I paid $5 for a $0.50 coding task

Hey friend,

I kept coming back to one question this week: who is actually best placed to decide which intelligence should handle a task? Cursor already routes based on the coding context it sees. OpenRouter sees hundreds of models and providers. Frontier labs know their own models better than anyone. As model choice starts disappearing into the infrastructure, those are three completely different advantages. Interestingly, routing benchmarks are already suggesting it might not be the routing algorithm itself. The bigger advantage is who has the best data on what “good” looks like for that specific task. Which made me wonder: if that’s true, was Stripe’s $7B OpenRouter deal actually worth it?

Summary

Read time: 4 min

Highlights Of The Week

I paid $5 for a $0.50 coding task

Routing vs. Fusion, and why everyone suddenly cares 👇

Signals

Databricks closed a $5B round at a $190B valuation, and crossed a $7B revenue run-rate after growing more than 80% YoY.

OpenAI hired Wiz President and COO Dali Rajic as its new revenue chief, replacing former Slack CEO Denise Dresser after less than a year in the role.

Canva Code now generates interactive tools from a single prompt, pricing calculators, sign-up forms, quizzes, built on your brand guidelines and published on your own domain.

OpenRouter sold to Stripe for $7B

Anthropic ships enterprise auth for Claude connectors, no OAuth setup needed

Calendly Adds Meeting Notes

==Routing vs. Fusion, and why everyone suddenly cares

==

Routing chooses the best model for a task based on quality, cost, speed and reliability. Fusion sends the same problem to multiple models and compares or combines the answers. Routing asks, “Which model should do this?” Fusion asks, “Is this important enough to get several models involved?”

Both are becoming products. OpenRouter launched Fusion, where multiple models answer in parallel and a judge model looks for consensus, contradictions and gaps. That makes sense for research, strategy or anything expensive to get wrong.

Routing is where the trend is now. Stripe agreed to acquire OpenRouter, while Ramp launched Router.com the same day. The best model keeps changing. New models launch, prices move, providers hit limits and different models win at different tasks. Companies don’t want to benchmark all of that manually. They want one layer deciding where each request should go.

So was OpenRouter really worth $7B to Stripe? Maybe, but not because its routing algorithm is impossible to copy. OpenRouter has aggregation: hundreds of models, huge amounts of cross-provider traffic, pricing and reliability data, and developers already using it as the place where inference gets bought. Stripe already sits on the monetisation side. Now it also gets closer to deciding where AI spend gets allocated.

For Eli, we’re starting where a huge amount of AI spend already lives: inside the software companies are already paying for. Gartner estimates 85% of enterprise agentic AI investment is already bundled into existing SaaS and cloud renewals. So before companies start optimising every individual model call, there’s already an entire layer of AI subscriptions, licences and tools they need to understand and control.

The end state is not managing ChatGPT subscription over here, API spend over there and agents somewhere else. It’s one layer deciding what the company should use, what it should cost, and whether it’s actually creating value. See where it's at :

==MUST READ: When One AI Agent Can Access Everything

==

As AI agents connect to more apps, they also gain more access, cost and risk. Here’s how companies should think about ownership, permissions and visibility before agent sprawl gets out of control.

What’s In Their Stack?

This week: Andrew Yeung - Founder of Fibe, investor and one of the busiest people in the tech events world, Andrew’s stack is built around one thing: moving fast without adding more admin.

His AI and productivity layer includes Wispr Flow for voice, Granola for meetings, Poke for getting things done from anywhere, and Raycast for speeding up work on his computer. See Andrew's full stack →

Want to see what’s in your stack? Map it with ELI.work

Stay curious.

Ghita