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Guide 05 — From Prompt to Agent
A practical ladder from one-shot generation to bounded agentic workflows.
Six levels of AI system design, what chooses the next step at each level, and the controls each level requires.
A4 sheet — scroll sideways or pinch to zoom
Visual Guide 05 · GenAI / Agentic / Builder
From Prompt to Agent
A practical ladder from one-shot generation to bounded agentic workflows.
Healthcare AI Learning
| Level | What it is | Who chooses the next step | Typical use | Healthcare example | Main control need |
|---|---|---|---|---|---|
| 1Prompt | One request, one model response. | User or system defines the task. | One-off generation or rewriting. | Rewrite a patient-facing explanation from supplied text. | Input and output review. |
| 2LLM application | Prompt plus UI, bounded context and output formatting. | Software defines the task shape. | Repeatable single-step tasks. | Structured summarisation assistant. | Output validation and formatting rules. |
| 3Context / RAG-enabled application | Runtime retrieval supplies relevant information to the model. | Retrieval logic is defined by software. | Answers that need current, private or approved sources. | Retrieve approved guideline sections before drafting an answer. | Source allowlist, grounding checks, provenance. |
| 4Tool-enabled AI | The model or app can call defined external functions and services. | Model may select from a defined tool set. | Tasks needing data lookup, calculation or actions. | Retrieve a FHIR Observation, calculate a score, create a draft task. | Tool allowlist, permissions, argument validation. |
| 5Fixed workflow | Steps and branching are primarily predefined by software, with model or tool calls inside. | Software chooses the sequence. | Known, repeatable multi-step processes. | Intake → retrieve → summarise → validate → human review. | Deterministic sequence, checkpoints, audit trail. |
| 6Bounded agentic workflow | The system can choose and sequence at least some steps or tool use toward a goal, within explicit boundaries. | System chooses within permissions and stopping rules. | Tasks that genuinely benefit from iteration and feedback. | Gather approved context, choose allowed tools, check quality rules, escalate when required. | Permissions, stopping conditions, logging, escalation, monitoring. |
More agentic ≠ better. Use the simplest architecture that safely meets the task.
Common misconceptions
- “Tool use means it is an agent.” Not necessarily — fixed workflows use tools too.
- “A workflow is an agent.” Not necessarily — predefined steps are not self-directed.
- “An agent is fully autonomous.” Not in this learning platform’s bounded definition.
- “Multi-agent is more advanced, so better.” Not inherently; it adds failure modes.
- “Agentic systems remove human oversight.” No. Oversight and escalation stay required.
Related learning
Guides summarise the same primary sources cited in the related courses — official EU legal texts, standards bodies and peer-reviewed literature. Educational summaries only, not legal or clinical advice; regulatory dates were checked between 25 August and 10 September 2026.
Updated Sep 2026