Introduction

Thinking back on this week, it didn’t go according to plan. My goal was as follows: finish designing the remaining Pando screens, design and build the landing page, and continue progressing on my JavaScript learning path.

However, it’s now 9pm Friday and none of those items are fully complete. The landing page isn't built, JavaScript study got deprioritised, and while the application screens are now close to completion, the design process took significantly longer than I expected.

Whilst that sounds like a failed sprint, I’m actually pretty happy with how it went. I’m probably one or two days behind where I aimed to be, but I gained a lot of clarity that I expect will save time further down the road.

Complexity ballooned again

As I worked through the remaining screens, I discovered that some important concepts in the product were still under-specified. By Tuesday I had created the initial user flow and designed the first iteration of the screens, so everything appeared to be on track. However, when reviewing those designs I realised I needed a more granular workflow than I originally accounted for.

Originally, Pando was centred around evaluating opportunities. The assumption was that users would submit an idea, receive an assessment, and then decide what to do next. However, as I pushed deeper into the workflow, it became clear that in order to prioritise opportunities effectively, they need to evolve over time with evidence.

That realisation introduced several new concepts and workflows that I hadn't fully accounted for. I needed a way to capture early ideas with minimal friction, track evidence over time, incorporate founder-specific goals and constraints, and ensure that prioritisation could adapt as confidence changed. At the same time, I was trying to balance depth with usability. Some parts of the workflow needed to be lightweight and fast, while others required more structure and analysis.

As I worked through the details, the relationships between the different parts of the system became clearer. More importantly, I became increasingly convinced that meaningful prioritisation can't come from a one-shot AI report. Opportunities need to evolve through evidence, and that evidence should influence what gets worked on next.

At this point I made a deliberate decision to slow down and work through the details properly. On the one hand I wanted to avoid costly redesigns later, but I also needed to decide whether the problem I wanted to solve was truly worth the effort required to solve it well. Had I rushed into implementation, I would almost certainly have needed to redesign large parts of the product later. Spending extra time clarifying the system now felt like the better decision.

Looking into competitors helped to clarify the space

In parallel with refining the workflow and designing the remaining screens, I spent some time researching the competitive landscape to better understand where Pando would sit.

As the product evolved, I felt like I was encroaching into a different product category. What began as validation tooling was gradually moving closer to customer feedback, product discovery, and prioritisation software.

I found that it’s a congested space, with some fast growing competitors and strong incumbents.

Most established players fall into one of three categories: customer feedback intelligence platforms (Enterpret, Chattermill, Kraftful), research repositories (Dovetail, Condens, Great Question), or product management and prioritisation tools (Productboard, Aha!, ProdPad, airfocus). While they solve different problems, they all help teams understand customer needs and decide what to build.

What stood out, however, was that these mostly target established product teams with existing customers, research processes, and roadmaps. That helped clarify where Pando should focus. Rather than helping teams prioritise features that already exist on a roadmap, the most interesting gap appears to be helping founders and small teams decide which ideas deserve validation before they reach a roadmap.

Rather than focusing on customer feedback management or product operations, Pando can focus on helping founders develop conviction in opportunities before committing resources to execution.

So is Pando commercially viable?

I’m skeptical, probably not.

The space is clearly large enough to support significant businesses, but most successful companies appear to monetize through enterprise research, customer feedback, or product management workflows rather than pre-revenue founder validation.

My strongest concern is retention. Validation is generally a temporary activity. Once a founder commits to building something, the need for opportunity evaluation naturally declines. To become a durable business, Pando likely needs to evolve into an ongoing decision-making workflow rather than a one-time validation tool.

There are other challenges too. Solo founders generally have limited budgets, making pricing more difficult. Many already rely on a combination of spreadsheets, Notion, existing product tools, and LLMs to manage their thinking. It's not yet clear whether this problem is painful enough for people to adopt a dedicated solution.

I'm also cautious about drifting into project management territory. That's a crowded market with strong incumbents and products that are already deeply embedded in company workflows.

Finally, I'm not convinced there is a particularly strong "why now". AI makes analysis easier and lowers the cost of building software, but founders have been trying to validate ideas for a long time. I'm not sure the underlying problem has fundamentally changed.

Taken together, I don't think this is a strong commercial opportunity.

But after thinking it through, I decided that I’m OK with this. My goal over the next few months isn't to build a venture-scale SaaS. It's to increase my learning velocity, become a better builder, create useful content, and develop products that solve problems I personally care about. If executed well, Pando should help me achieve all of those things. More importantly, it gives me a vehicle to explore a problem space that I find genuinely interesting. Even if Pando itself never becomes a large business, it may lead me towards opportunities that do.

Given those goals, continuing to invest in the project feels like the right decision.

Looking ahead

Having worked through the product design and thought more carefully about the commercial realities of the space, the next step is execution. I've given myself a deadline to get a usable Pando MVP live before I leave for a friend's wedding in mid-August.

It’s important not to spend too much time planning now and not enough time shipping. I also need to continue investing in my software development skills alongside the project given that one of my goals this year is to become less dependent on AI coding tools by strengthening my own technical foundations.

Now it’s time to ship the MVP, get it in front of users, and learn from what happens next.