The Science worked. The market didn't care.

👋🏼 Hi, I’m Moiz. I'm a Fractional Head of Product who helps top climate-tech teams build product from strategy, discovery, to execution. You’re receiving this because you’re building in climate and we’ve crossed paths. Each issue distills one proven concept that I use with my clients - and gives you a way to apply it to your work.

Here's what's inside:

This one’s a deep dive. Grab a coffee.

• A fascinating deep tech solar product with DOE validation, experienced team and solid business model
• Why I said "not yet" to this opportunity
• Where my discovery system shined and failed

Before we dive in - Sign up for my free workshop How I ran discovery to commercialize a deeptech solution in solar Learn the difference between Prompts vs Skills vs Agents Leave knowing how to build Claude Skills for your product workflows Sign up for Free

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Worth Repeating

“It doesn't matter how beautiful your theory is. If it doesn't agree with the experiment, it's wrong”

— Richard Feynman

A Solar product that should sell itself

A friend introduced me to a deep tech team with a solar product. This was a Founding team led by a PhD working on his 2nd company. We got along immediately: 30 mins turned into 90 mins and next steps.

Here's the use case and technology brief:

• Bifacial solar panels are designed to capture sunlight from both sides — front and back. In theory, they boost output by 5-30%.
• In practice, most solar farms have poor ground reflectance so the panels underperform.
• This team built a high-albedo ground coating that fixes that. DOE awarded them the Solar X Prize for it.

Furthermore, it looked like a relatively straightforward, cash-flowing business model. We'd finance via debt, offer $0 down and monetize on performance. And here's the kicker: they already had manufacturing and distribution lined up.

I could hear the boxes checking.

I was seriously considering joining as a co-founder.

The team's instinct was to ramp production, get financing and start implementation.

I wanted them to be right.

But I've worked on enough climate commercialization projects to test assumptions first.

"Who wouldn't want this?" is a Bias, Not a Strategy.

A coating that boosts solar output by 10-20% for $0 down? Who says no to that?

The assumption — that obvious technical value equals obvious market demand — is the most dangerous bias in deep tech.

It sends teams into premature scale and 6-8 months of trade shows, only to discover they had the wrong customer, wrong value proposition, wrong geography.

So before any of that, we stepped back and uncovered our assumptions. We laid out every assumption the commercialization plan depended on.

Then we asked ourselves, "Which of these assumptions do we feel least confident about?"

I guided the team towards testing the assumption that solar asset owners truly care about increased generation.

Then we started talking to customers.

What the market said

We only needed four discovery conversations to realize we weren't there. Here's what we learned from customers.

1. The asset owner didn’t talk about energy gain.

They talked about operational risk. Land lease obligations. Proving it to their legal teams it was worth it. They would need at least 1-year of field data to send an email to their engineering and finance teams.

2. The economics didn’t scale the way the physics did.

Inverter clipping meant that at larger installations, the energy boost might not translate into economic value. The science worked at every scale. The business case didn’t.

3. Golden Nugget - Target smaller solar farms first

Target < 10MW scale farms who have less operational and legal hurdles.

These conversations proved that our initial assumptions - The Problem, The Customer's Measurement of Success and Ideal Customer Profile - were all proven to be untrue.

Discovery pointed to field tests

We didn't charge forward into 96 more interviews.

It was clear that we'd hear the same thing every time. The market needed field results, not lab results.

Then, the Asset Manager might consider sending an email to his Legal team.

So discovery sent us back to the lab. Not because it failed — because it worked.

It told us exactly what we needed before we could move forward, event for grant money.

What's next?

I wish the answer had been "Build" instead of "Not yet."

I'd love to work with this team.

And the market keeps getting more interesting. Tesla is rolling out EV charging super sites with bifacial solar canopies.

I charged at one in California — it was brutally hot when I stepped out.

High albedo underneath those canopies would cool the site and boost output.

But only if the real-world performance data backs it up. I'm hopeful the team can come back with real-world data that we can bring to the market.

Because there is a real business to be built here.

That's what the discovery showed us.

From Insight to Action

After this project, I rebuilt my whole discovery system with Claude Skills. The fundamentals of my system work but I wanted to get to the insight faster.

I'm running workshops and cohorts to show you how.

• Free workshop - Claude Skills that turn Interviews into Product​
• Free coaching - What goes on the Roadmap? Bring your Idea and I'll help you decide whether to build it.
• ​Cohort #4 of AI Powered Customer Discovery Launches on March 17. Email me SHIP for a discount code.