The 6 most important things to know about SaaS+ product architecture

Welcome to TechCrunch+ Tuesday

“SaaS+” refers to software companies that augment their core products and services with value-adding features like embedded e-commerce, insurance or payments processing.

Baking these features into the product pipeline creates secondary convenience that delights customers — along with new revenue streams that thrill investors.

Drawing from their experience building a platform for youth athletics, Justin Kaufenberg (managing director at Rally Ventures) and Greg Blasko (co-founder of Monoline) explain how to “build the foundation of your SaaS+ house correctly” with multimerchant cart technology, parent-child data models, and other ideas.

All six recommendations include detailed examples of software architecture choices made inside companies like Kayak, Amazon and Shopify that combine to boost the number of transactions each user makes.

“Being aligned on these concepts will drive product roadmap, core technical architecture, pricing strategy and product marketing,” according to the authors.

Thanks very much for reading TC+!

Walter Thompson
Editorial Manager, TechCrunch+

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Never express your ‘use of funds’ slide as percentages

Building a pitch deck is like four-dimensional chess: Founders need to give investors a convincing narrative that will carry the company from this fundraising round into the next one.

Some teams like to share slides that explain how they plan to allocate funding, but Haje Jan Kamps says percentage breakdowns are a “red flag” to potential investors.

“How much tech do you need to have developed? How many customers and how much revenue do you need? What staff do you need to develop that tech, sell to those customers, and support them?

In other words: “You’re raising for milestones, not for percentages or runway.”

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4 ways to show customers they can trust your generative AI enterprise tool

In light of our ongoing debate about the existential dangers of AI, it was interesting to sit in a theater last night and watch a three-hour epic about the dawn of the Atomic Age.

Eight decades later, we’re once again rushing into a new technological era without first creating a framework for ethics, safety, trust, or a thousand other considerations.

Since there are no industry standards or government agencies guiding AI development, startups need to establish new best practices, according to TC+ contributors Luigi La Corte and Leo Arango.

“Providers that take active steps to reduce the potential for LLM ‘randomness’ and build the most trust will be outsized winners.”

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Pitch Deck Teardown: BusRight’s $7M Series A deck

America’s school buses comprise the country’s largest public transportation fleet: According to one estimate, students take 10 billion trips each year.

School-bus management platform BusRight recently raised a $7 million Series A with a “well-designed” deck that’s “full of careful touches,” according to Haje Jan Kamps:

1. Cover
2. Go to market
3. Target audience
4. Market size
5. Problem
6. Solution/product
7. Traction
8. Sales process
9. Business model/unit economics
10. Testimonials
11. Sales decision dynamic
12. Growth projection
13. Team
14. Closing/contact

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Ask Sophie: What are the visa options for a startup founder with family?

Dear Sophie,

I’m a startup founder in Berlin. I just returned from a visit to Silicon Valley where I met with a new customer. On the trip I realized I need to be based in the U.S. to grow our base with U.S. customers.

What are the best visa options for my family and me? Will any of them allow my husband to work and continue his career?

— Seeking Scale

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Looking for your next book? These 9 authors have reading recommendations for you

• Adam DuVander
• Phil Rosen
• Adi Polak
• Andrew Lee Miller
• David Kadavy
• Sarah E. Brown
• Zeke Faux
• David Spinks
• Purna Virji

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Making AI trustworthy: Can we overcome black-box hallucinations?

Characters in cartoons might imagine giant hot dogs when they’re hungry, but a large language model (LLM) can hallucinate for a variety of reasons, such as poor data quality or an unclear prompt.

Major AI platforms “infer and extrapolate based on what they believe to be the most likely answer, not actual data,” according to Dr. Mike Capps, CEO and co-founder of Diveplane.

Instance-based learning, on the other hand, compares training data points “against each other to gain insight into the dataset and the predictions,” says Capps. “In other words, IBL ‘shows its work.’”

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