Agentic Workflow

Most reliable production systems labelled as agents are actually agentic workflows. Rather than handing a model a goal and twenty tools in an unconstrained loop, engineers decompose the business process into explicit nodes and edges using orchestration frameworks or state machines. Deterministic code handles control flow, retries, and schema validation, while language models are invoked at specific nodes that require judgement, synthesis, or unstructured data extraction.

Common design patterns inside an agentic workflow include prompt chaining (breaking a task into sequential stages), routing (classifying an input and sending it to a specialised sub-pipeline), parallelisation (running multiple retrieval or evaluation passes concurrently), and evaluator-optimiser loops (where a second model call critiques a draft against a rubric and triggers a revision if checks fail).

Consider a Bristol insurance claims processor handling commercial property claims. The workflow first runs an OCR and extraction node over uploaded loss-adjuster PDFs, routes claims above £25,000 to a policy-exclusion check against the underwriting database, runs a critic node to verify every cited policy clause exists verbatim, and outputs a structured JSON dossier to the claims handler's queue.

Agentic workflows give engineering teams the capability gains of iterative AI reasoning without sacrificing production observability or budget predictability. Because the state graph is fixed in code, teams can unit-test individual nodes, set hard caps on loop iterations, mix cheap small language models for classification with frontier reasoning models for synthesis, and satisfy compliance auditors who demand explainable decision paths.

The trade-off is upfront engineering effort and lower flexibility on edge cases that fall outside the pre-designed graph. If the task domain is highly unstructured, such as exploratory codebase debugging or open-ended market research, a rigid workflow will brittlely fail on unanticipated states, making a more dynamic AI agent with tool-selection freedom the better fit.