The AI Product Development Lifecycle
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Building an AI product is more than just training a model and somehow rolling it outβitβs about integrating it into an experience that has a (validated) purpose.
I kick off my AI PM 101 course with the AI Product Development Lifecycle concept, hereβs an (overly simplified) breakdown of this process for my followers:
β¨ 1. Ideation:
It all starts with mapping out AIβs unique capabilities to the right problem. What pain points can AI uniquely solve? Use AI where it adds the most value, and avoid using it for problems that simpler solutions can handle.
β¨ 2. Opportunity:
Assess the market and determine if the idea is an experience your target persona & market need, and whether it supports a scalable business model. This is where you evaluate not just the experience, but also how AIβs ability to personalize, predict, or automate can create differentiation. Also consider AIβs infrastructure demandsβwill you need specialized hardware, or can it scale?
β¨ 3. Concept & Prototype:
Work with your xfn partners to scope out the details.. data requirements, the right model(s), architecture, experiments, even design and map out the end-to-end experience. This step also involves assessing trade-offs i.e. balancing technical feasibility vs delivering early user value.
β¨ 4. Training & Development:
Model training! Train the model and integrate it onto an experience to assess whether it meets the MVQ. Think about performance & product metrics, and dogfood to validate if the experience adds immediate value from day 1.
β¨ 5. Testing & Analysis:
Testing in AI involves continuous learning/evaluating model outputs. Validate against real-world data, monitor for bias or drift, and use this feedback to iterate.
β¨ 6. Roll-out:
If everything looks good, launch by making the experience accessible to users. The models might require ongoing tuning and monitoring post-launch to adapt to new data so you may need to retrain or tweak the model as you gather more real-world usage data, and this might involve further iterations before finding the right product-market fit.
Join my free webinar on how to nail your next product review that will dive into the best practices on how to lead the discussion and decisions for the stages above.
The AI Product Development Lifecycle (AIPDL) Β© 2023 by Marily Nika is licensed under CC BY-ND 4.0
