Building AI Products That Actually Work
A practical framework for product leaders navigating AI strategy, evaluation, and execution.
The AI Product Leader's Dilemma
The Promise
AI promises revolutionary capabilities: unprecedented automation, intelligent personalization, and exponential efficiency gains. Every competitor is shipping AI features.
The Reality
Most AI initiatives fail not from poor execution, but from fundamental misalignment between ambition and reality. Teams struggle with unclear value propositions and readiness gaps.
The challenge isn't building AI—it's building the right AI, at the right time, with the right team.
The Five-Gate Decision Framework
Before committing resources to any AI initiative, evaluate it through these five critical gates.
Real Value
Identify meaningful business impact—revenue growth, cost reduction, efficiency gains, or customer delight. Vanity AI projects fail fast.
AI Suitability
Validate that AI is the right solution. Some problems are better solved with better UX, process optimization, or data infrastructure.
Team Capability
Assess execution risk. Do you have the engineering talent, data quality, domain expertise, and organizational support needed?
Rigorous Evaluation
Establish clear success metrics: accuracy, latency, cost per request, and user satisfaction. AI is probabilistic—measure everything.
Risk Tolerance
Define acceptable failure modes. How fast can you ship? What level of experimentation is allowed? What mistakes are tolerable?
Build vs. Buy: The Strategic Choice
One of the most consequential decisions in AI product development is whether to build proprietary solutions or leverage existing platforms. This choice impacts speed, cost, differentiation, and long-term strategic positioning.
When to Build
- ●The capability is core to your business strategy
- ●Differentiation provides competitive advantage
- ●You need proprietary IP and deep customization
When to Buy
- ●The functionality is commoditized
- ●Speed to market outweighs customization
- ●Vendors achieve economies of scale you can't match
The Imagination Gap
"Most companies fail not because they were wrong about what they built, but because they failed to imagine what was now possible."
The greatest competitive disadvantage today isn't lack of resources or talent—it's failure to imagine. Organizations anchored in incremental thinking miss exponential opportunities that AI enables.
Study Success Patterns
Analyze successful AI-first companies. What mental models do they use? What assumptions have they challenged?
Lean Into Capabilities
Reimagine what's possible when AI handles tasks previously considered impossible or too expensive.
Think Exponentially
Stop asking "how can we improve by 10%?" and start asking "how can we make this 10x better?"
Spec-Driven Development
AI projects fail more often from unclear specifications than from technical limitations.
- Write FirstDocument the problem, desired behavior, inputs, outputs, and success criteria before writing any code.
- Review ThoroughlyHave technical and product stakeholders validate the spec. Catch misalignments early.
- Execute PreciselyBuild exactly what was specified. Deviations require spec updates.
The 3 Pillars of Evaluation
AI systems are probabilistic. Establish rigorous measurement across three dimensions.
Task Performance
Did the model complete the task correctly? (Accuracy, precision, recall)
Response Speed
Latency matters. (Time to first token, P95/P99 latency)
Cost Efficiency
Is it scalable? (Cost per request, cost per user, ROI)
Your AI Transformation Playbook
Start with Value
Identify meaningful business impact before exploring solutions
Validate AI Fit
Confirm AI is the right tool for the job
Ensure Capability
Audit skills, data quality, and organizational readiness
Drive with Specs
Document clearly before building anything
Evaluate Rigorously
Measure performance, speed, and cost systematically
Build Core, Buy Commodity
Invest resources where differentiation matters most
Think Product-First
Solve customer problems, not technical challenges
Personalize Intelligently
Guide users to discover, don't just deliver answers
Imagine Boldly
Think exponentially, not incrementally
Ready to build better AI products?
Let's turn this framework into your reality.