Popularized by Amazon, a Single-Threaded Owner (STO) is a leader who is 100% dedicated and accountable to a new initiative such as inventing a new product, launching a new line of business, or executing a digital transformation. The Single-Threaded Owner is responsible for turning strategy into real results.

SaaS businesses are all the rage! Even companies that have success with traditional products are re-thinking their business as a SaaS offering, to reap the many benefits:

• Valuation. Even if all you sell is basically the same product to the same customers, but on a "SaaS" model, that can be enough to attract new investors and increase your valuation by an order of magnitude.
• Recurring revenue. SaaS implies a subscription model, which lends itself to more recurring revenue, or at least more predictable recurring revenue.
• Additional revenue streams. SaaS businesses can collect and monetize anonymized customer data, including patterns of customer behaviour. They can serve ads to different customer segments, or upsell partnering products.
• Product stickiness. Customer behaviour data can be analyzed to quickly assess how to make the product more sticky. Feature "experiments" can be run on different customer segments.
• Reduced operational costs. Cloud technology can theoretically allow for a zero IT footprint on the client site, reducing deployment and support costs. And because SaaS is also usually "self-service" ie. purchased and upgraded directly online, it can reduce sales overhead as well.
• Access to new markets, such as SME and mid-market customers that increasingly buy only SaaS.

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These benefits are so attractive that every and any product and business model is being re-imagined as SaaS, leading to some great ideas (e.g. Spotify, Coursera, bacon-of-the-month dropped off at your doorstep!). But not every business lends itself intuitively to a SaaS model. Especially if you have years of legacy technology and processes established with an existing customer base, the transition won't happen overnight. There are key questions to answer in each facet of the business.

AI/ML has the potential to deliver incredible value to customers. A single breakthrough can make a product company's growth soar. A fine-tuned model can completely transform an enterprise's operations.
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The mechanics of delivering such a program are very similar to traditional projects on the face of it, so it is tempting to think of the implementation as being the easy part. But because of the non-deterministic nature of AI/ML, all the pitfalls of ordinary software development programs - misaligned objectives, underestimation, lack of process, skimping on QA, ignoring risks, etc. - are amplified x10. To deliver successfully, you need to ratchet up the program diligence.

Studying for the PMI-ACP agile PMP exam? Here is a cheat sheet to review before the exam, to help answer all the trick questions.

From research and prototyping to commercial development, AI/ML requires making decisions and trade-off's. This is where the PM needs to provide loads of context to the R&D team: what are the customer problem(s) are that we are trying to solve? What parameters and trade-off's would be acceptable to a customer? Have we considered the cost trade-offs of operating in practice? ​

Yes the PMP exam does have many "trick questions". ​Here is my cheat sheet of tricks, gotchas and pitfalls collected about these questions. You have to be very careful about the wording and cut through the noise in the question to find what the really important answer is. This is meant to simulate project management in the real-world, where day-to-day you have to cut through the noise and make decisions based on what's truly important. There is also lots of terminology, acronyms and references to names of theories and principles that you need to know, and sometimes these terms are not even in the PMBOK itself.