Previously, 'done' meant deploying to production. AI collapses the build-test-learn cycle so dramatically that the new definition of 'done' is when a feature is fully adopted and delivering value. The feedback loop can be instantaneous, making anything less an incomplete job.
The Agile Manifesto optimized the software development process for the internet era. The Makers Manifesto is a broader successor for the AI era, focusing on the entire value creation lifecycle—from purpose to adoption—not just the technical build phase.
When any feature can be replicated quickly using AI, the feature set itself is no longer a defensible moat. Sustainable competitive advantage must now be built on harder-to-copy assets like proprietary data, established distribution channels, and strong customer loyalty.
To empower a distributed team of human and AI 'makers,' strategic context can no longer be implicit or tribal knowledge. It must be explicitly codified and continuously accessible as a living document to guide day-to-day trade-off decisions for both people and automated agents.
AI empowers individuals to perform tasks from adjacent disciplines (e.g., a PM doing 80% of a designer's job). This breaks down rigid silos, allowing non-technical teams like customer support to directly contribute to product development through prompting, fostering a more integrated and responsive organization.
The traditional "find PMF, then scale" model is obsolete. AI accelerates market changes, competitor moves, and customer expectations so much that PMF is no longer a stable achievement but a moving target that must be constantly monitored and defended.
While AI can automate parts of user research, over-reliance on it creates a dangerous distance from the customer. In a market where features are easily copied, the "gold nuggets" for true differentiation are found in nuanced, direct insights that only come from observing users firsthand.
An organization's best prompt engineer might be a non-technical Subject Matter Expert (SME). Deep domain knowledge and specific vocabulary to articulate complex outcomes, like writing a business proposal, can be more effective than generic technical prompt-writing skills.