Suggested prompts in the empty AI state
Seed the blank AI box with realistic starter prompts so users can borrow a good first move instead of freezing at an empty input.
Why this can grow a startup
Blank inputs ask the user to do product design in public. They have to imagine what the AI can do, translate that into a prompt, and take the risk of looking wrong if the product disappoints. Suggested prompts remove that cognitive tax. They turn the first session into selection instead of invention, teach the shape of good requests, and give the product more chances to create an early success that users can then adapt to their own work.
Source-backed example
PostHog added prompt suggestions after seeing users open Max AI, stare at the empty box, and forget the kinds of product questions the assistant could actually answer.
Source-reported evidence
Source: PostHog Newsletter · Browse PostHog Newsletter tactics
PostHog says suggested prompts helped counter the common empty-box failure mode where users felt intimidated and forgot possible use cases.
Attributed to the cited source; GrowthDex has not independently verified it. Use this as context, not as a forecast, benchmark, or recommended target.
Evidence scope: claims and metrics are attributed to the linked source; GrowthDex has not independently replicated the reported result. Check the original context and validate fit before applying it. Read the evidence methodology.
Source discovered: May 26, 2026
When to use it
Use this when Onboarding, Activation, Retention is relevant to ai products, activation, ux and you can run a bounded test with a free budget.
When not to use it
Do not use it as a substitute for customer evidence, a clear owner, or a measurable stop condition. Local platform rules and market behavior still need checking.
How to do it
- Choose one target segment and define the exact next action this tactic should prompt.
- Adapt the tactic to Onboarding and Activation, using evidence from PostHog Newsletter as context—not as a promised result.
- Record a baseline for: Share of target users completing the product's first-value action. Set a guardrail that would make you pause the test.
- Run a narrow pilot and choose a test window that fits the normal decision or use cycle; do not scale before you have observed the full cycle.
- Compare the signal with its baseline. Scale only if the intended action improves without crossing the guardrail; otherwise revise one variable or stop and record what you learned.
Compare a stack for your situation
Compare source-backed tactics against your product, stage, budget and channel strengths, then choose one experiment to test.
Explore the context
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Apply this with an operator
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