Generally, I am thinking of success in 3 dimensions: Vision, People and Execution. All three need to work well for a team to succeed over time. Early in your career Execution takes a bit of a higher focus. You can get your first 2-3 promotions by launching bigger and more complex projects. However, as you grow in your career the ability to offer broader, more ambitious vision and have others join you in the journey become more central for your success. Your already proven execution skills help in attracting people to work with you since they know you will deliver. It’s important to invest in all three dimensions throughout your career, since honing these skills takes time. When I joined Meta I was excited to find out that here we are formally aligning PMs expectations with similar axes: Impact (which includes Strategy and Execution) and Capacity Building (which includes healthy team and cross functional relationship as well as broader contributions to the organization). I believe this structured view creates the right incentive and culture.

First of all, we need to address Amazon's terminology for these roles. A technical product manager at Amazon is generally referred to as a Product-Manager-Technical (PM-T). Whereas a Technical Program Manager (TPM) is a distinct role that sits at the intersection of product, engineering and program management. An Amazon TPM is a unique role that combines business ownership over delivery with high-level technical architecture. They are usually the program glue - that brings together PMTs, engineering teams and business stakeholders on all aspects of an initiative. However, note that this AMA is focused on the technical product-manager role or PM-T. So please make that translation whenever you see "TPM" in these questions.

Great question. It's really hard to prioritize small, iterative product improvements against large new features/bets. In my experience you need both, as well as a few other aspects. The way we do it in my teams is to think of it as balancing investment levels between different buckets, and to dedicate capacity to each of these buckets. Otherwise it's a constant struggle. We've tried to describe it in this section of the Atlassian product discovery handbook talking about ideas, and that one about prioritization. A couple of different types of buckets: * Boulders, rocks and pebbles * Boulders: large investments with potentially big payoff but high uncertainty, too. E.g. one or multiple teams over one or multiple quarters. * Rocks: medium sized investments with fewer risks, but potential for delighting users. E.g. one team for a month. * Pebbles: Small, typically straightforward change. E.g. one person for a week. * Don't underestimate the impact of rocks and pebbles! In my experience users LOVE to see the app they use get better every time, that's a great way to create fans. * RUF: Reliability + Usability improvements + new Features. Think of the RUF framework as a pyramid: * At the base of the pyramid there's Reliability. Reliability is about building trust. Trust takes a long time to build, but can be destroyed very quickly — a single event of data loss or security breach can be a serious source of churn, let alone repeat incidents. So you need to invest in your product's reliability first and foremost. * Usability Improvements comes second: a feature is rarely “done” — it’s part of a system and that system needs constant tuning. In your roadmap, it is important to allocate budget and resources to keep investing in improving your current feature set. * At the top of the pyramid is new features, both large and small. Then you decide how you want to invest in each: E.g. for a super early stage app you might be spending all your time on boulders and rocks, and little in reliability or usability improvements. For a more mature product you might spend 50% in the reliability bucket and only 10-20% on new features. Then how you actually implement that in your team can vary. In my teams we look at it at investment over time: we might be focusing on a boulder for a quarter, then go back and tackle a few rocks and pebbles. Some of the teams have a rotation where 1 engineer is focusing on pebbles each week. etc. But the important part is to have a strategy and make it a conscious choice, vs something that you react to every time you get a new request from a customer or stakeholder.

Perhaps a contrarian take, but technical skills aren't the most critical for the majority of PM roles out there, except for deeply technical products or platform positions. For the general PM role, it's much more important to demonstrate your ability to delve into customer problems, set strategy, execute, and drive impact that aligns with your organization's mission and vision. Technical skills matter, but they are secondary. They usually revolve around your ability to work with engineering counterparts and understand enough technical concepts to make trade-offs, and to work with data and perform analysis for decision-making. In my experience, both of these skills are often inquired about directly.

Will add my favorite question to ask the managers of product managers (GPM, Director and above): "Tell me about a product manager you've worked with, and who's better than you and inspires you. What about them makes you say so?" Best answers usually involve leaders speaking about people on their team (reports etc), or someone more junior than them who they helped grow. If someone has been a people manager for a decade or longer, and they have never had a more junior person on the team who's better than them, this makes me probe more into their ability to lead, recognize talent and be humble enough to see that someone has better craft skills than they do. As a leader, you are guaranteed to have to lead people who are smarter, better and more talented than you. Having the humility to recognize that and work with it is key to scaling as a product leader and being able to attract and retain talented folks.

No-one can, or should ever be sure that they have a 100% right product strategy. But you can do a lot to de-risk your approach, and your tactics should vary depending on how much time you have to plan. * Is your strategy ultimately going to drive the change in behaviour you want? Find the key participants in your strategy -- e.g. the customers -- and talk, talk, talk to them. You'll learn a ton from the first 5-10 conversations, and suddenly you'll start to hear the same themes and be able to predict what they'll say. Then you can move on. * Read, and connect with people who are familiar with this situation in your industry or other industries. How did things work out? Is the current market / environment similar enough that you can draw conclusions? * The more experienced you are, the more confident you can be about relying on product intuition. A phrase I often use is "we've seen this movie before" and, it's surprising how many times the same situation gets repeated.

Taking a step back, I think the 1st PM needs to act a lot like a head of product in the early days. The ones I see that do well for their company (and themselves) typically focus on doing 3 things well, where others only do 1-2: 1. PM Execution * Typical activities you expect from a PM i.e. research, talking to customers, ideation, roadmap * This is foundational, but I think you will likely fail or at least get overlooked for leadership opportunities if you only spend time on this 2. Building the PM playbook * A key part of establishing the function is to determine the stage-appropriate processes, tools and people (hires) needed to achieve our goals * By owning the execution piece, you have an unfair advantage (and incentive) in shaping what the playbook should look like * If you can take most of this off your founders' plate, IMO you almost instantly distinguish yourself in the top performance quartile * You will also have greater control of your own destiny i.e. who joins the team, how prioritization decisions get made 3. Stakeholder management and education * Expect to spend 1/3 of your time (ideally not too much more) aligning with key stakeholders not just on what will make it in the roadmap and be shipped when, but also on how decisions should get made, and why there is a business justification for certain resources to achieve your goals. * In a startup, your leadership and key stakeholders probably have a limited understanding of PM best practices. In fact, they may have a (somewhat biased) view that a lot of it is unnecessary red tape that will slow down execution. Know when to push back and when to optimize for speed of execution and document learnings later. * I think the best founding PMs think like mini-CEOs: they scrutinize the business value of features (output) as well as the inputs (imagine this is your own $ or resources). They push back and say no when it's needed, and they're flexible enough to update the playbook and processes as teams grow. To answer your question more specifically, here's a simple sequence I'd use to prioritize my startup product roadmap from first principles: * Align on north star goals: * Where do we need to get the business metrics to be in the 6-12 months in order to raise our next round of funding? (or whatever the company north star is e.g. reach profitability) * As a result, where do we need the product metrics/behaviors to be in the 6-12 months in order to raise our next round of funding? (or whatever the company north star is e.g. reach profitability) * Work backward from north star goals to your current reality: * What are the 3-5 key jobs to be done that our customers come to our product to achieve? * How well does our product help customers complete these jobs to be done today? * What customer behaviors do we need to see in the product for us to know this is true? What product KPIs/metrics can we use to measure and back up that these behaviors are really happening? * Which business metrics (e.g. revenue, retention) will this impact? * Other first principles I'd think about: * Leverage the fact that your team is smalll to talk to more customers. You should become the expert on your customers 'jobs to be done' and current workflows. This will give you all the ammo you need when having to confidently decide, slice, and justify your roadmap. * >50% of the time, in the early days, doubling down on features or a product area that already works (i.e. has usage) will yield better results than shipping a shiny new feature. Communicate this accordingly to your stakeholders. * Be very clear about whether a feature is to play offense or defense (i.e. filling a gap with a competitive product.) There's nothing wrong with either, but a large lack of either signal you are either focusing too much or too little on the products you are evaluated against.

Product School, Try Exponent, and Product Allinace are good resources for PM interviews prep. Later is a good question. Interesting idea. I don't know of any, but it so interesting that someone should be offering it. Perhaps they might have rolled into certification or cohort courses with live projects!

Let's cover this in two ways: (1) how to think about KPIs, (2) examples of poor ones and how they can be better. I'll also approach the question a little more broadly than Product Managers alone. Remember that Key Performance Indicators (KPIs) are used at all levels of a company (e.g. project, team, group, division, exec team) with different levels of fidelity and lag (e.g. daily active user vs. quarterly revenue). The appropriateness of standard KPIs will also differ by industry (e.g. commerce software will not rely on daily active users the way social networks do). Finally, many people use the term KPI when they actually just mean metrics (whether input, output, health, or otherwise). As the name suggests, only the metrics that are key to success should be elevated to KPIs, and there should be as few of them as possible. When I see more than 1 from a team, 3 from a group, or 5 from a division/exec team, there are good odds that some can be cut, amalgamated, or otherwise improved. KPIs are, after all, meant to drive decision making and accountability. So what are the criteria of KPIs that stand to be improved, and examples of them? 1. Vanity metrics: these look impressive but doesn't actually measure the success of a product. Examples include the amount of traffic to a website, the number of sign-ups a product has, daily active users for marketplaces that monetize through purchases, or the number of likes across posts on a social network. 2. Poorly instrumented metrics: these are not reliably measured, which can lead to incorrect or misleading conclusions about the effectiveness of a product. For example, if the first step of a conversion funnel (e.g. checkout) has many ingress pathways, and the user can transition in and out of that step before proceeding down funnel, how well your instrumentation deduplicates that first step is critical to your conversion calculations. 3. Lack of attribution to effort: any metric who's fluctuations cannot be explained by the combination of efforts from the team/group using it as a KPI, plus seasonal and random variability, is going to be ineffective. For example, if a common funnel in the company has multiple teams trying to improve its conversion, each team needs to define a KPI that does not overlap the others or they won't know if their efforts resulted in an outcome versus another team's efforts. Note that if all those teams are in the same group (e.g. a growth org), then that group could effectively use the conversion rate as their KPI. When in doubt, or if you're unable to isolate your efforts with lower level metrics, run an A/B test against every major change by each team to get a better (but imperfect) indication of relative contribution. This criteria covers many grey areas as well. Revenue is a prototypically difficult KPI for individual teams to use because of attribution. However, you can find relatively small teams or groups that build add-on products that are directly monetized and expansion revenue can be an excellent KPI for them (e.g. a payroll add-on to an accounting system). 4. Unclear tie to next level's KPI: companies are concentric circles of strategy, with each division, group, and team needing to fit its plans and focus into that of the prior. This includes KPIs, where you'd expect a well modeled connection between lower level KPIs driving higher level ones. For example, say a SaaS invoicing platforms sets an X in Y goal as an activiation hurdle to predict long term retained users (i.e. 2 invoices sent in first 30 days). It would be reasonable to assume that onboarding will heavily influence this. But what about onboarding, specifically, will matter? If a team concots a metric around how many settings are altered in the first 7 days (e.g. chose a template, added a logo, set automatic payment reminders) and wants to use that as their KPI, they'd need to have analyzed and modeled whether that matters at all to new users sending their first 2 invoices. 5. Lagging metrics at low levels: the closer you get down to a team level, the more you want to see KPIs defined by metrics that are leading indicators of success and can be measured without long time delays. Bad KPIs are ones that just can't be measured fast enough for a team to learn and take action. For example, many teams will work to increase retention in a company. But larger customers in SaaS may be on annual contracts. If features are being built to influence retention, it's better to find leading activity and usage metrics at the team level to drive behaviour and measure them weekly or monthly. These can tie into a higher level retention KPI for a group or division, and keep teams from getting nasty delayed surprises if their efforts weren't destined to be fruitful. The only caveat for this criteria is how platform and infrastructure teams measure themselves. Their KPIs are typically more lagging and this topic is deserving of its own write-up. 6. Compound or aggregate metrics: these are made up of multiple individual metrics that are combined using a formula in order to provide a more comprehensive view of the success of a product without needing to analyze many individual numbers. Examples include effectiveness scores, likelihood indicators, and satisfaction measures. Arguably, many high level KPIs behave this way, such as revenue and active users, which is why (3) above is important to keep in mind. However, its formulas that are particularly worrisome. They inject bias through how they're defined, which is hard for stakeholders to remember over time. You find yourself looking at a score that's gone down 5% QoQ and asking a series of questions to understand why. Then you realize it would have been simpler to look at individual metrics to begin with. In my experience, these KPIs lead to more harm than good. 7. Lacking health metrics or tripwires: having a KPI is important, but having it in isolation is dangerous. It's rare for lower level metrics to be improved without the possibility of doing harm elsewhere. For example, in commerce, we can make UX changes that increase the likelihood of conversion but decrease average order value or propensity for repeat purchases. Therefore, a KPI that does not consider tripwires or does not get paired with health metrics is waving a caution flag.

In my previous answer, re: finding the right opportunities + making decisions - I mentioned four lenses (Customer, Business, Market, and Technology) as key components of coming up with ideas and making decisions. The best advice I have to offer is to be intentional about spending time developing your muscles in those areas. It can be as simple as picking a product or service in your day-to-day life and thinking through what inputs might have contributed to the experience you’re having as a user. Additionally, a lot of product strategy is about being able to identify the opportunity that will maximize impact. How will you hone in on the right problem and arrive at an excellent solution? I’ve found that strong problem-solving intrinsics and the ability to make effective decisions are very valuable. Here are two frameworks I’ve always found helpful: * McKinsey’s Seven Steps of Problem Solving - Helps abstract underlying problems/issues * Playing to Win - Strategy book by the former Procter & Gamble CEO A.G. Lafley Lastly, communication is essential for being able to get buy-in and execute product strategy. Work on simple, effective communication.