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Empowering your Product Teams, Bootstrapping Your Startup & What's in Store for 2024?

Author

Alastair Preacher
December 22, 2023 • Estimated Reading Time: 22 minutes

We track Product so you don't have to. Top Podcasts summarised, the latest AI tools, plus research and news in a 5 min digest.

Hey, Product fans!

As Christmas is fast approaching it seems time to reflect… We’ve been going for a month now and this marks our 20th edition of Product Tapas 👀 🥳!

Ok so not the biggest milestone, but when I started this I didn’t quite know what to expect. It was done as a test and it seems to have resonated (and I’m still enjoying creating them) so I’m going to keep the test going!

That said, this is likely to be the last serving of Tapas for the year. So it’s a bit bigger today. Thanks for the continued support, have a great holiday period and an even better New Year! See you in 2024 🚀 

Here’s today’s sumptuous edition of Product Tapas! 🌮🎅 

🔥 What's Sizzling? 🔥

📰 Not Boring: We're serving a tech feast with headlines from Bill Gates’ annual "Year Ahead" letter to the latest in AI and console gaming. Dive into the GoPro Best of 2023 montage, and up to speed on VanMoof 2.0 and Apple's Vision Pro. Plus, catch the pace with Waymo's driverless milestones and Aston Martin's sleek Apple CarPlay interfaces. A dash of EU antitrust action against Apple adds zest to this platter! 🚗💻

🎄 Festive GPTs & Timesavers: As it’s holidays for many, we're gifting you Snooze.ai for personalised out-of-office responses and Simple Analytics to chat with your data. Plus, unwrap our exclusive list of 200 GPTs – all for free! 🎁🤖

🍔 Blog Bites: We cover Marty Cagan's insights into the future of product management. From the evolving roles of product managers and leaders to the integration of Generative AI, we're dishing out a full course of predictions to prep you for the coming year. 🚀📆

🎙️ Pod Shots: We’re wrapping up the year with three podcast highlights. Following on from Cagan’s piece, we delve into the ethos of empowered product teams, bootstrap wisdom from Jason Fried, and the exciting frontier of text-to-video AI.🎄🔊

So, grab your favourite holiday treat and settle in.

Remember, your thoughts add flavour to our community – keep sharing and inviting friends to join the feast. 🚀👇🍽️

OK sorry, not sorry for all the puns. I’ll be sure to temper those come 2024. In the meantime have a great festive period and here’s to a fantastic 2024. 🎊

Happy Reading!📚

📰 Not boring

📰 Time-Saving Tools & GPTs

  1. Perfect for the holidays - Snooze.ai: Send personalized out-of-office responses and automatically loop in backups on urgent conversations

  2. Chat with your analytics for free with Simple Analytics

  3. Given it’s Christmas, we’re giving away our curated list of c200 GPTs for free! 🔥 Check it out by clicking the button below 👇️ 

📱 Check out our recent social posts

Did you know we are all over the socials? Here’s where we put up our Product Tips and tricks in Reels/Shorts/TikTok clips. Plus of course, you can also follow us on Twitter. We’d love it if you can help follow and share the love to build up our presence there.

@producttapas

🎬 Unveiling User Research Myths! 🕵️‍♂️ Are you stuck trying to get a 'representative sample' in your user research? Think again! We bust t... See more

🍔 Blog Bites

🌟 Product Predictions 2024

‘Tis the season! - here we’ve got a summary of Marty Caga’s views on what lies ahead in 2024 for Product.

What lies ahead for Product in 2024?

📖 Read the full article here 

📆 Published: December 19, 2023

Reading Time: <1 Minute - Time Saved 4 minutes! 🔥 

 🐝 What's The Buzz? 🐝 

Marty Cagan shares insights on his view on what the future holds for the product community. Covering a range of topics from the role of product managers to the impact of Generative AI, he provides a comprehensive look at the anticipated trends and challenges in product management for 2024.

🌟 What's The Big Deal? 🌟 

Key takeaways:

  1. Product Managers: Marty’s hope is for more companies to adopt the model of strong, empowered product managers, though there's concern this may swing back given Air BnB’s recent well-covered shift.

  2. Product Owners: Marty’s been a vocal critic of POs for a long time. No change here - he continues to criticise their rise as damaging to the craft and hopes for a shift away from this trend.

  3. Product Teams: Again a big proponent of empowered teams he crystalises his distinction between feature teams and empowered product teams, with a hope for more companies to embrace empowerment in 2024.

  4. Product Leaders: Strong product leaders are seen as crucial for fostering strong product teams and managers.

  5. Product Ops: The article expresses hope for a focus on evidence-based decision-making in Product Ops, as opposed to a process and governance approach.

  6. Customers & Data: Recognising the strong push for data-led decision-making, Marty emphasises the need for teams to also engage directly with customers and not rely solely on quantitative data.

  7. Process: Marty advocates for a principles-focused approach over a strict adherence to processes and hopes this will be a continued trend.

  8. Product Coaches: Again staying on track with previous years, he stresses the importance of experienced product coaches in guiding teams and leaders.

  9. Product Model: Marty calls for a consensus on the principles defining strong product companies, rather than a focus on processes or tools.

  10. Generative AI: Not unexpectedly AI makes an appearance. Marty highlights the potential of AI in enhancing product decision-making while warning against over-reliance on AI tools.

💡 Why Should You Care? 💡 

Marty is the OG Product guy so it’s always worth reading what he has to say. He’s pretty metronomic on the topic and some could argue there’s not much new here. But if it aint broke….? Plus if you haven’t read his stuff before (really??) it’s definitely worth checking out.

📖 Read the full article here 

🎙️ Pod Shots

As it’s Christmas 🎄 we’ve thrown in 3 Pod Shots to see the year out in style!

Continuing the SVP / Empowered Teams topic we start off there with Andrew Skotzko’s recent “Product Experience” podcast. Next we cover Jason Fried’s recent appearance on Lenny’s Podcast. It’s a great contrarian view to the VC model and covers loads of information about bootstrapping your startup, staying small and optimising for profit - I see this being somewhat on-trend for 2024.

Finally talking about being on-trend, I had to throw something in about AI. I’ve been messing around with text to video for our social channels. Whilst I’d say the output is mixed (on the side of amazing - but a little too stale for me) this is a trend you don’t want to fade. See below for some of the recent videos I’ve created.

🎙️Empowered Product Teams

🕒 Estimated Reading Time: <2 minutes. Time saved 26 minutes 🔥 

💡 Introduction

As we discussed above, the concept of empowered product teams has become increasingly popular. In this episode, Andrew Skoczko, a product leadership coach, shares his insights on what it means to have an empowered product team and how organisations can work towards achieving it. He emphasises the importance of trust, autonomy, and accountability in building strong product teams.

🧠 Defining Empowered Product Teams

Andrew explains that empowered product teams are the result of a trade-off between autonomy and accountability. It is an agreement between teams and leadership, where teams have the freedom to come up with solutions while being accountable for delivering outcomes. Autonomy does not mean a free-for-all, but rather a bounded autonomy within certain constraints. The team is empowered to drive results and make creative decisions within the given boundaries.

🤔 Understanding Autonomy and Trust

Autonomy is often misunderstood as complete freedom to do whatever one wants. However, Andrew clarifies that autonomy within empowered teams means having the freedom to come up with solutions that drive results, while still meeting certain constraints. Trust is a crucial element in empowering teams. Andrew defines trust as choosing to make something you value vulnerable to somebody else's actions. Trust is multidimensional and can be categorised into dimensions such as sincerity, competence, reliability, honesty, and respect.

🤝 Building Trust within Product Organizations

Building trust within product organizations requires effort from both leaders and team members. Leaders need to earn trust by insisting on strong thinking, managing their biases, and not overusing veto power. They should also extend trust by giving up control, creating space for teams to explore ideas, and leading through context rather than control. Celebrating wins and acknowledging mistakes are also important in building trust. Team members, on the other hand, can build trust by externalizing their thinking, bringing stakeholders along for the ride, and giving credit where it is due.

🛣️ The Journey to Becoming a Strong Product Team

Andrew advises against trying to jump straight to an empowered product team without going through the necessary steps. He suggests a deliberate approach that starts with the ability to ship good products. Once the organisation can consistently ship, the focus should shift to collaborative problem-solving and product discovery. Finally, product leadership and strategy come into play. This journey takes time and can range from six months to three to five years, 👀 depending on the size and complexity of the organisation.

🙏 Practical Tips for Organizations

To start the journey towards empowered product teams, organizations should focus on the following:

  1. Shipping products: Ensure the ability to ship products regularly, with a benchmark of at least every two weeks.

  2. Collaborative problem-solving: Encourage cross-functional teams to engage in product discovery and prototyping.

  3. Product leadership and strategy: Develop a clear product vision and strategy, and provide the necessary context for teams to make decisions.

  4. Transforming the relationship: Once credibility and momentum are built, organizations can start making bigger changes in the company-level relationship.

❓️ Conclusion

Building empowered product teams requires a deliberate and gradual approach. Trust, autonomy, and accountability are key elements in creating a strong product organization. By earning and extending trust, leaders and team members can foster a culture of collaboration and innovation. The journey towards becoming an empowered product team takes time, but the rewards are worth it. Organisations that embrace this approach will be better equipped to deliver products that truly matter.

  • "The Thin Book of Trust" by Charles Feldman

  • "Growing Groups into Teams" by Pam Fox Rollin

🔗 Listen to the Original full Episode: here

⏰ Timestamps:

  • 00:00:41 - Podcast Theme and Host Introduction

  • 00:01:21 - Guest Introduction: Andrew Skoczko

  • 00:03:06 - Defining Empowered Product Teams

  • 00:04:47 - Misconceptions About Team Autonomy

  • 00:07:11 - Product Leadership Challenges

  • 00:09:52 - Trust in Product Teams

  • 00:11:15 - Rebuilding Trust Within Teams

  • 00:14:50 - Trust Dynamics Between Leadership and Teams

  • 00:19:33 - Steps to Becoming a Strong Product Team

  • 00:26:49 - Timeline for Organizational Transformation

  • 00:29:12 - Closing Remarks and Credits

🎙️ Challenge your thinking on fundraising, goals, growth & more

🕒 Estimated Reading Time: <2 minutes. Time saved 100 minutes 🔥🔥 🔥

Embracing the Bootstrap Ethos 🚀

In the realm of entrepreneurship, the allure of venture capital and the pursuit of unicorn status often overshadow the merits of bootstrapping. However, the latter offers a compelling alternative, one that hinges on the fundamental skill of making money—a skill that is honed through practice and necessity. Jason Fried, co-founder and CEO of 37 Signals, champions this approach, advocating for the value in building a business that thrives on profitability rather than external funding.

37 Signals, the company behind Basecamp and Hey, exemplifies this philosophy. With no investors, no board, and no intention to go public or sell, they've carved out a niche of success, boasting 24 consecutive years of profit. Their model is a testament to the viability of bootstrapping, demonstrating that a company can flourish without the crutch of venture capital.

The Power of Constraints and Intuition 🧠

Fried's approach to business is refreshingly contrarian. He posits that constraints, such as small teams and limited cash flow, often lead to better outcomes. At 37 Signals, product development is a dance of discipline and creativity, where features are crafted by pairs—a designer and a programmer—within a strict six-week timeframe. This method, detailed in their ShapeUp framework, ensures that projects are manageable and that teams remain agile and focused.

The company's decision-making process is equally unconventional. Eschewing data-driven methods, Fried relies on gut instinct and intuition. This reliance on human judgement over metrics may seem risky, but it aligns with the company's overall ethos of simplicity and clarity. It's a reminder that, at its core, business is about human experiences and that sometimes, the best decisions come from a place of instinct rather than spreadsheets.

The Infinite Game of Business 🌌

Fried's perspective on success is not about reaching a finish line but about enjoying the journey. He views his career as a continuum, where the joy comes from the act of creating and selling products that resonate with like-minded individuals. This philosophy is encapsulated in the concept of the 'infinite game', where the goal is not to win but to keep playing, to keep finding fulfilment in the work itself.

This mindset extends to the company's operational strategies. For instance, after each six-week cycle of product development, the team engages in a 'cool down' period, allowing for reflection, minor tweaks, and preparation for the next cycle. This practice ensures that the team remains energised and that the work continues to be a source of inspiration rather than exhaustion.

A Model for the Many, Not the Few 🌍

While Fried's approach may not be for everyone, it offers a compelling alternative to the traditional venture-backed path. It's a model that prioritises sustainability, employee well-being, and long-term enjoyment over rapid growth and exit strategies. It's a reminder that there are many ways to build a successful business and that sometimes, the road less travelled can lead to a more fulfilling destination.

In a world where the startup narrative is dominated by tales of massive funding rounds and billion-dollar valuations, 37 Signals stands as a beacon for a different kind of success—one that is measured not by the size of the company but by the happiness of its creators and the value it provides to its customers. It's a practical example that success in business doesn't always have to follow the Silicon Valley playbook.

As a Product Manager, the insights from Jason Fried's podcast can be incredibly valuable for shaping your approach to product development, team management, and strategic decision-making. Here's how you can apply the information:

Embrace Bootstrapping

  • Practice Financial Discipline: Focus on profitability from the start. Make decisions that ensure your product is financially viable without relying on external funding.

  • Value Constraints: Use constraints as a tool to drive creativity and efficiency within your product team. This could mean setting strict deadlines or limiting resources to encourage innovative solutions.

Small Teams and Efficiency

  • Adopt Small Teams: Implement the two-person team structure for projects where feasible, to encourage focus and accountability.

  • Time-Bound Work: Introduce a maximum time frame for projects, similar to the six-week cycle mentioned by Fried, to prevent projects from dragging on and to maintain team morale.

Decision-Making and Planning

  • Trust Your Gut: Encourage your team to use their intuition and experience in decision-making, alongside data.

  • Flexible Planning: Avoid long-term planning that is too rigid. Instead, plan for the short to medium term and be prepared to adapt as circumstances change.

Operational Tips

  • Cool Down Periods: After intense periods of work, allow your team time to refresh and work on less critical tasks. This can prevent burnout and foster a culture of sustainable work.

  • Avoid Promises: Be cautious about making promises on delivery dates, especially "by the end of the year" promises that can set unrealistic expectations.

Applying the Insights

  • Experiment with ShapeUp: Try implementing the ShapeUp framework for product development on a low-criticality project to see if it improves efficiency and outcomes.

  • Encourage Open Discussion: Foster an environment where team members feel comfortable sharing their feelings and thoughts about the work, rather than just data-driven insights.

By integrating these practices into your role as a Product Manager, you can build a product development process that is efficient, sustainable, and adaptable to change. This can lead to a more engaged team, a better product, and ultimately, a more successful business.

Listen to the full episode here

⏰ Timestamps

🎙️ Exploring the Future of Text-to-Video AI Models

🕒 Estimated Reading Time: 3 minutes. Time saved 30 minutes 🔥 

Introduction

In this episode of the a16z podcast, they dive into the world of text-to-video AI models. While text-to-text and text-to-image models have gained popularity, text-to-video models present unique challenges due to the large size of video files and the need for dynamic representations of the world. However, researchers at Stable Video Diffusion have recently released an open-source generative video model that aims to tackle these challenges. Not to mention there are a heap of other text-to-video AI software already available for you to try.

In this episode, Andreas Blattman and Robin Rombach discuss the difficulties of text-to-video AI, the importance of accessible models, and the potential applications of this technology.

😬 The Challenges of Text-to-Video AI

Text-to-video AI models face several challenges that make them more complex than text-to-image models. Firstly, video files are much larger in size compared to text or images, often reaching gigabytes. This poses difficulties in data loading and processing. Additionally, video models require a more dynamic representation of the world, incorporating factors such as physics of movement and 3D objects. This complexity makes it harder to generate realistic and coherent videos. However, despite these challenges, the researchers at Stable Video Diffusion have taken on the task of developing a state-of-the-art open-source generative video model.

🗺️ The Journey from Text-to-Image to Text-to-Video

Stable Diffusion, a text-to-image generative model, served as the foundation for the development of Stable Video Diffusion. The researchers at Stable Video Diffusion recognized the potential of video models in capturing the physical properties of the world. By training the model on a large dataset of videos, they aimed to enable the generation of videos with realistic object and camera motion. The model's ability to learn from the temporal dimension of videos opens up possibilities for understanding the world and even deriving physical laws from the model's representations.

⚡️ The Power of Diffusion Models

Diffusion models, the go-to models for visual media, differ from autoregressive models in their representation of data. While autoregressive models generate data token by token, diffusion models gradually transform noise into data in small steps. This iterative process allows for better spatial compositionality and the preservation of perceptually important details in the generated content. Furthermore, diffusion models offer the advantage of being able to generate high-quality samples with fewer sampling steps, leading to faster and more interactive user experiences.

👀 The Impact of Open-Source Models

One of the key factors contributing to the success and widespread adoption of Stable Diffusion and Stable Video Diffusion is their open-source nature. By making the models accessible to everyone, the researchers at Stable Video Diffusion have fostered a vibrant research community and encouraged innovation in the field. The open-source models have served as building blocks for developers and creators, allowing them to explore new possibilities and create personalized and individual content. The ability to fine-tune the models using lightweight adapters called LORAs further enhances the control and creativity of the users.

🌟 Applications and Future Possibilities

The release of Stable Video Diffusion has already sparked creativity among developers and creators. From animating memes to bringing famous artworks to life, the model has demonstrated its potential in various domains. However, there are still open challenges to address. One of the main priorities is enabling the generation of longer and more coherent videos, which requires advancements in processing capabilities. Additionally, incorporating multimodality, such as adding audio tracks synchronised with the video content, opens up new avenues for exploration. The future of text-to-video AI models lies in providing users with more control and faster rendering, allowing for real-time synthesis and personalized content creation.

📣 Conclusion

The development of text-to-video AI models presents unique challenges, but also exciting opportunities for understanding the physical world and enabling creative expression. The researchers at Stable Video Diffusion have made significant strides in this field, with their open-source models serving as a foundation for innovation and collaboration. As the field continues to evolve, advancements in processing capabilities and user control will drive the next wave of creativity and exploration in text-to-video AI

The 3 videos at the top of today’s newsletter were all made using text-to-video software. Whilst rough around the edges in places and I’ve not yet ponied up for the premium voices and avatar - you can see the potential. Let us know your thoughts in the comments. Do you want more, less, unsure?!

⏰ Timestamps

  • [00:00:24] Text-to-video challenges.

  • [00:04:39] Diffusion models vs autoregressive models.

  • [00:06:51] Improvements in image models.

  • [00:10:12] Video generation and computational demands.

  • [00:13:47] Interesting bugs during training.

  • [00:18:19] Incorporating LORAs for fine grain control.

  • [00:22:33] More control over video creation.

  • [00:25:22] Bringing artworks to life.

  • [00:27:10] Overcoming computational limits.

  • [00:30:49] Collaboration in the industry.

That’s a wrap.

Hope you have a great holiday period and a successful 2024! 🚀👋

Alastair & the Product Tapas Team 🍽️.

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