and more about designing the right guardrails, evaluation criteria, and fallback paths.
Related terms:
Agentic AI
Agentic AI refers to systems that autonomously pursue goals—planning actions, employing tools, and adapting based on feedback—without waiting for human instructions at every step. Unlike passive AI that only responds when prompted, agentic AI can monitor systems, diagnose issues, and propose fixes on its own.
Accretive Software
Accretive software refers to AI platforms that automatically absorb model improvements as margin expansion by treating models as interchangeable components and routing queries to the optimal model in real time. Rather than fighting obsolescence, these platforms convert every efficiency breakthrough into customer value or profit margin.
Structured Output
Structured output occurs when a language model returns data in predictable, machine-readable formats—such as JSON, XML, or typed objects—rather than free-form prose, enabling software systems to reliably parse fields like names, dates, and dollar amounts. By using constrained generation to enforce a JSON schema, structured output transforms AI from a conversational interface into a dependable system component.