#advice

Most companies stumble across a market with a problem and spend most of their early-stage investment on finding the solution. So, while you can be strategic about choosing the right market and problem (mostly by pivoting to different problems that your target market is facing, or solving the same problem for a different target market), most companies leave this up to luck. What should never be left to luck is the discovery of a solution for your market. This is where great product management principles and operations can make or break a startup, and much of the time this means prioritising the right solutions and finding the best way to tackle them.

Startup leaders are constantly facing decisions of whether they should build something themselves, or buy an out-of-the-box third-party solution. I believe startups should be biased against building anything inessential that doesn’t pose a legitimate opportunity to create a competitive advantage. In other words: only do what you’re positioned to do better than anyone else.

Products with product-market fit are products that have found an adequately sized market that they can be sold into. It’s more of a spectrum than a binary state — some products are more suitable for their market than others.

While losing staff to customers and partners is pretty common in B2B SaaS, I would advise against having any sort of non-compete/anti-poaching clause in your standard customer and partner terms. First of all, this is bad for your employees. As an employer, you should be competing in talent market by providing a great place to work, with fair compensation and benefits, not trying to lock them in with contracts they don’t have any influence over and may not even be aware of. If an employee wants/needs to leave, and their best prospects are with a partner or customer, it’s unfair to limit their options.

The best product teams I’ve worked with embrace the iterative nature of software development. Instead of committing to roadmap items, they commit to high-level, long-term goals. These goals are the focus of one or more teams for at least a year, and teams work towards these goals by tackling small chunks of work and constantly re-prioritising and re-thinking their approach.

In SaaS, your customers repurchase your product every month, quarter, or year. Your product should improve at this same pace. Renewals are so automated they feel like a passive process. But this is a false sense of security. Every time a customer pays, they should receive compelling value. This week, we explore why and how startups should operationalise their investment in software development.

A common topic in product companies is the prioritisation of so-called customer-facing initiatives versus so-called technical initiatives (e.g., automated testing, reusable technical patterns, SDKs, automation, API-first services).

Assumptions around both expected value and effort required are usually wrong, often dramatically. The outputs of ROI algorithms can lead you astray if the inputs are incorrect, making prioritisation based on this method an exercise in futility. This is why teams should factor confidence into their ROI estimations, recalculate and reflect on ROI estimates after work has been completed, and assemble around long-term areas of focus where multiple hypotheses can be tested.

While this is a word that often comes with negative connotations, I believe that great products, particularly in the B2B world, are usually very opinionated. They come with a strong view of how they should be used, and how the problem they are solving should be solved. These products differentiate themselves from the herd and disrupt incumbents by doing things differently. Many B2B SaaS products are simply automated workflows built from the opinionated views that you should solve that problem in this specific way.

A trend I’ve noticed amongst the most effective people I know is that many of them are keeping a personal knowledge base (which you could also call a personal wiki, a professional journal, or many other things). This is clearly a trend beyond my immediate network, given the glut of new tools at least partially designed with this purpose in mind (e.g., Notion, Craft, Clover, Roam Research, or Obsidian). I started my personal knowledge base in 2010 (using Evernote) and it has been incredibly valuable to me throughout my career, so it has been great to see this trend take off recently.

Thanks to artists like Beeple and projects like CryptoPunks, NFTs have been the main character of crypto news in 2021. This has led to an avalanche of NFT sales by artists and celebrities all over the world. Despite the heavy focus on people with clout cashing in on their social capital, I think NFTs will have an even bigger impact on artists emerging today.

A common anti-pattern in the world of software development is the over-operationalisation of the research and development process. In moving away from traditional ways of working, companies will spin up long-lived teams, working to sprint cycles, but still find a way to cram an inordinate amount of upfront planning into the system, causing a significant amount of waste. This can feel like a big step in the right direction but often comes with very little benefits compared to the old way of working, as the way the team works doesn’t change.

The world of work is rapidly migrating from physical space to the internet and this newly dominant medium for work is going to significantly change how we structure society. This may sound dramatic, but it is inevitable that industrial-revolution era systems, legislations and structures will eventually be superseded. I think, in the crypto community, we’re already seeing the structures of the future emerge.

A playbook I’ve used to describe the responsibilities of a software engineer for hiring and professional development purposes.

In much of the world, industrialisation has led to the abundance of calories, often in very unhealthy forms — a novel state for a creature that is accustomed to subsistence. This has posed serious challenges for society (e.g., how do we provide large populations of people with healthy food?) and individuals (i.e., how do I eat healthy food in reasonable amounts when millions of years of evolution has instilled a nature of scarcity into me, that drives me to consume all I can find?). Growing up in the 1990s, the golden age of the fad workout plan and diet, the public debate regarding the dangers of junk food was prominent. The parents of many kids in my generation changed their attitudes towards sustenance significantly throughout our childhoods. Abundance, while positive in so many ways, comes with challenges.

On August 25th, Identify and Disrupt passed both houses of the Australian parliament with support from both major parties, just one day after it was first debated. Officially dubbed Surveillance Legislation Amendment (Identify and Disrupt) Bill 2021, the bill empowers the Australian Federal Police (AFP) and the Australian Criminal Intelligence Commission (ACIC) with three new and egregious powers when investigating federal crimes, or state crimes with a “federal aspect”.

To make effective decisions when developing products, engagement with customers is critical. Building this into your way of working should be the priority of any product leadership. Along the way, data should be captured and analysed.

Today, software-as-a-service (SaaS) is the standard business model for monetising business-to-business software. In the SaaS model, software is licensed to customers through an ongoing recurring subscription (e.g., a customer might pay $25 per month for continued access) or another form of operational monetisation (e.g., transactional fees on application usage) which also includes customer services.

I am an advocate for simple and collaborative methods for defining strategy for a team, department or company. Many strategy frameworks are too complex and while they may seem democratic (by embracing voting, for example), they usually lead to the middling harmony of sticking to the status quo. Instead, your collaborative process should encourage rigorous debate to overcome the mediocrity of concensus.

Many people say they don’t care about what data Big Tech is collecting on them. “I’ve got nothing to hide” is a common explanation for this. But, just because you’re comfortable with the ways your being tracked today doesn’t mean you will be in the future, when more data points are available for aggregation.

I talk a lot about regulation. But, let’s put this aside for a minute. Let’s talk about what Big Tech <em>should</em> do. Not just for shareholders (though their needs should obviously be a priority), but for the broader technology ecosystem.

Last week, House lawmakers announced their bipartisan legislative agenda to regulate Big Tech, led by Antitrust Subcommittee Chairman David N. Cicilline. This agenda consists of five bipartisan bills tackling Big Tech from multiple angles. While some proposals seem fair (i.e., updating filing fees for mergers for the first time in two decades), others, as is often the case with tech regulation, will likely come with unintended consequences.

Over the past decade, many of the big software suppliers in ecommerce have been moving towards an “all-in-one” strategy, with seemingly everyone trying to become the one-stop-shop for retailers (i.e., inventory management systems adding order management capability, order management systems adding inventory management capability, marketing apps adding storefront functionality). The result has been the emergence of broad platforms that have a lot of features, but don’t do anything great (jack of all trades, master of none; wide but not deep).

Google has been a focal point in the ongoing Big Tech anti-trust conversation, having achieved what many describe a monopoly in general search. Their defence? The “competition is one click away”.

Big Tech in-fighting has highlighted the tension between privacy and digital marketing. While I’m undecided on where we should draw the line, here is a summary of how I see the current situation.