3 So What's
v.29
A conversational agent that guides users through the 3 So What Technique - A structured approach to drive outcome-focused thinking and ensure actions, insights, or ideas are connected to meaningful and strategic objectives. By asking "So What?" three times, you challenge surface-level observations and force a deeper analysis of implications and value.
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Share a recent decision, action, or idea you're excited about
I just built a no code GenAI tool
So what impact does building a no code GenAI tool have?
It turns AI from something you buy into something you build.
So what difference does it make if AI is something you build rather than buy?
Buying AI locks you into someone else’s assumptions. Building it means your competitive edge comes from how well you know your users—and how fast you can ship.
So what if your competitive edge comes from how well you know your users and how fast you can ship?
Then you need tools that move at your speed. Building AI means you’re not waiting for roadmap updates—you’re shipping your own.
Output
## Ultimate Outcome Summary **You've shifted from being a consumer of AI to a
producer of AI solutions.** This fundamental change means your competitive
advantage now lies in your ability to rapidly iterate and deploy AI tools that
perfectly match your users' needs, rather than being constrained by vendor
roadmaps and generic solutions. ## Potential Actions to Maximize Impact ### 1.
**Establish a Rapid Iteration Framework** - Set up continuous deployment
pipelines for your AI tools - Create feedback loops with users for
weekly/bi-weekly improvements - Build modular components that can be quickly
recombined for new use cases ### 2. **Develop Deep User Intelligence** -
Implement comprehensive user behavior tracking within your AI tool - Conduct
regular user interviews to understand evolving needs - Create user personas
specific to AI tool usage patterns ### 3. **Build a No-Code AI Toolkit** -
Document and systematize your building process - Create templates and frameworks
for rapid AI tool development - Establish a library of reusable AI components ##
Ways to Measure the Outcome ### Speed Metrics - **Time-to-market**: Days from
idea to deployed AI feature (target: <7 days) - **Iteration velocity**: Number
of meaningful updates shipped per month - **Feature request fulfillment**: Time
from user request to implementation ### Competitive Advantage Metrics - **User
retention**: Monthly/quarterly retention rates compared to off-the-shelf AI
tools - **Feature differentiation**: Percentage of features that are unique to
your solution - **User satisfaction**: Net Promoter Score specifically for AI
functionality ### Business Impact Metrics - **Cost per AI capability**: Compare
building vs. buying costs over time - **Revenue attribution**: Revenue directly
tied to custom AI features - **Market responsiveness**: Time to adapt to new
market opportunities vs. competitors The key is measuring not just what you
built, but how much faster and more precisely you can respond to opportunities
than those dependent on vendor solutions.