Yann Ranchere

Founder @usemotley / Venture Partner @anthemis : board @Qover

[Yann Ranchere @tek_fin]

Back in the builder seat. I have started @useMotley with my cofounders Egor (ex head of AI at Wise) and Artem. https://t.co/IDati1Iqi3. Lots of discussions around systems of records. We are building the best way to interface with those, starting from a reporting automation.

[Yann Ranchere @tek_fin]

T

[Yann Ranchere @tek_fin]

Assistant agent will need to connect to their customers internal databases to help them manage their workflows. Build a framework for each so that they understand it. Semantic layers will play a critical role. We are building SLayer for this lightweight, embeddable > https://t.co/hYb1xp9iRI

[Yann Ranchere @tek_fin]

@LexSokolin @gdibner That phase will happen (if it should) in the next 5 years. Also will be silent first as new premium dominate. The magic of insurance. Also the structure is interesting. How much of the risk the customers carry themselves is an interesting question .

[Armin Ronacher ⇌ @mitsuhiko]

This is such a good post. https://t.co/IdmAnh18Nt

[Kyle 🚄 @KyleTrainEmoji]

PICARD: Data, shields up

DATA: Brilliant! Shields can reduce damage we sustain. Not immunity. Not hubris. Just prudence. It's not precaution—it's strategy.

[camera shakes]

WORF: HULL BREACHES ON NINE DECKS

DATA: Here's what happened: you told me to raise shields, and I didn't

[Greg Brockman @gdb]

bring-your-own MCP servers:

[Yann Ranchere @tek_fin]

"If something takes less time for you to create than for the recipient to consume, it’s probably slop"

I love that as a guiding principle

[Max Brodeur-Urbas @MaxBrodeurUrbas]

https://t.co/Bvx9PUgWgq

[Max Brodeur-Urbas @MaxBrodeurUrbas]

https://t.co/Bvx9PUgWgq

[Yann Ranchere @tek_fin]

Really interesting benchmark from the @RogoAI team. That models of the same generation are fairly similar in capabilities is what we intuitively feel, but I was surprised by how much the spikes differ.

The key point to note. These were running under a fairly basic harness. I think that's where the biggest improvement lies: better harness and better tooling.

Watch this space for data analysis cc @EgorKraev

[Rogo @RogoAI]

Which AI model is best for the financial work our customers do? We built the Big Finance Bench to find out.

928 questions written by ex-finance practitioners, scored against more than 15,000 rubric criteria, used to rigorously analyze ten frontier models across the workflows that run inside banks, PE firms, and asset managers. The first benchmark of its kind for finance.

The findings surprised us. Read more on our blog.

[Yann Ranchere @tek_fin]

@DoDataThings @ttunguz That’s a very interesting problem. Our approach is that there should be levels of trust. User tagged, team level tagged, organization tagged. This also gives another tool for agents to work on ie mining user level metrics to suggest team level promotions.

[Yann Ranchere @tek_fin]

This is why you want your semantic layer to be headless, open source and independent from your BI tools

[The Information @theinformation]

Microsoft blocked a Databricks feature that helped Power BI customers connect data more easily, escalating a fight over who controls the infrastructure behind AI agents.

The clash shows how semantic layers are becoming one of the most strategic battlegrounds in enterprise software.

https://t.co/M9gqXbx4c6

[Yann Ranchere @tek_fin]

@DoDataThings @ttunguz Agreed. This is where semantic layers are interesting because vs in an BI world, with agents they are much less static over time and agents should be able to write and manipulate it.

[Yann Ranchere @tek_fin]

Use @useMotley in Manus via our MCP server. Instantly built semantic layer on top of your database, letting your agent ask any data question with full transparency and specific tooling for reporting.

[Manus @ManusAI]

New: Projects are now available on mobile.

We’ve updated the experience so you can organize project-based work wherever you are, from simple task management to more advanced workflows that rely on shared files, instructions, skills, and connectors.

[Greg Brockman @gdb]

the model alone is no longer the product

[Yann Ranchere @tek_fin]

Yes! Finally we are almost there for being able distribute plugins to Claude Cowork / OpenAI Codex and Google Spark

[Google Gemini @GeminiApp]

Gemini Spark is your new 24/7 personal AI agent.

Give it a task and it works autonomously in the background, even if your phone and laptop are turned off. You choose to turn it on and it's designed to check with you before taking major actions. #GoogleIO

[Yann Ranchere @tek_fin]

@tylermacro10 The caviar of potatoes

[Yann Ranchere @tek_fin]

Tooling and training. Building the right infra for data and reporting agents can really improve this (hence @useMotley ) but also training people to iterate and validate ie think like a data scientist.

[Lenny Rachitsky @lennysan]

Not enough people are talking about how much AI is impacting the role of data science.

I was chatting with a DS friend, and he said that most of his team's work now is reviewing half-assed AI data analysis from PMs and engineers. And that 50% of the time, that analysis is wrong.

The role is becoming less fun.

[Yann Ranchere @tek_fin]

Yay for Workers. Time to hook up SLayer to it https://t.co/4wiXhVUv4R

[Notion @NotionHQ]

BIG one for devs today. Introducing the Notion Developer Platform:

- Notion CLI, ntn (Notion in your terminal)
- Workers (run code on Notion's infra)
- Database sync (any data source into Notion)
- Agent tools (build any workflow)
- Webhook triggers (trigger Notion from any app)
- External Agents API (bring any agent into Notion)
- Notion Agents SDK (use Notion Agents anywhere)
- …and a bunch more API improvements

And soon, you won't need to be a developer to build on Notion. Your agent will be one for you.

[Yann Ranchere @tek_fin]

@GammaApp Shoutout to @GraphyHQ for their SDK integration with @GammaApp

[Yann Ranchere @tek_fin]

.@GammaApp is almost there to replace ppt + thinkcell. We are deploying @useMotley with a customer and replacing a - manual database extract + transform to in excel + update with thinkcell + write content manually - with - prompt Claude Cowork + Motley MCP + Gamma MCP - . 100 data driven one shotted from a database.

[Yann Ranchere @tek_fin]

@GammaApp a few improvements we would like to see :
- annotations parameters kept in templates
- manually set average lines
- solving some odd font size discrepancies
- an easy way to set the complexity level of slides (in terms of number of components)