AppZen raised $180M Series D. The headline number isn't $180M. 87% of expense audit + AP now runs autonomous across 500+ enterprises (65 of the F500). Not a productivity stat, The first load-bearing layer of the #AgenticFinance stack. https://t.co/bLOk9BBCUo
OpenAI bought Hiro Finance earlier this month. Focusing on Personal CFO chatbot. 7th acquisition of this year.
The buyer is the story. Not a fintech. Not b2b SaaS. The labs want to own "CFO copilot" natively. https://t.co/IVYFxbLydO
Also true for PMs, at least at @Rippling...
- No more planning decks, only markdown pushed to a git repo
- Customer issues identified in ~realtime using LogRockets scanned via MCP
- PMs fix your own damn copy slop ๐คฃ
really crazy how much it has changed
While everyone asks "which model scores highest?", a lot of AI money goes into inference chips in one month.
Enterprises don't care about your benchmark. 56% say latency is the #1 deployment barrier.Quality is converging. Here's the performance summary from Databricks KARL..
CLIs are super exciting precisely because they are a "legacy" technology, which means AI agents can natively and easily use them, combine them, interact with them via the entire terminal toolkit.
E.g ask your Claude/Codex agent to install this new Polymarket CLI and ask for any arbitrary dashboards or interfaces or logic. The agents will build it for you. Install the Github CLI too and you can ask them to navigate the repo, see issues, PRs, discussions, even the code itself.
Example: Claude built this terminal dashboard in ~3 minutes, of the highest volume polymarkets and the 24hr change. Or you can make it a web app or whatever you want. Even more powerful when you use it as a module of bigger pipelines.
If you have any kind of product or service think: can agents access and use them?
- are your legacy docs (for humans) at least exportable in markdown?
- have you written Skills for your product?
- can your product/service be usable via CLI? Or MCP?
- ...
It's 2026. Build. For. Agents.
Quick recap of what is happening across different layers of the Gen AI landscape. https://t.co/HVEsVfLw7w
--Software is in for major "disruption" driven by larger context window, reliable agents, text-to-action capabilities [Eric Schmidt at Stanford]
#EnterpriseAI#GenerativeAI
@adridder True. Ability to combine various models of choice is critical. It not only allows selection of what works for given task. More broadly, aligns with "Agentic AI" which is what we would like "GenAI" to become. Agentic AI is where the true value lies for enterprise tech.
Quick recap of what is happening across different layers of the Gen AI landscape. https://t.co/kqTACkwWcW
- Big emerging theme convergence of open models with closed ones
- Interesting discussion UI for AI from LangChain, etc. #EnterpriseAI#GenAI