Come with me if you want to sell.

There’s a version of the dystopian, Terminator-like universe where the machines are a little bit less T-1000 and a touch more like the one that tries to help John Connor. One company is leaning into that narrative: humans and machines working together to solve problems.

Workforce solutions company Asymbl built an AI SDR, gave it a job description and even a name.

“We gave him a name specifically to help the rest of our team think of him as an employee and not just a bot,” Asymbl CEO and founder Brandon Metcalf said. “We call him Theodore when he’s being naughty, and he’s Teddy’s when he’s doing a good job.”

Building an AI workforce: Theodore wasn’t an accident but rather was part of a deliberate drive to increase digital deployment in the organization. “We went through a program with Salesforce, of trying, iterating, adapting, coaching, all of that,” he said.

Keep reading here.—BS

Beauty is big business, and in 2021 that growth exploded. That year, a staggering $3.3 billion was raised in venture capital for beauty and wellness startups. Some of the checks were cut by VC titans like Tiger Global Management dipping their toe into the space, but that hasn’t always been the road to success.

Specialized funds are increasingly proving that deploying the biggest cash pile doesn’t necessarily mean you’re onto the next L’Oréal. True Beauty Ventures has carved out its own niche, quietly forging a path on a smaller scale that’s making a big impact.

Launched in 2020 by Rich Gersten and Cristina Nuñez, it isn’t your typical investment firm. True Beauty Ventures caps its funding at just $5 million, far less than some private equity firms are shelling out.

“We’re willing to write a smaller check, but we operate and behave like traditional private equity investors,” said Gersten. “I think that our unique point of differentiation is our sector specialization.”

Small check, big reward: True Beauty Ventures currently has a roster of 20 brands that includes Vacation, Crown Affair, Caliray, Dieux, and others. Gersten says smaller checks are a huge part of the unique value proposition the firm provides.

Keep reading here.—LI

In a world where every customer interaction can spark—or stall—growth, harnessing data and tech is essential. At The Modern Revenue Engine, we’ll explore how alignment, strategy, and smarter tools can transform revenue organizations. Hear from Jia Hyun, VP of Global Large Customer Sales at Reddit, as she shares lessons from building customer-first strategies at scale and offers insights you can apply to accelerate growth in 2026 and beyond.

AI may promise long-term efficiencies for your business, but enterprises tiptoeing into the arena (or “AI leapers” diving right in) can’t be too careful. Deploying AI tools is like peeling an onion; there’s layer upon layer to contend with, and without care, you’ll end up in tears.

According to a new report, 80% of enterprises are missing their AI infrastructure forecasts by more than 25%. The “2025 State of AI Cost Management” report, published by consulting firm Benchmarkit and cost governance platform Mavvrik, also finds 84% of companies see over 6% gross margin erosion due to AI infrastructure costs.

“These numbers should rattle every finance leader,” said Benchmarkit CEO Ray Rike. “AI is no longer just experimental—it’s hitting gross margins, and most companies can’t even predict the impact.”

Margin compression emerges as a real risk, and the catalysts for this fit into a few specific buckets:

• Hidden costs: The top-ranking is data platform usage (56%), followed by networking charges (52%).
• Visibility gaps: Most companies (94%) say they track costs, but only 34% have mature cost management.
• AI repatriation:​​ Only 35% include on-premises AI costs in reporting.

“AI is blowing up the assumptions baked into budgets,” said Mavvrik CEO Sundeep Goel. “What used to be predictable is now elastic and expensive.”

Big takeaway: Companies need to be smart about their investments: Scaling AI requires keeping a close eye on creeping costs, meaning more accurate forecasting, and perhaps more realistic expectations all around.—LI

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