
top saas vendors on Ramp (march 2026) Three clear themes: agents! vibecoding for nontechnical users. voice as an AI interface gaining clear transaction. I wrote about these software trends below.
Jared Short
5.3K posts

@ShortJared
🛠️ @stedi Prev: @Trek10Inc, @goserverless ☁️ AWS DevTools Hero. 🧔 he/him.

top saas vendors on Ramp (march 2026) Three clear themes: agents! vibecoding for nontechnical users. voice as an AI interface gaining clear transaction. I wrote about these software trends below.

We shipped the Stedi Agent – from first design doc to public announcement – in 13 days. At re:Invent, our founder @zackkanter got to sit down with AWS Director of Technology, Olawale Oladehin, to talk about how we built the agent and the design philosophy behind it. One key principle he shared: Quality doesn't mean slowing down. Instead, we ruthlessly cut scope to maintain high quality at speed. That focus lets us quickly ship simple – but powerful – features that our customers care about. Thanks to Amazon Web Services (AWS) for hosting and the invite. Link to the full recording below.

Announcing our $70M Series B co-led by @stripe and Addition, and with participation from @USV, @firstround, @BloombergBeta, @BoxGroup, @RibbitCapital, and other top investors. We also recently shipped two AI-native tools: Stedi Agent and MCP server. For more, check below. ⬇️

Pretty cool to see @stedi on this list after building for so many years.



Neat to see PromptQL go public! I've been playing with it for a little bit now and working with the team to give feedback. Being able to wire in disparate data sources and ask all sorts of questions and get answers has been very neat. Even questions about what questions to ask!


Hot take: AI Assistants are failing us Despite the buzz, closed-domain AI assistants are falling short. Without reliable, context-aware responses, they’re not ready for serious business use. Where AI Assistants Fail Here’s a scenario from a well known sales assistant that’s out there today: 📊 User Query: “What’s the length of my average sales cycle?” ➡️ Assistant Response: “I calculated the average sales cycle length for your opportunities, but there are no results to show.” The assistant can’t perform a computation. Why? Let’s break it down. 🛑 The Issue: Closed-domain AI assistants rely heavily on search-first RAG methods, making them unsuitable for high-trust applications. Consider a task like “Find all emails from last week that need follow-ups.” A search-based AI might skip important messages if they lack specific keywords, leaving critical follow-ups unnoticed. When this incomplete data is passed to the language model, the result is unreliable, making these assistants ill-suited for nuanced business queries. ✅ The Solution: Agentic query planning. Instead of rigid keyword search, assistants should gather all relevant emails and then use an LLM to classify follow-ups—just as a person would—ensuring accuracy. That’s why our AI lab built PromptQL - an agentic, data access API for your AI! Here’s a look at what we’ve been up to ⤵️





