Todd McKinnon of Okta on the current state of Enterprise AI sales: "Our biggest competitor is confusion. We're competing against confusion. So our solution has to be clarity. Customers are confused because there's so much excitement and so much opportunity in AI... they have 17 vendor meetings and every vendor tells them they have the right answer"

I’m super excited to announce Synthefy’s $6.5M seed round, led by Wing Venture Capital and joined by Haystack, Samsung Next, Canonical, Lightscape, and angels and operators from OpenAI, Microsoft, and Meta. Setting the price of every Uber ride in real time. Spotting the early signs of disease from thousands of patient measurements. Blocking a fraudulent payment before money moves. Keeping the power grid stable as supply and demand change every second. These decisions are not waiting for a better chatbot. They require Machine Intelligence, systems that can learn from massive volumes of structured data and make predictions beyond human scale. At Synthefy, our vision is to advance Machine Intelligence, enabling enterprises and users to make predictions on their troves of structured data that enable them to make critical business decisions. Nori is our first foundation model in a class of AI that will transform prediction. It already unlocks brand new ways of looking at prediction. But this is only the beginning of our journey towards zero-shot prediction that outperforms any bespoke ML. Our mission is to give customers predictive answers from their structured data that they cannot get from today’s tooling, 100× faster and at one-tenth the cost of bespoke ML. We aim to make Nori the universal prediction engine that enterprise software and agents call whenever they need to forecast, score risk, or make a decision from structured data. I’m deeply grateful to my co-founders, the Synthefy team, our early users, and investors. Special thanks to @ai for backing us from day -10, when I was still learning what PMF meant, and to Gaurav (Wing) for seeing the ambition and helping us take it further.

GLM-5.3 uses the same base model as GLM-5.2 with all the gains coming from post-training. It saw a +50% improvement on their in-house code bench and Terminal-Bench 3.0 jumped over 20 points. shared how they scaled their environments:

Good read on how Ramp allows customers to "build" their own integrations and has dropped integration time from weeks/months to hours. "On the customer's side, they describe what they want, the integration gets built underneath, and the task just completes. On our end, an internal integration factory turns that same demand into first-party integrations for everyone. We've already shipped 75 integrations this way"

Toast might be one of the few public SaaS companies that have launched a true "AI-native services" offering. Toast IQ Grow is a $499/month AI marketing service that pairs an AI agent with human support. It is the fastest-growing new offering Toast has ever launched

Got a Matic a few months ago and it's incredible and it keeps getting better through software updates like these. Also had a chance to interview @mehul on the hard-earned lessons from building Matic which will be out next week

Pinterest Average Revenue Per User by region in Q2: • US/Canada: $8.30 (+14%) • Europe: $1.35 (+4%) • Rest of World: $0.23 (+21%) US/Canada monetizes at ~6x of Europe which monetizes at 6x of Rest of World per user

Feels like most software companies are moving >10% in either direction on earnings this quarter: • Atlassian: +31% • Twilio: +27% • Shopify: +19% • Zeta: +15% • Palantir: +12% • Klaviyo: -15% • Figma: -15% • HubSpot: -19% • Datadog: -19%

Non-human traffic passed human traffic on Cloudflare's network in May for the first time. Cloudflare believes in five years it could be 1,000x human traffic as humans become "a rounding error on the internet"

Interesting to see SaaS companies starting to report MCP usage on earnings calls: - Datadog: MCP tool calls up 4x q/q, 22x since Q4 2025 - Figma: MCP write usage up 75% q/q - Atlassian: MCP calls up 400% q/q

Uber is live with AVs in 7 cities and says they'll be expanding with multiple partners across the coming years: 2026: Zoox in Vegas, Nuro/Lucid in SF, Wayve in London & Tokyo, Baidu in London, Pony in Zagreb 2027: NVIDIA/Stellantis in LA & SF 2028: NVIDIA/Stellantis in 28 cities, Rivian in SF & Miami

Datadog's largest customer, widely believed to be OpenAI, recently renewed a nine-figure contract across 17 products. However, they've reduced usage starting in Q3 which is large enough to impact Datadog's guidance for the year

Per Pinterest earnings call, open models they post-trained on their own data costs under 8% per transaction versus comparable closed models Their CEO said: "Any CEO that’s not taking advantage of open source models is almost certainly wasting a lot of their shareholders’ money"