Craft and Beauty in Creating Excellent Software Products

After Stripe Sessions last week in San Francisco, a conference to “discuss the most important internet economy trends”, I found myself reflecting less on the future of payments and more on the future of work. Specifically, excited to explore what the future of software product and development work will look like as AI becomes as ubiquitously used as it is talked about today. One of the breakout talks that was most striking was hosted by Katie Dill, the Head of Design at Stripe. She facilitated a discussion on “Craft and beauty: The business value of form in function” with Karri Saarinen, Cofounder CEO of Linear, and Yuhki Yamashita, Chief Product Officer at Figma.

Katie kicked off by sharing some fascinating observations around observing and measuring beauty. While “beauty is in the eye of the beholder” is a popular phrase and the subjectivity of aesthetics is often taken for granted, there is more than meets the eye. She shared the example of a Mondrian artwork compared to a fake version with slight design differences.

A quick poll of the audience reflected the wider statistical truth that over half of people, regardless of their art experience, can recognize the real Mondrian over the fake version. The way Mondrian deliberately laid his lines of paint is more beautiful, and his decision-making process reflects a rationale beyond just “looks nice”.

How Valuable Is Quality For A Business?

Stripe, Figma, and Linear are companies known for their opinionated and thoughtful approach to craft and design. This care shows up in details from the branding to the specifics of the user experience and even the emails their customers receive. Katie shared an example of an email for new Stripe users that saw double-digit percentage improvements in performance after design changes made the email not only more beautiful, but also more legible and effective.

Meticulous Craft: Decision-Making, Product, and Culture

One of Stripe’s core principles is “meticulous craft” and all members of the panel discussed the importance of craft in your company’s culture and people. Yuhki, for instance, called out that “if you need an OKR to convince someone of quality, you probably have the wrong team.” Similarly, Karri Saarinen said “quality doesn’t happen on its own, you need to push for it.” He further distinguished between craft being the activity and work that you put in, quality and beauty being the output that reflects the impact of that effort.

In this discussion, a key focus was around how craft and beauty and their inherent “quality” relate back to business value. How do you measure quality? Katie described three paths to achieve this goal. First, talking to your users, e.g. qualitative user research. Second, looking at data, and being specific about the metrics you choose to represent quality. Third, look to the team and if people take pride in their work and what you are making, then it is a good sign.

An example Yukhi later gave to embody evaluating and building a quality experience came from his past work at Uber. The team liked to imagine the “perfect” rideshare experience from the rider perspective. When imagining a perfect ride, you likely are thinking of as frictionless and fast an experience as possible. This was something we often thought about during my time working on the pickup experience team at Lyft as well.

Perhaps you imagine a one-click magical experience of calling a ride with the driver promptly arriving, you hopping in a clean and spacious car, and then arriving at your destination. However, the reality actually reflected that having additional touch points,like the ability to text or call your driver, could really improve the rider’s experience. While a “call driver” feature does not necessarily fit the imagined “ideal” experience, prioritizing this touchpoint creates a higher-quality experience for real riders in situations where a phone chat might make the difference between a completed pick up and a delayed or missed one.

Functional Beauty: Prioritizing Quality

Focusing specifically on functionality in beauty, there were a few observations. Yukhi emphasized the need to diligently evaluate if you are solving for a symptom or a root cause with what you are building. While solving for a symptom might seem simpler, you are likely creating a superficial solution that fails to actually address the core issue. Similarly, Karri discussed prioritization and suggested “don’t compromise on the main thing” you are focused on as a team. For Linear in their early days, this meant not compromising on core product decisions but putting less effort into non-core features like the help center in order to move faster. For Karri, this was an intuitive choice focused on “how and why” his business existed and what it is fundamentally about at its core.

Similarly, the discussion captured specifically design and quality for business (enterprise) as compared to consumer products or other categories. For decades, it was acceptable for enterprise software solutions to focus on functionality alone and ignore beautiful design. Karri challenged this, calling out that “business tools should not be worse than my personal tools, if anything it should be better.” Yukhi observed that the distinction between enterprise and consumer software design is getting thinner.

Beauty and the Beast of Workplace and Enterprise Software

For workplace products, users might care more about efficiency and productivity, and less about novelty. Moreover, thinking about the end use case is critical to designing a great product; Karri gave the example of dishwashers. Professional grade usually means more powerful, durable, simpler, and more focused. For a restaurant, a dishwasher might be simpler (fewer features) but also faster and more performant. This concept could be extended to professional quality software.

Extensibility: Continuous Craft for Software Products

While this Breakout talk was a highlight for me in Stripe Sessions, the theme was further reflected the next morning in the main stage AMA with Patrick and John Collison, Cofounders of Stripe, facilitated by Fidji Simo, the CEO of Instacart. Throughout the other presentations, whether it was explicitly discussed or implicit in the content and products shared, I continued to observe the themes of craft, quality, and beauty in software development and their impact on performance and business.

Do Users Love Your Product? The Future of Quality in Software Products

Karri asserted that “if people aren’t raving about your product, you probably don’t have a good product. Great products create fans.” Beyond the business value in individual product quality decisions, product quality is a potential moat for a software business.

This represents an interesting perspective, especially in light of a new wave of tools and products leveraging AI to help more people generate their own designs and digital products. Low/no code solutions like Bubble or Webflow have been around for a while, yet new solutions to help anyone create software are emerging left-and-right. While it is exciting to see new tools engineered to empower the next generation of founders and builders, regardless of their technical skills, I wonder: what will this future look like? How do we avoid a wave of generic, beauty-less new technology products created, not crafted, with AI tools?

AI has the potential to transform how software gets built and this technology is already starting to do so, as developers rely on products like GitHub Copilot to write code faster and marketers rely on tools like ChatGPT for quicker content generation. However, the core value in AI is not that it unlocks the ability to mindlessly create; instead, I believe it is that AI unlocks the ability to learn and iterate faster, creating something mindfully and then more easily iterating and improving on this starting point. In a world where AI increases productivity and generation of software products, craftsmanship becomes even more important in differentiating great products and user experiences from the rest.

Final Thoughts

In my experience working on new technology products at startups such as Kamcord, Lyft, and now as a founder, moving fast is of the utmost importance. However, I resist the notion that there will always be a tradeoff between speed and quality. In delivering great products, over and over, it’s about speed AND quality. Scope of your product work reflects what you’re able to deliver at the appropriate speed and with the appropriate quality — and even beauty.

While the goal of this post was primarily to recap my observations at Stripe Sessions, building quality products for companies and consumers alike is a passion of mine. Creating delightful experiences that add value to users’ lives cannot be done without craft. This is something I have experienced over and over while working on products for all kinds of customers.

Right now, our team is working on something new with the intent to help software teams build high-quality products, faster, and with more delightful and productive collaboration.

If you’d like to learn more about what we’re building or discuss how quality, craft, and beauty contribute to building uniquely great software products, please drop a line.

In December 2023, we conducted a survey with a goal of hearing from developers and their collaborators building software products, projects, and companies to learn about how we might better support these individuals and their teams.

Two weeks ago, as part of an experiment to open-source more of my own learnings as a founder and product manager, I asked on LinkedIn if anyone was interested in an aggregated, anonymized version of the results of this survey. The answer was universally “Yes” so this post is a follow up to share our learnings.

Disclaimers

This survey was not meant to be indicative of global trends or patterns. Rather, it’s a point-in-time snapshot of trends amongst the respondents. We had 55 responses to the survey, although many questions were optional and we segmented certain questions depending on whether the respondent currently codes or not.

Additionally, we shared this survey primarily through our personal social networks, so responses from specific demographics, such as founders, CEOs, CTOs, experienced developers, and people based in California (both SF/the Bay Area and Southern California) and New York City, are more prevalent.

For more quantitative data and generalizable trends, if that’s what you’re looking for, you might instead look at surveys run by larger enterprise organizations or developer groups. Three larger surveys that our team found interesting were:

• 2023 Stack Overflow Developer survey results
• JetBrains 2023 State of the Developer Ecosystem survey results
• Hired’s 2023 State of Software Engineers survey results
• Reveal Survey Report: Top Software Development Challenges for 2023

While we should not generalize the results of our much smaller-scale survey, we were heartened to see that there were certain consistencies with patterns shown in the much larger scale surveys listed above, which will be called out once we get into insights and analysis.

Let’s dig in!

2023 Developer and Collaborator Insights and Analysis: Demographics

Demographic information is helpful because it grounds the rest of the information collected through a better understanding of who is responding to this survey and their relevant experience and circumstances. The vast majority of our respondents identified their work status as employees of a company (50%), founders (38%) or self-employed (16%). Note that the total is >100% because respondents could check multiple options if relevant to them.

In terms of experience levels of their current position, the majority of respondents again identified as founders (38%). This was followed by lead/principal level (29%), then senior level (20%), then mid-level (7%). A much smaller percentage of respondents identified as executives or junior level.

In terms of the description of their role, CEO (25%) was the most common, followed by CTO (15%). Given the levels of experience, the CEO and CTO respondents seem like they are mostly or all founders as well.

Outside of CEOs and CTOs, product manager (15%) and backend developer (10%) were the next most common. There were a number of other developer respondents, with specific roles varying from Security Developer to Frontend Developer, Data Engineer, and Full Stack.

Survey respondents were overwhelmingly technical, with the majority coding for both work and personal projects (44%). Some coded only for personal projects (17%) while others code only for work (9%). Just over a quarter of respondents (26%) responded that they do not code.

Background and Experience with Coding for Technical Respondents

Of the 40 respondents who identified that they code, we had specific questions about their background and experiences coding. The majority of respondents (35%) had 10+ years of professional programming experience. This likely reflects our network demographics and has a bias towards more experienced respondents.

In terms of which platforms respondents develop for, the most popular answer by far was web, with a nearly even split between a frontend focus (70%) and with a backend focus (68%). This is likely indicative of respondents who build web applications as full stack engineers, writing code across the entire application. Another popular platform was mobile, with iOS (30%) getting nearly double the development attention of Android (15%). A smaller percentage of respondents develops for terminal (23%) and other more specialized platforms such as IoT / embedded, gaming platforms, and infrastructure.

In terms of the primary programming languages used, where each respondent could list multiple languages, we saw significant overlap between our 40 respondents’ answers and the wider developer surveys referenced above.

The most popular language by far was JavaScript (70%) which lines up with the focus we saw on web application development from our respondents. We unfortunately had a survey bug where Javascript was duplicated among the responses, so we manually de-duplicated the data and created the chart below.

The next most frequently used language was Typescript (53%) followed by Python (43%). HTML / CSS (38%) and SQL (30%) were also frequently used. Other notable languages included Go (15%), Rust (10%), Java (10%), Elixir (8%) and Ruby (8%).

Smart contract languages such as Solidity and Move were write-ins as an “other” option, as was Cypher, so potentially those were slightly underrepresented by respondents since it was not an immediately available options.

Developer Tools: How Much Is AI Used for Writing Code?

When asked if developers currently use any AI tools when coding, of the 31 respondents the majority use ChatGPT (68%) and GitHub Copilot (55%). Other tools, if mentioned at all, were significantly less popular, with Claude and Cursor each only getting one response. That said, this survey was in December 2023 and it would not surprise us if the discovery and usage of other AI tools has meaningfully increased. We would also expect ChatGPT and Copilot to continue to dominate AI usage among developers for coding in the near-term.

Developer Tools: Resources, Technologies, and Discovery

Of our respondents who code, most discover new tools, resources, and technologies through friends (62%) and colleagues (54%). Communities such as Discord groups (49%) are also popular, as are specific news sources such as hacker news (46%) and blogs they follow (44%). Interestingly, search (36%) and Product Hunt (13%) and social media were identified as far less popular sources.

When it comes to paid resources, books were the top resource people paid for personally, followed by hosting costs, and courses. This indicates a significant investment in growth and learning among respondents who code. For folks paying for hosting, we expect they are likely either working on their own projects or early-stage founders.

Resources used by those who coded, and which were paid for by their company, were topped by hosting, messaging (e.g. Slack), and project management (e.g. Jira).

Tools that were most likely to have been used for free included component libraries, design systems, data / API access (e.g. weather API), testing / CICD (e.g. CircleCI) and build / pipeline tools (e.g. Expo).

Tools that were most likely to be used if a company paid for them included paging / monitoring (e.g. Sentry), Hardware (e.g. AI GPUs) and the previously mentioned project management and messaging tools.

Interestingly, wellness apps (e.g. Headspace) were equally likely to be paid for by an individual or their organization, and twice as likely to be paid rather than free usage. Professional coaching was mostly not used by respondents, but if it was, their organization most likely paid for this service.

Background and Experience: Collaborators Who Do Not Code

26% of our respondents said they don’t code, and so we have a much more limited set of results from this group. Of those who do not code, when asked how coding relates to their personal and professional experience, most had learned to code but do not actively use this skill (60%), some have never learned and have no plans to but work with developers (33%) and some are currently learning (13%) or would like to learn to code (13%).

As for the respondents who code, when it comes to using AI tools (in this case at work and not to write code), ChatGPT dominated (over 73% responded using it). Nothing else came close. The next most common response was not using AI tools (13%) and we had one response each for different tools such as Bard, Notion AI, Grok, Otter, and others. Note that this was an extremely small sample size however, with only 15 respondents.

In terms of discovering new tools, resources, or technology, responses were similarly likely to rely on colleagues (67%) and friends (53%). Communities (47%) and blogs (47%) also were popular. Search (40%) was slightly more popular than for coders, but this might also be due to small sample size.

In terms of resources that were paid for personally, this cohort responded overwhelmingly with books and courses.

Of resources paid for by their company, messaging (e.g. Slack) and design collaboration tools (e.g. Figma, FigJam) were the most common, followed by note taking (e.g. Notion) and project management tools (e.g. Jira). This group was understandably less likely to use tools for paging / monitoring, hardware (e.g. AI GPUs), and technical collaboration (e.g. Storybook). This potentially indicates a gap in tools for non-coding product team members and founders who are still working on or responsible for software products, but not as intimately involved in the development and testing of their product’s code. We will be delving into this more as a team in the future.

Bonus: What Did ChatGPT “Think” Of Our Survey?

In addition to the questions synthesized above, we fed survey results into ChatGPT and requested analysis and synthesis. This included more free-form responses, and led to ChatGPT identifying a set of themes and experiences.

Here is the verbatim response we got from ChatGPT which identified a number of challenges and pain points among developers and collaborators when it comes to creating and managing software products:

“The responses you’ve provided span a wide range of challenges and experiences in software engineering and technology leadership. Here’s a grouped summary:

Project Management and Development Challenges:

- Environment setup and maintenance.

- Struggles with clarity, prioritization, and speed in teamwork.

- Merge conflicts and wasted effort on unused features.

- Difficulty with context switching and managing time demands.

- Release cycles being too long and lack of customer feedback.

- Challenges with database scaling and understanding cloud expenses.

- Tooling fatigue, syntax issues, and dependency management.

- Slow build processes and deployment times.

Team and Collaboration Issues:

- Need for better team communication and collaboration.

- Challenges in integrating with poorly designed APIs.

- Difficulties in getting engineers involved in the design process early.

- Remote collaboration issues and lack of spontaneous interaction.

- Cross-team work inertia and knowledge imbalances among teammates.

- Poor communication and passive-aggressive behavior in teams.

- Misalignment on strategy and vision.

Business and Leadership Struggles:

- Business growth challenges and financial pressures.

- Difficulty in finding a cofounder and identifying real problems.

- Navigating internal politics and bureaucratic structures.

- Leadership making uninformed decisions.

- Maintaining visibility on developers’ day-to-day production.

- Difficulty achieving product-market fit.

Personal and Professional Development:

- Lack of coding practice leading to skill atrophy.

- Learning new technologies and keeping skills updated.

- Adapting to the use of AI in workflows.

- Seeking high-quality feedback and user engagement.”

What’s Next: Continued Learning, Building, and Experimentation

Our team is exploring three fronts in parallel. First, we are conducting ongoing research to better understand the challenges, experiences, and needs of software product teams and developers and collaborators working in these organizations.

Second, our developers are spearheading a technical R&D exploration into what we can do in terms of providing a valuable solution to some of the challenges we’ve identified, specifically around helping software product teams build high quality products faster and facilitate better understanding of changes.

Finally, we are also taking on a limited number of early design partners to provide a personalized software simulator solution for their teams.

Right now, we are focused on helping early-stage software startup teams and software consultancies in this category. If you’re interested in this, please reach out at nadia [at] ethoswallet [dot] xyz.

Survey 2.0

We recently kicked off a new survey to learn more about product teams and software collaboration processes. If you’re interested in sharing your feedback, you can take that survey here: https://bit.ly/2024-software-survey . Note that all questions are optional.

On software teams, there is often a lot of energy involved early on in setting up your technology stack. You choose programming languages, frameworks, platforms, and even specific productivity tools to support both the product you plan to build and your team.

Why bother with tools for product management?

In discussing helpful tools for product management, there is occasionally resistance from product managers to even classify this as something worthy of consideration. As a founder or PM responsible for both a product and team, you might prefer to prioritize your teammates’ requests over your own ideas. In this case, you might defer to developers and designers on what their ideal tools are, or just agree to whatever project management tool your CTO or Engineering Manager suggests. While this is often well-intended, the result can be a mismatch between the tools chosen by individuals and the product management processes that best serve the team, speeding you all up and providing sufficient support.

Maybe you leverage a service like Superhuman to be faster on email (I certainly do), but the thought of trying to add tools to your workflow to make product management or product-related responsibilities such as quality assurance and testing more productive seems counterintuitive.

What happens to the product stack when AI is more widely used to build software?

In a future where software developers and other team members are increasingly adopting AI to increase their productivity and output, building more software products and features faster, Product Managers and product-oriented founders must adapt.

While the desire to be a good collaborator and supportive of the tools requested by your team is a strong and useful urge for founders and Product Managers, you need to also consider how you’re interacting with those tools and your team. Are you able to make decisions efficiently and proactively? Or are you reacting to fire-drills, bugs and breaking changes? The latter might indicate that you either have outgrown your product stack or have not sufficiently invested in it and as a result are stuck in fire-fighting mode.

Leveling up the product stack is critical if product leaders want to be empowered decision-makers, productive contributors, and effective collaborators. Yet when compared to the quality and quantity of tools available to software developers, those targeting the software product life cycle are lacking.

Today, the majority of tools I am aware of seem to focus on project management, data analysis, user research, experimentation, communication, and manual testing.

How do you start to build your product stack?

Today, building your product stack should directly relate to your skills, your team’s needs, and your product and scale.

When you are pre-product or working on your first pre-product-market fit product and a small team with a couple of developers at most, Google Documents and Sheets or a GitHub tasklist is likely sufficient for prioritization and task management. You likely are testing changes in production, which is reasonable when you have no users, speed is of the essence, and there is a low likelihood of changes colliding as different developers push changes to production.

In the early stages, resist the temptation to add process or tooling prematurely. Leverage lightweight techniques and processes, primarily stand up meetings, designs in Figma, and lightweight to do list tracking, to make sure the team is on the same page around priorities and what needs to get done.

Once you’ve grown the product to something slightly more complex, have external users, and grown the team to more than a couple of contributors, maybe you’re now in your project management era. As long as you’re prepared for the overhead of making sure your projects, stories, and tasks stay updated, this is a great time to adopt a tool like Linear or Asana to help everyone understand priorities and track progress.

Update your product stack as needed

You will likely add and drop processes as requirements change, systems break, and graduate from one approach or task management tool to another to accommodate your growing product and team. Leaning on communication supplements project management tooling, and relying on regular cadences for check-ins on your product can help.

Our team, which is remote and distributed, uses two meeting formats: lightning-fast daily stand ups that are followed by a more free-form forum immediately afterwards for topics requiring a deeper dive, and weekly retrospectives. As asynchronous communication in a tool like Slack or Discord increases along with your workstreams, messaging will become harder to follow as channels proliferate so using threads or having a system for managing communication to help team members understand as they come online where to start and what to focus on is essential.

As you start to feel your product stack breaking, either because the team, user base, and/or your product have grown, look for solutions to address specific pain points. For example, if you are spending a lot of time in stand ups discussing priorities and it is no longer a quick meeting, consider adding tooling or rotating the meeting host and empowering them to manage the clock. If testing and QA is a struggle, look into tools that enable non-developers to preview and test changes in a staging environment.

Today, this is a little bit of a jigsaw puzzle, but with creativity and ingenuity you can create a product stack that is highly composable and achieves its purpose of flexing with you, your product, and team.

How will the product stack evolve in the future?

For people to make fast, smart product decisions in a future where AI is a potent part of the software development process, the product stack needs to evolve to support more complex projects and dynamic teams.

Project management platforms like Linear are already exploring leveraging AI to improve and expand their product’s capabilities, making it useful for product planning as well as project management.

Developer tools like GitHub’s Copilot are making writing code faster and easier than ever.

However, the part of the product stack that excites me the most is the tooling around in-development work. This is where there is the greatest opportunity both because there is a gap in tools available to product leaders and their teams today, and because in the future this gap will become increasingly painful as teams are able to more efficiently ship, and must then manage, more products and features.

We are working on a new product that compliments existing products for product planning and project management by focusing on improving the experience for all members of software product teams when a feature is in-development.

You can read earlier thoughts about how AI will impact software development, products, and teams in my previous post. I’ll also continue to open-source my observations, ideas, and learning in this ongoing writing experiment.

We’re also conducting a survey to learn about how others are building their product stack: https://bit.ly/2024-software-survey . Don’t be intimidated by its length; all questions are optional so you can skip anything as needed.

If you have feedback, please reach out at nadia [at] ethoswallet [dot] xyz .

As a software startup founder, my passion is building products that add value to people’s lives and businesses. As an experiment, I plan to start open-sourcing more of my ideas and learnings through this blog. I hope to inspire and connect with like-minded individuals with this writing. If you have feedback, reach out at nadia [at] ethoswallet [dot] xyz.

Now, let’s dig into today’s focus: how will AI impact software development, products, and teams?

Why should we care about AI in relation to our work / life?

AI is a hot topic that is a frequent source of discussion and change in my network. Many friends who work in technology are joining AI startups or building or integrating AI products at their existing organization. And connections in other industries are considering how to advise clients and evaluate AI products on their benefits and risks.

Unlike other game-changing technologies such as blockchain, where many in my network were deeply curious but not directly impacted, AI is already changing our day-to-day. Almost everyone I know is interacting with AI through product experiences such as ChatGPT and the content consumed. AI technology is increasingly utilized through products and integrations in both work and personal life.

What is the role of AI in software technology companies?

This is a fundamental question for anyone building or whose business depends on software (hint: probably you!).

There is generally consensus that AI will play a role in writing code for software products. How that happens may vary significantly in the short- and long-term. One version of how this happens today is GitHub Copilot (from Microsoft) that’s betting on helping developers move faster. After ChatGPT, Copilot was the most adopted AI product among 50+ respondents to a survey we conducted in December 2023. Another approach is that of Devin AI (built by Cognition Labs, who recently announced a $21 million Series-A round). Devin AI is marketed as the “first AI software engineer” that is fully autonomous and able to complete tasks independently.

Regardless of your thoughts around complete autonomy versus human-in-the-loop, the future likely involves more code being written more quickly, via direct or indirect involvement of AI. This means that new software companies, products, and features can be launched faster.

However, this increase in AI adoption to create code can lead to side-effects such as more code to maintain, more complex codebases, and possibly also less human-readable code. Merging in changes to a codebase can already be challenging without AI. Even the best Pull Request review process is likely to miss some details. If AI is generating more PRs at a much higher speed, then these issues will become even more untenable.

This leads to another question…

If software developers increasingly use AI to write code in one form or another, what does this mean for their product and team?

Anyone working on software products has likely experienced “technical debt” and the pains it produces for the team. Decisions made to ship fast in the early stages lead to compounding challenges later on that ultimately might lead to a slowdown for developers and deployments. In a world where there’s more code and more complex code, this painful experience accelerates.

For non-developer product team members, like product managers, UX researchers, designers, data scientists, and customer support roles, this amplifies an existing challenge around understanding what’s going on in your product and the underlying code, and how it impacts your business and users.

What if instead of project management, product teams could get a snapshot of the current state of the product directly through the code?

We’re not talking about reading GitHub commits, which while technically feasible can be difficult to get value from as a non-developer if your developers aren’t writing detailed change logs. While I can’t share too many details on what we are building yet, we are exploring helping software product teams understand the real status of their product by simulating changes to the code and providing summaries and interactive demonstrations.

If successful, this should not only help product team members answer questions like “What happened to this task that a developer was working on?” or “When will this feature hit production?” but it will also help with quality assurance and testing. Even the least technical member of the team should be able to easily set up a user scenario and experience a change, before it hits production. You can change variables to see how product changes impact users with different attributes without logging in or out or generating multiple user accounts for testing.

This same functionality can greatly benefit pull request reviews as well. Adding a completely new dimension of information to pull requests reduces the likelihood of any issues getting merged in.

What does the role of the product manager or product owner look like in the future?

Even before the adoption of AI in software development, there was skepticism about whether product managers are necessary. Now with AI, there’s an interesting question of “Who should make product decisions?” — if you could wholly automate them and make Devin a PM friend (or just give Devin product decision-making powers) should you do it?

Product decisions should and will continue to be made by people for the most part. However, AI can speed up and improve these decisions and will become a critical tool to help empower product decision-makers, whether that’s a Product Manager, founder, or engineer. AI can provide better data and insights to help PMs make smarter product decisions, faster.

We plan to leverage AI to reduce the amount software product teams need to spend on project management and communication to get everyone on the same page. We want to enable shorter, faster, and more meaningful and informed product decisions by providing everyone with a better understanding of the product. This includes simulating how a software product will appear for users in different states based on the underlying code changes earlier in the process than possible today. This will reduce collisions and miscommunication and lead to shipping high-quality products faster and with less cost and effort.

How can product managers and founders use AI to build quality products faster?

AI unlocks superpowers for founders and product managers to empower them and their teams to ship high-quality products faster than ever and experience more delightful collaboration in their interactions with developers and other critical team members such as design and product marketing. This will work for all software product teams from remote to hybrid to in-person.

Our team is partnering with select individuals to pilot an early product. If you’re curious to learn more about this, please reach out to nadia [at] ethoswallet [dot] xyz .

We’re also conducting a survey and will be prioritizing respondents for follow-up. You can complete the survey here: https://bit.ly/2024-software-survey .

All the survey questions are optional, so if you don’t know how to answer a question, just skip it.

What’s next?

Exploring how AI can help product and development teams collaborate more effectively to deliver high-quality products quickly is our focus. We’re investigating both how we can leverage AI to help solve software product process challenges today, and to build a solution that empowers teams to make great decisions in a world where AI becomes more common in software development. I’ll also continue to open-source more of our ideas, experiences, and learnings.

Recently, I joined South Park Commons’ inaugural Founder Fellowship cohort. In my first few weeks, I explored different spaces by asking myself: what am I passionate or curious about? I focused on exploring new problems without pushing pressure on myself to “solve” them or build at this point. In this post, I’ll share some of the learnings and opportunities uncovered in this initial exploration.

Following my sense of curiosity, I explored six spaces:

1. 🙋‍♀️ empowering women
2. 🧠 reducing sadness/depression
3. 🕵️‍♂️ future of news/information/media/communication
4. 🎒 ecommerce
5. 👑 consumer social media
6. 🌱 sustainability

I first conducted research, then synthesized key takeaways. Some results reinforced what I already knew to be true, while other learnings surprised me. I found that I naturally focused on two of the six spaces: (1) empowering women and (2) reducing sadness/depression. Below are the insights that most excited me from these two spaces, as well the opportunities for further exploration that they inspired.

1. 🙋‍♀️ empowering women

Women continue to earn less and are underrepresented in the C-Suite, particularly in male-dominated fields.¹ The women who successfully enter fields such as math, science, and technology are more likely to lack confidence in their competence and ability. Even when they are recognized as high-achievers, women in these fields are more likely than male peers to shrug off praise or lowball their own abilities.² Beyond this confidence gap, there’s also a promotion gap. For every 100 men promoted to manager, only 85 women were promoted. The gap is worse for Black women and Latinas: only 58 Black women and 71 Latina women were promoted per 100 men.³

A frequently offered “solution” is for professional women to champion other women. One study found that women at Harvard Business School in the top quartile of centrality (central and connected to people with many contacts in the MBA student network) and with an inner circle of 1–3 other women landed leadership positions that were 2.5 times higher in authority and pay than their female peers without this combination. Meanwhile, women in their class whose networks most closely resembled those of their successful male peers (with centrality but no female inner circle) took jobs with some of the lowest authority and compensation.⁴

In the workplace, however, senior-level women who champion younger women are more likely to receive negative performance reviews.⁵ Since there are fewer women promoted to senior-level roles at every level, there are fewer potential senior-level women to champion and uplift other women. This creates overhead for existing senior-level women, who already face additional pressure and stress as compared to their male peers.

Senior-level women in the workplace are significantly more likely than men at the same level to feel burned out, under pressure to work more, and that they have to be “always on”. They’re at higher risk for attrition and are about 1.5 times more likely than male peers to think about downshifting their role or leaving the workforce because of COVID-19, often citing burn out.⁶

Taking an “off-ramp” or career break is a privilege. Off-ramping is increasingly unaffordable, particularly for women with dependents. In January 2019, 15% of women in the workforce said they would like to off-ramp but can’t afford to do so. Moreover, while 89% of off-ramped women want to resume their careers, only 40% successfully return to full-time employment.⁷ Off-ramping often comes with significant opportunity cost: rejoining the workforce is hard and, if women do, they generally earn less and have less job security.⁸

Why should we try to address these problems now? There is some early signal that we may be nearing a tipping point at which meaningful change could be accomplished. At the beginning of 2020, the representation of women in corporate America was trending up and in the right direction. This progress was most pronounced for senior management roles: from January 2015 to January 2020, women in senior-vice-president roles grew from 23 to 28%, while representation in the C-suite grew from 17 to 21%.⁹

So, what opportunities are there to empower women? Some that jump to mind are:

1. Help companies, particularly those in male-dominated fields like technology, better support, promote, compensate, and retain women. This is supported by data: 26% of women who off-ramped felt their careers were unsatisfying and 16% felt their careers had stalled.¹⁰
2. Help women address the primary causes of off-ramping. Causes to address include burn out, pay and promotion gaps, stalling careers, and caretaking for children or family members. 69% of the women who off-ramped said they wouldn’t have done so if their companies had offered more flexible work options (e.g. reduced-hour schedules, job sharing, part-time career tracks or short, unpaid sabbaticals).¹¹
3. Offer new types of work or careers to help women have greater flexibility and an easier time exiting and reentering the workforce. The gig economy is one example of this, but perhaps there are as-of-yet unexplored opportunities to create meaningful, flexible work that will disproportionately benefit the professional women who need it most.

2. 🧠 reducing sadness/depression

Feelings of loneliness and isolation are on the rise in the U.S. digitally, and physically. More than 60% of Americans are lonely, feel left out, poorly understood, and that they lack meaningful companionship.¹² A report found a nearly 13% rise in loneliness since 2018.¹³ Loneliness is also strongly linked to mental health issues such as anxiety and depression.

What is causing this loneliness? Feelings of loneliness and isolation are connected with higher social media usage; 73% of heavy social media users reported feeling lonely, compared with 52% of light social media users.¹⁴ It’s sad yet unsurprising, then, that Gen Z respondents (18–22 years old) had the highest average loneliness score.¹⁵

Feelings of loneliness are potentially further exacerbated by the content we engage with on social media. “Engagement” is a metric often used by consumer social media companies as a way to prove they are providing value. However, at Facebook, the models of what content to show you to maximize engagement also “favor controversy, misinformation, and extremism.”¹⁶ This creates a negative flywheel where this content gets more engagement, which results in more of this content being prioritized, repeatedly. For example, Facebook employees found that users who would “post or engage with melancholy content — a possible sign of depression — could easily spiral into consuming increasingly negative material that risked further worsening their mental health” and this issue was reinforced by existing content-ranking models.¹⁷

Feelings of isolation are mirrored by actual isolation and self-segregation in the U.S. by political party lines. People are physically living in partisan bubbles, meaning Democrats self-select to live near others Democrats who share their political party affiliation and views; the same goes for Republicans.¹⁸ This co-location with only those with the same political party is nearly ubiquitous and agnostic of whether U.S. residents live in a city or suburb or rural areas.¹⁹ This self-segregation along political party lines in the physical U.S. seems to mirror the isolation and echo chambers that exist in the digital world.

There is no great alternative to social media for news. Traditional media can also perpetuate problematic narratives around minorities and people of color — if they even bother to cover them. Researchers at the University of Leeds shared reported that minorities received very little general news coverage in the U.K., but figured prominently in stories with “specific news agendas, notably immigration, terrorism, and crime.”²⁰ Brands and media advertisers are not doing much better in terms of diverse and inclusive representation. For example, an analysis of 27,000 Instagram images showed that the fashion industry’s Black Lives Matter mea culpa resulted in little to no change in representation of people of color.²¹

The pandemic has accelerated the general increase in loneliness and isolation. This has been a challenging time for U.S. workers, who face an increase in mental health issues.²² For example, 75% of U.S. employees struggled at work due to anxiety caused by the pandemic and other recent world events and 80% would consider quitting for a company with a greater focus on supporting mental health.²³ Employees that shifted to remote work are also experiencing new challenges. According to a recent survey: 4 out of 5 remote workers find it hard to “shut off” in the evenings, 50% cite sleep patterns interruptions, and 45% say they feel less mentally healthy while working from home.²⁴

So, what opportunities are there to reduce sadness/depression? Some that jump to mind are:

1. Promote wellness as a lifestyle by creating shared experiences that bring people together and build bonds. There are already a lot of different approaches to this — from Peloton and Strava to BetterUp and Headspace — so figuring out a unique, significant problem to solve or insight is critical.
2. Create an environment that rewards engaging with diverse thoughts and people and helps them disengage from unhealthy media habits. This seems like an extremely challenging but potentially rewarding endeavor. Companies like Clubhouse are already creating forums for potentially diverse groups to interact, while others like Dispo are attempting to introduce consumption constraints; anything new needs to meet an unmet need and answer the questions: “why this? And why now?”

As Founder/Investor Sari Azout recently tweeted:

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Social Networks (old) = people you know sharing things you don't care aboutSocial Networks (new) = people you don't know sharing things you care about🚀 Bringing online relationships IRL is an infinitely more exciting opportunity than digitizing IRL relationships 🚀

What’s next?

I’ll continue to deep-dive into these two spaces. I plan to generate deeper insights into pain points, then begin to converge on more specific problems, markets, and opportunities. This will hopefully lead to testable hypotheses and ideas, and create a flywheel of testing and learning, increasing my velocity as I engage in this process and move from the “idea” to “build” phase.

Thoughts, feedback, advice, questions, or words of encouragement?

Please feel free to reach out on Twitter.

Finally, a special thanks to Zorayr Khalapyan for the suggestion to write about this and Amit Sankaran, Asad Akram, Jen Yip, Kate Yuan, and Leon Lin for the thoughtful feedback, edits, and support.

[1] https://hbswk.hbs.edu/item/how-gender-stereotypes-less-than-br-greater-than-kill-a-woman-s-less-than-br-greater-than-self-confidence

[2] Ibid.

[3] https://www.mckinsey.com/featured-insights/diversity-and-inclusion/women-in-the-workplace

[4] https://hbr.org/2019/02/research-men-and-women-need-different-kinds-of-networks-to-succeed

[5] https://hbr.org/2018/09/dont-underestimate-the-power-of-women-supporting-each-other-at-work

[6] https://www.mckinsey.com/featured-insights/diversity-and-inclusion/women-in-the-workplace

[7] https://www.amanet.org/articles/time-outs-take-an-increasing-toll-on-women-s-careers/

[8] https://www.nytimes.com/2020/11/17/business/economy/women-jobs-economy-recession.html

[9] https://www.mckinsey.com/featured-insights/diversity-and-inclusion/women-in-the-workplace

[10] https://www.amanet.org/articles/time-outs-take-an-increasing-toll-on-women-s-careers/

[11] Ibid.

[12] https://www.npr.org/sections/health-shots/2020/01/23/798676465/most-americans-are-lonely-and-our-workplace-culture-may-not-be-helping

[13] Ibid.

[14] Ibid.

[15] Ibid.

[16] https://www.technologyreview.com/2021/03/11/1020600/facebook-responsible-ai-misinformation/

[17] Ibid.

[18] https://news.harvard.edu/gazette/story/2021/03/democrats-and-republicans-live-in-partisan-bubbles-study-finds

[19] Ibid.

[20] https://www.nytimes.com/2021/03/10/world/europe/harry-meghan-media-race.html

[21] https://qz.com/1971689/fashion-brands-arent-keeping-their-instagram-diversity-promises

[22] https://www.forbes.com/sites/chriswestfall/2020/10/08/mental-health-leadership-survey-reveals-80-of-remote-workers-would-quit-their-jobs-for-this

[23] Ibid.

[24] Ibid.