Generative AI is building the foundation of proptech’s next wave

Welcome to TechCrunch+ Tuesday

Generative AI reminds me of ball bearings: the technology is relatively inexpensive, highly adaptable and a proven way to reduce friction.

Investors have taken notice: CB Insights reports that VCs poured $49 billion into AI last year, a 40% jump from the year before.

The hype so far has largely centered on chatbots and avatars, but “AI’s emergence will cut through material use cases in real estate tech,” says Kunal Lunawat, co-founder and managing partner of Agya Ventures.

For TC+, Lunawat explores several examples, including the potential for layering AI into construction workflows, using ML data to optimize bidding and estimation, and automating processes like obtaining insurance and underwriting mortgages.

“The opportunity for entrepreneurs in real estate tech across search, listings, mortgage, insurance, construction and sustainability is the kind that shows up once a generation.”

Thanks for reading,

Walter Thompson
Editorial Manager, TechCrunch+
@yourprotagonist

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Choosing a cloud infrastructure provider: A beginner's guide

At the risk of being dogmatic: all non-technical founders need to hire a CTO.

Most eventually will, but like many aspects of startup operations, this gap won’t be filled until it’s absolutely necessary.

In the meantime, someone needs to make fundamental decisions regarding cloud infrastructure and strategy.

“It’s essential to analyze the tools available before you decide on a cloud infrastructure provider to keep application maturity and running costs in check,” according to Sashank Purighalla, founder and CEO of BOS Framework.

In a guide that delves deeply into best practices for spinning up a cloud strategy, Purighalla examines the challenges and benefits of “cloud monogamy,” compares major providers, and offers tactics that can help developers avoid “analysis paralysis.”

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What do investors need from your problem slide?

Early stage investors usually understand verticals better than the aspiring entrepreneurs who pitch them.

In general, they’re seeking ideas that can scale and founders who can execute, which is why every pitch deck needs to describe “what could be better and how that gap in the market can be turned into an opportunity,” writes Haje Jan Kamps.

Using examples from presentations he’s analyzed in the past, Haje explains his framework to help first-timers articulate the value their startup creates and why it’s poised to grow:

• Who has this problem?
• How are they currently solving this problem?
• What are they willing to sacrifice for their current solution?
• What’s wrong with the way they are currently solving this problem?

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Cybersecurity teams, beware: The defender's dilemma is a lie

The Defender’s Dilemma is one of cybersecurity’s touchstones: “Defenders have to be right every time. Attackers only need to be right once.”

It may sound authentic, but David J. Bianco, a staff security strategist at Splunk, says it’s actually a false narrative that leaves systems less secure.

“Defenders rightly expect attackers to lie and cheat to achieve their goals, but sometimes we forget that lying and cheating can work both ways.”

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To improve close rates for technical interviews, give applicants feedback (good or bad)

“White coat syndrome” occurs when patients register artificially higher blood pressure because they’re anxious about visiting the doctor.

Technical interviews are similar: In a survey that crunched data from 1,000 people who conducted 100,000 interviews, a quarter of the candidates who received passing grades initially thought they’d failed.

“Our research shows that 43% of all candidates consistently underrate their technical interview performance,” said Aline Lerner, founder and CEO of interviewing.io.

In a comprehensive TC+ post, she offers a playbook for gathering and sharing “honest (and sometimes harsh) feedback” and asking post-interview questions that create objective benchmarks.

“Only about 25% of candidates perform consistently from interview to interview,” writes Lerner. “This means a candidate you reject today might be someone you want to hire in six months.”

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