• Introduction

Suggestion

The offer of a system-generated recommendation that the actor can accept, modify, or reject, balancing automation with agency.

Input assistance

Conversation

Clues for what’s possible and what to do next.

Form

Auto-completion and smart defaults reduce cognitive load and prevent errors.

Form element

Individual form fields can provide contextual suggestions as users interact with them.

Suggesting relationships

The system can identify and propose connections between data points that users might not have considered.

Proposing solutions

Intelligent recommendations for actions or workflows based on current context and user patterns.

Certainty

Suggestions should communicate their confidence level to help users make informed decisions.

Adjustment

Users should be able to refine or modify suggestions to better match their needs.

Limitations

Fixation risk

Providing explicit suggestions can constrain creative exploration through fixation effects:

  • Users anchor to AI-generated examples rather than exploring alternatives
  • Ideas homogenise as multiple users converge on similar AI-suggested approaches
  • Diversity decreases even when users generate initial ideas before seeing suggestions
  • Lower elaboration depth compared to question-driven approaches (65% minor elaboration, 25% no elaboration in suggestion-based dialogue vs 55% substantive elaboration in question-driven)

Research shows suggestion-based dialogue reduces both individual creativity and collective diversity (Maier et al. 2025). The effect occurs because concrete examples limit the solution space users consider, even when suggestions are high quality.

Mitigation strategies:

  • Use question-driven scaffolding or ambiguous analogies that leave interpretive space for human creativity rather than concrete examples
  • Delay suggestions until after initial ideation to reduce anchoring
  • Present suggestions as inspiration rather than recommendations
  • Provide diverse suggestion sets from different conceptual domains
  • Consider whether the task benefits more from exploration (use questions) or optimisation (use suggestions)

See Conversation dialogue forms for alternative interaction patterns that preserve diversity and elaboration depth.

Dismission and override

Users must have clear paths to reject suggestions and provide alternative input.

Resources & references

Related patterns

Precedes

Enacts

  • Adaptability — suggestions might sharpen on the actor's accepted-or-rejected signal, fitting their patterns over time
  • Formality — suggestions ease the step from informal intent to formal expression, formalising by recognition rather than recall
  • Agency — the system proposes and the actor disposes; accept, modify, or reject keeps the final say with the user

Complements

  • AI completion — AI completion is a suggestion mechanism; fixation risk and dismissal apply directly
  • Autocomplete — system-generated recommendations more broadly
  • Autofill — autofill as a form of implicit recommendation
  • Collaboration — Suggestions support collaborative decision-making through AI-assisted discovery
  • Dynamic hyperlinks — suggested actions and connections
  • Searching — "did you mean?" and related patterns that guide query formulation
  • Template
  • Transparent reasoning — can emerge from the visible reasoning process.

Tangentially related

Alternatives

  • Conversation — dialogue forms that provide alternatives to suggestion-based interaction

Related

  • Good defaults — A weaker form of default ("Did you mean X?") or a dynamic default
  • Inline interface — recommendations the actor can accept, modify, or reject in the flow.
  • Assistance — providing likely next actions and narrowing the option space
  • Delegation — agent might suggest opportunities it believes will help

Preceded by

Instantiated by