To secure buy-in for its risky "Platform 2," Zipline built a rough prototype and held a "conviction milestone" event for the whole company. Witnessing the tangible demo converted even the most ardent skeptics on the leadership team, aligning everyone to bet the company's future on the new product.

Generic use cases fail to persuade leadership. To get genuine AI investment, build a custom tool that solves a specific, tangible pain point for an executive. An example is an 'AI board member' trained on past feedback to critique board decks before a meeting, making the value undeniable.

Traditional "writing-first" cultures create communication gaps and translation errors. With modern AI tools, product managers can now build working prototypes in hours. This "show, don't tell" approach gets ideas validated faster, secures project leadership, and overcomes language and team barriers.

To make platform progress compelling for executives, avoid code demos. Instead, stage a "before and after" customer scenario. Team members can role-play as a customer and an agent to vividly show how a new API improves the experience or saves time.

When driving major organizational change, a data-driven approach from the start is crucial for overcoming emotional resistance to established ways of working. Building a strong business case based on financial and market metrics can depersonalize the discussion and align stakeholders more quickly than relying on vision alone.

When introducing AI to a skeptical executive, a detailed, multi-week rollout plan can be overwhelming and trigger resistance. A more effective approach is to showcase one specific AI capability within an existing tool to solve a tangible problem. This "dip your toe in the water" approach builds comfort and demonstrates immediate value.

When an engineering team is hesitant about a new feature due to unfamiliarity (e.g., mobile development), a product leader can use AI tools to build a functional prototype. This proves feasibility and shifts the conversation from a deadlock to a collaborative discussion about productionizing the code.

To keep non-technical stakeholders engaged, don't show code or API responses. Instead, have team members role-play a customer scenario (e.g., a customer service call) to demonstrate the 'before' and 'after' impact of a new platform service. This makes abstract technical progress tangible and exciting.

When leadership pays lip service to AI without committing resources, the root cause is a lack of understanding. Overcome this by empowering a small team to achieve a specific, measurable win (e.g., "we saved 150 hours and generated $1M in new revenue") and presenting it as a concise case study to prove value.