Ai Differentiator Solution Ideation

---
name: ai-differentiator-solution-ideation
description: "Ideates 3 distinct AI-native solution directions for the chosen AI differentiator need (AI wedge) through three lenses — competitor, future, and connect-the-dots — so the team doesn't fall in love with the first idea."
---

# AI Differentiator Solution Ideation

## Purpose

Prevent the most common ideation mistake: latching onto the first
solution idea that comes to mind and never comparing it against
alternatives. This skill forces the ideation of three genuinely different
AI-native solution directions for one chosen AI differentiator need (AI
wedge), using three different lenses so the directions aren't just the
same idea in different words.

## Based on

- The methodology of an external "AI-first SaaS Product" workshop,
  applied by the owner to one own case — see
  `../../references/ai-first-saas-workshop-source.md` and the worked
  example `../../cases/ai-decision-coach-mvp-case.md`, section 5. **Note:**
  applied only once so far (the owner's own case) — not broadly validated.
- The email-marketing personalization example from the workshop
  illustrates the "genuinely different" requirement: 1:1 history-based
  personalization vs. 1:1 contextual social personalization vs.
  1:group cluster-based personalization — three AI-native approaches to
  the same need (relevance), not three variations on the same idea.

## Method (draft — to be filled in further)

1. **Start from one chosen AI wedge**
   (from `../customer-vision-to-jtbd/SKILL.md`) — don't ideate for more
   than one need at a time, it breaks the comparison.
2. **Ideate solution direction 1: the competitor lens.** Ask: how do
   existing players (TTOs, incubators, generic AI tools, consultants)
   solve this need today, and what would AI make possible that ISN'T
   possible for them (scale, continuity, personalization, speed)? Goal:
   differentiation from existing competition.
3. **Ideate solution direction 2: the future lens.** Ask: how was this
   need solved BEFORE (via workshops, templates, sticky notes, frameworks
   applied solo — a heavy, energy-draining process that always has to be
   refitted to context), and how will it be solved in the FUTURE, when
   context is continuously built and taught to AI, an AI mentor asks the
   right questions to reach shared understanding, and the user is in
   continuous interaction with AI that keeps producing small building
   blocks (e.g. an ICP definition, a value proposition, a revenue-model
   hypothesis)? Goal: imagine a solution that doesn't just digitize the
   old process but changes the shape of the process itself.
4. **Ideate solution direction 3: the connect-the-dots lens.** Ask: what
   other separate tasks/activities (a+b+c+d) does this user do around
   this need that could be COMBINED into a single AI-native experience?
   Goal: a solution that emerges from combining several separate steps,
   not from speeding up one step.
5. **For each of the three directions, capture:** a name, the AI-native
   concept (2-3 sentences — how it works), the primary output for the
   user, and why it's distinctive relative to competitors/the status quo
   (not replicable with a static checklist or a generic LLM prompt).
6. **Compare the three directions side by side** in a table: core value /
   why it fits the chosen AI wedge. Resist the urge to pick right away —
   take all three to `../rice-scoring-and-mvp-synthesis/SKILL.md` for
   objective scoring before choosing.

## What this skill does NOT do

- Does not choose the MVP for you — it produces three comparable
  alternatives; the choice is made in the next skill via RICE scoring.
- Does not assess technical feasibility or build cost — only the
  distinctiveness of the concept. Feasibility/effort is assessed in
  `../rice-scoring-and-mvp-synthesis/SKILL.md`.
- Does not guarantee that all three directions are equally good —
  it deliberately also produces weaker/riskier options, so the comparison
  is genuine rather than artificial.

## Refinement notes

This skill has so far been applied to one case (the owner's own case).
As you apply it to more businesses, add:

- your own additional lenses or variations on the three lenses that have
  proven useful
- typical pitfalls (e.g. when the three directions end up too similar,
  and how to notice that)
- concrete examples from other cases in the `../../cases/` folder

Once this section has been filled in with multiple cases, raise
`skills_index.json`'s `maturity` field to `validated`
(see `../../../../meta/maturity_levels.md`).

## Continue from here

- Preceding skill in this pack: `../customer-vision-to-jtbd/SKILL.md`
  — produces the AI wedge that is ideated on here.
- Next skill in this pack:
  `../rice-scoring-and-mvp-synthesis/SKILL.md` — scores the three
  directions and selects the MVP.
- Worked example: `../../cases/ai-decision-coach-mvp-case.md`, section 5.
- The pack's shared guardrails: `../../CLAUDE.md`

## References

- `../../references/ai-first-saas-workshop-source.md` — source information
- `../../cases/ai-decision-coach-mvp-case.md` — worked example
- `../../CLAUDE.md` — the pack's shared guardrails