@pratduvvuri@Cisco@splunk It’s almost like money in a way. Its definition will evolve as the ecosystem matures, but fundamentally, tokenomics comes down to the economics of generating intelligence. The interesting part will be how we measure the value of that intelligence, not just its cost.
Your team’s AI bill doubled 🫠. Is that wasted spend, or money well spent?
Before you can answer, you need to know where the increase came from. More people using AI? A few heavy users? Unnecessary Opus 5.5 and Astra 6 use?
At Galileo (acquired by @Cisco) and now @splunk agent observability, we were piecing that story together across five AI providers, each with its own definition of usage.
Here's another qs - Whose budget does that usage belong to? Knowing someone’s manager doesn’t automatically give you the answer. In fact, finance may attribute your manager's spend to a different category than your spend...
We’ve been building tokenomics in Splunk Agent Observability to help employees understand their usage, managers understand adoption, and finance connect spend to budgets.
That gives people a starting point for deciding whether the spend makes sense :).
We learned A LOT building the tokenomics product for CRAZY different ICPs - Engineers, Finance folks and Management ..... all while building it for the scale of a 100K ppl at Cisco - our first customer.
I wrote all about in my blog (in 🧵), please tell us what you'd wanna see in a product like this.
what does tokenomics mean to you?
Sending lots of love to the Apple community on my last day as CEO. My title changes tomorrow, but the love I have for the Apple community never will. Thank you for being a constant source of inspiration. My gratitude is endless, and I’m excited for the next chapter!
Introducing https://t.co/TKDSTvTZEk
it's exactly like https://t.co/9Z9rHru2no
except 3/4th of your bid money is donated to people who don't have clean drinking water
→ 2.2 billion people don't have access to clean water today → meanwhile AI is on track to withdraw an olympic pool every 12 seconds → the 3/4th goes to https://t.co/t6YmFiVUgL, they have helped 92 million people so far get access to clean water for life → you pay them directly, it never touches our account
→ Get marketing done, Help a Person in need, Save on taxes
can we get to $1,000,000 donations?
New AI agents on the @e2b_dev map
👾@zapier Central - New AI workspace (in Beta) where you can teach bots to work across 6,000+ apps
🪐 @RelevanceAI_ - Let your AI Workforce help with Sales, Marketing, Operations & more
🍜 Brainsoup by @Nurgo - Build an AI team that works for you, on your PC
📅 bumpgen - AI agent that keeps npm dependencies up-to-date
⚙️L2MAC by @samianholt - Agent framework able to produce large complex codebases and entire books
Check out the full list: https://t.co/ICjwOaTPPT and add your own product via form or PR.
More coming soon!
1/ Some thoughts on the recent OpenAI and Google announcements, and what it indicates about what's next in AI.
Hint: post-training is REALLY important...
THREAD
🔗👇
Thank you for the invitation and the chance to talk about @e2b_dev giving agents the code interpreting layer ... and also chat a bit about life and hope for humanity. 👀
🧡 @Dest_BigLeagues@RONAKDINESH
Enjoying digging deeper into creating Custom GPTs.
I wish OpenAI let you take a Custom GPT you've built and then make calls to it using their APIs.
This would let you use the web UI as a "studio" (builder interface) but create your own apps based on that GPT.
Yes, I know I can just use the existing APIs to upload files and do anything that Custom GPTs can do. But, it's easier to build in the Custom GPT interface during dev/testing -- especially when non-devs are involved.