---
id: "concept-build-to-learn"
type: "concept"
source_url: "https://hbr.org/2024/12/how-to-create-value-systematically-with-gen-ai"
source_title: "How to Create Value Systematically with Gen AI"
source_timestamps: ["§ Putting the Pyramid into Practice"]
tags: ["rapid-prototyping", "agile", "execution"]
related: ["framework-half-day-prototyping", "contrarian-no-complex-infrastructure"]
definition: "A rapid prototyping approach where teams build functional Gen AI solutions in 90 minutes using existing tools to immediately demonstrate value and accelerate organizational learning."
enrichment_confidence: "high"
sources: ["spine"]
sourceVaultSlug: "hbr-seg-spine"
originDay: 1
articleStem: "hbr-nm-98-create-value-systematically-genai"
sourceUrl: "https://hbr.org/2024/12/how-to-create-value-systematically-with-gen-ai"
sourceTitle: "How to Create Value Systematically with Gen AI"
---
# Build to Learn Prototyping

**Build to Learn** is a rapid execution methodology for Gen AI initiatives that prioritizes immediate, low-fidelity prototyping over prolonged strategic planning or complex infrastructure development.

Within the authors' [[framework-half-day-prototyping]] workshop, "Build to learn" is the third phase and occupies **90 minutes**. During that window, cross-functional teams take high-priority use cases and build working prototypes that demonstrate transformational value using only existing, off-the-shelf enterprise tools (e.g., ChatGPT or Microsoft Copilot).

The premise is that interacting with a functional — if rudimentary — AI prototype generates more organizational learning and momentum than theoretical discussion. It proves transformational AI value can be unlocked **without** waiting for massive IT overhauls, which is exactly the contrarian position argued in [[contrarian-no-complex-infrastructure]] and the feasibility claim [[claim-half-day-transformation]]. The methodology depends on prerequisite [[prereq-existing-enterprise-ai]] (teams must already have access to foundational tools) and is enacted via [[action-run-half-day-prototype]].

**Enrichment / validation.** "Build to learn" is best understood as a GenAI-specific adaptation of well-established agile innovation practices — Google Design Sprints, lean-startup MVPs, and hackathons — where teams routinely produce functional proof-of-concepts within hours. Innovation literature broadly supports fast, cheap prototypes to accelerate learning and stakeholder buy-in. The 90-minute build window and reliance on existing tools are documented directly in the article's PDF.


## Related across articles
- [[concept-minimum-viable-ai]]
- [[concept-ai-learning-journeys]]