Startup Dramas, Murky Valuations, & OpenAI's Concession

TLDR;

This week, we examine new dubious valuations, startup drama, and another telling event about NVIDIA’s future. We then move to the world’s first known attempt at leveraging inference-time compute for video generation and research showing how AIs learn similarly to humans.

Finally, we take a look at Amazon’s new feature and how OpenAI is conceding and adopting its biggest competitor’s communication protocol.

Enjoy!

AGENTS

The Future of Agent Payments

Manny Medina, founder and former CEO of Outreach, has launched a new startup called Paid, aiming to address the unique billing challenges faced by companies developing AI agents.

The company argues that traditional software billing models, such as per-user or usage-based pricing, are inadequate for AI agents that often operate autonomously and perform entire roles.

Paid offers a platform that enables agentic startups to create flexible pricing strategies—both fixed and variable—focused on profitable margins. The platform also tracks agents’ output to validate return on investment, effectively blending billing and HR management for the AI agent era.

Paid has secured €10 million (approximately $11 million) in pre-seed funding from investors including EQT Ventures, Sequoia, and GTMFund.

TheWhiteBox’s takeaway:

If you’re a regular reader of this newsletter, you’ll know that we have been proclaiming the death of seat-based pricing. With agentic software, it really doesn’t make sense.

Instead, we have been proposing usage-based pricing, where customers pay only for what they consume. This makes much more sense in a world where most software will act on our behalf based on what we instruct.

But Paid takes it a step further, and I think they are actually into something. The idea would be outcome-based pricing, getting billed only for successful agent inferences (the whole point of this platform is to measure agents’ success and clearly separate irrelevant inferences from those that matter).

Since agents are probabilistic-based software, picturing a world with 100% agent accuracy is pointless. Worse, if we factor in multi-agent scenarios, the customer will feel hopeless in trying to measure return on investments, let alone agent accuracy. Consequently, this idea of getting paid per successful outcome makes a lot of sense but feels incredibly hard to measure.

If Paid pulls it off, this is a billion-dollar startup in the making.

It’s also interesting to see how we are witnessing the creation of a new software stack around agents: new client-server communication protocols (MCP), new metering software (Paid), and auth for agents (Okta), among many others.

PRIVATE MARKETS

Perplexity, an $18 Billion Startup?

Perplexity AI, an artificial intelligence search startup, is reportedly in early discussions to raise up to $1 billion in a new funding round that would value the company at $18 billion.

This valuation represents a significant increase from its $9 billion valuation in December 2024. The startup offers an AI-powered search engine that provides real-time answers by searching the internet, positioning itself as a competitor to Google’s Gemini and OpenAI’s ChatGPT.

Furthermore, Perplexity introduced Comet, a web browser that leverages AI to perform complex searches and tasks. They plan…

Enjoyed the introduction? Subscribe or sign in to continue with this edition.