Key Concepts
- 1Separate demoware from durable value by asking: does the agent reduce a real cost (support tickets, cart abandonment, time-to-purchase) or just look impressive in a keynote?
- 2The 'hype tell' is any capability that only works on a curated happy path — a demo that breaks when you swap the SKU or ask a follow-up question is a prototype, not a product
- 3Real value shows up in unit economics: cost-per-resolved-conversation falling, contribution margin per order rising, or a measurable lift in a metric you already report to finance
- 4Discount durability: if a feature's advantage disappears the moment a competitor buys the same LLM API, it's table stakes, not a moat — the moat is your proprietary data, catalog quality, and workflows
- 5Beware 'agent-washing': wrapping a rules-based chatbot in LLM language. The test is whether it can handle novel, unscripted intent, not just re-skinned FAQ
- 6Time-to-value for SMBs matters more than ceiling: a modest agent live in two weeks beats a brilliant one that needs six months of catalog cleanup
- 7Use a 2x2: (impact on a reported metric) x (defensibility). Only the high-high quadrant deserves roadmap priority; the rest is experimentation budget
Why It Matters for PMs
Roadmap discipline: PMs are flooded with AI feature requests. A real-vs-hype filter protects scarce engineering capacity from chasing demos that never convert to retained users.
Credibility with leadership: Tying every agent bet to a metric finance already tracks (CAC, AOV, ticket deflection) turns 'AI strategy' from a vibe into a defensible investment case.
Avoiding sunk cost: Killing hype features early frees budget for the boring, durable work — catalog data quality, latency, guardrails — that actually determines whether the agent succeeds.
Test Your Understanding
Question 1 (Multiple Choice)
Which signal most reliably distinguishes a 'real' agent feature from hype?
Question 2 (Multiple Choice)
A competitor ships the same agent capability a month after you using the same LLM API. What does this tell you?
Question 3 (Multiple Choice)
For an SMB merchant, which factor usually matters most when evaluating an agent feature?
Question 4 (Short Answer)
You're handed an impressive agent demo. What three questions would you ask before putting it on the roadmap?
Think about your answer before revealing the explanation.
Question 5 (Short Answer)
How would you tell the difference between an LLM-powered agent and a rules-based chatbot dressed up in agent language?
Think about your answer before revealing the explanation.