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Noah Weiss
1/ “Chief Question Officer” is the unofficial role of many great product, design, and eng leaders. The best questions foster rigor, encourage focus, and teach instincts. Some favorites when reviewing product proposals / plans / specs:
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Noah Weiss 30 May 18
Replying to @noah_weiss
2/ “What is our fastest path to learning?” The biggest determinant to long-term product velocity is the pace of learning.
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Noah Weiss 30 May 18
Replying to @noah_weiss
3/ Learning is broader than just A/B experiments. How quickly are you developing new insights about customer needs and pain points?
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Noah Weiss 30 May 18
Replying to @noah_weiss
4/ Of course you need some mix of “earning” launches, ones you have high confidence will be a quick win for customers. But the “learning” launches are the ones that unlock future trajectory bending.
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Noah Weiss 30 May 18
Replying to @noah_weiss
5/ Relatedly: judge PMs in the short-term on their pace of learning, and long-term on their impact. Organizations that do the reverse perverse incentives towards short-term hill climbing.
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Noah Weiss 30 May 18
Replying to @noah_weiss
6/ “Are there any cheat codes?” Put another way, in the classic scope vs. time vs. quality tradeoff: are there scope cuts we can make to speed up time while preserving quality?
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Noah Weiss 30 May 18
Replying to @noah_weiss
7/ There are many great types of product shipping cheats: avoiding premature v1.1 polish, scalable for only a subset of customers, smart defaults + fewer settings, algorithm heuristics, human curation…
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Noah Weiss 30 May 18
Replying to @paulg
8/ In the early days of a product, the best framing on shortcuts is ’s “Do things that don’t scale”:
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Noah Weiss 30 May 18
Replying to @noah_weiss
9/ Don’t view launch cheat codes just as “lean startup” pragmatism. Reducing feature scope to optimize for learning is an act of product humility. Even the best experiment driven teams only generate wins on <40% of launches, after-all.
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Noah Weiss 30 May 18
Replying to @JeffBezos
10/ “Is there a 2-way door?” If it is, optimize for decision making speed; if it’s not, optimize for decision making quality. Borrowing from :
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Noah Weiss 30 May 18
Replying to @noah_weiss
11/ The reality is the vast majority of decisions are two-way doors — as long as your org has the right post-launch sensors and is great at error recovery.
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Noah Weiss 30 May 18
Replying to @noah_weiss
12/ Error prevention is costly and time consuming. Use it only when absolutely necessary.
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Noah Weiss 30 May 18
Replying to @noah_weiss
13/ The ladder up move: figure out how to decompose a monolithic, seemingly 1-way door product decision into a sequence of reversible, stackable launches.
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Noah Weiss 30 May 18
Replying to @noah_weiss
14/ “Is this the right investment mix?” Great product leads often take an investment approach and look at feature funding as portfolio allocation problem. It’s important to make sure teams are balancing the right mix of feature maturity bets.
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Noah Weiss 30 May 18
Replying to @noah_weiss
15/ Seed = speculative bet with outsized upside. These could be entirely new product capabilities, swings at step-function changes in the growth funnel, features that can create new network effects, etc.
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Noah Weiss 30 May 18
Replying to @noah_weiss
16/ Series A = validated customer demand ready to scale. These are often experiments or limited releases that looked promising; now it’s time to scale up to 100% and see what the full impact can be.
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Noah Weiss 30 May 18
Replying to @noah_weiss
17/ Series B = proven, scaled feature needing 1.x features. The customer-feature fit is fully validated and a meaningful driver of the business. Now it’s time to relentlessly refine and improve the quality of the experience.
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Noah Weiss 30 May 18
Replying to @noah_weiss
18/ … Series G = big company working on v10 of a plateaued growth product line that still has meaningful revenue. This is unlikely a place to do great product work.
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Noah Weiss 30 May 18
Replying to @adamnash
19/ A related great read on product investment types is post on 3 buckets: metric movers, customer requests, and and customer delight
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Noah Weiss 30 May 18
Replying to @noah_weiss
20/ “What are the anti-goals?” The goals are often boringly obvious. What you deliberately chose to not prioritize is more interesting and can force harder debates.
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Noah Weiss 30 May 18
Replying to @noah_weiss
21/ Good anti-goals range from metrics to use cases to customer types that you want to intentionally avoid prioritizing/moving.
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Noah Weiss 30 May 18
Replying to @noah_weiss
22/ An example: when improving Twitter’s timeline ranking, obvious goals might be tweet engagement rates and WAUs. A non-obvious anti-goal might be sessions/DAUs, which very well could decrease.
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Noah Weiss 30 May 18
Replying to @noah_weiss
23/ Questions > Answers. Recap of great product questions: fastest path to learn, cheat codes, 2-way door, investment mix, and anti-goals? Bonus: it’s easier to scale yourself with questions, and more fun for teams when they create the answers.
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