Fan de @cliengo y @Leadaki, más en https://xitter.cf/t.co/f8u0Fjs1Qw, y como les dije arriba no soy @rusosnith
Buenos Aires, Argentina
Joined October 2006
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Andres Martin Snitcofsky (No soy @rusosnith) retweeted
AI agents at Kavak sell the cars, underwrite the loans, coach the mechanics, and in one Mexican city, run the entire operation.
The Latin American used-car marketplace bet on agents three years ago. Today ~95% of interactions and transactions run end-to-end on AI: NPS tripled, sales conversion doubled, warranties down 26%, car loans approved in less than three minutes.
CPO & AI Officer Alejandro Maza joins a16z's Angela Strange and Gabriel Vasquez on how they pulled it off, why adoption without redesign fails, and why they deleted two years of working architecture to start over.
00:00 Intro
01:03 ML before transformers
02:23 Kavak's agent-per-customer architecture
04:59 Three bets: redesign the company, build superhuman agents, change the metrics
10:49 Agents with 2.1x conversion
14:23 Car loans approved in minutes
16:13 1.5x profits in a real city in six weeks
20:13 "Jedi Academy": training mechanics to ship agents
28:44 Destroying two years of work
32:52 Ford's factory: why adoption isn't enough
34:45 Advice for founders
@alehandromz @astrange @GEVS94
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
Catching skin cancer early is a home robotics problem.
Melanoma is highly treatable when detected early, yet today’s screening process depends heavily on patients noticing tiny changes across their entire skin surface. This requires patients to solve a near-impossible visual-memory and registration problem.
I built OpenDerm, an open-source 4-DOF robot that captures high-resolution images of the skin and uses them to reconstruct and track the skin surface in 3D over time.
The best way to make skin screening truly routine is to bring it into the home. OpenDerm shows that inexpensive robotic skin imaging is possible, but the path to scale is not a dedicated screening robot in every household—it is to make skin screening one of the many useful things a general-purpose home robot can do.
Read more about why I built OpenDerm and how it works here:
Blog: marionlepert.github.io/blog/…
Project: openderm.github.io/
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
Today we're releasing a new set of components for building chat interfaces.
We've taken the patterns we build every day, rethought the abstractions behind them, and turned them into components you can compose and customize.
We're starting with the conversation layer: streaming, scrolling, messages, bubbles, attachments, and markers.
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
As engineering, product, design, DS, etc. melt into a new kind of role, I was reflecting on what roles might look like in the future. For example, when I look at the Claude Code team I see what I think is five archetypes:
1. Prototyper: comes up with brand new ideas; churns out many ideas, most of which don't ship
2. Builder: quickly turns a prototype/idea into production-grade product/infra
3. Sweeper: cleans up the UI, simplifies the code and system, unships, optimizes performance
4. Grower: takes a product that has been built and iterates on it to improve Product-Market Fit
5. Maintainer: owns a mature system to make it secure, reliable, fast, and efficient as it scales
Many people span across 2 roles, and sometimes 3 roles. I also notice that these roles are not really tied to job function -- eg. across Anthropic, some designers match category 1, some 2, some 3; same for engineers, PM, DS.
A healthy team needs a mix of these, depending on the product:
- A product that is new and pre-PMF needs people that are strong at 1+2+3
- A product that is growing and has found PMF needs 2+3+4 and some 5
- A product that has strong PMF needs 3+4+5 and some 2
Maybe product roles of the future will look more like this, and less like the domain-specific roles of today?
Que linda empresa @midjourney
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
Announcing a new division of Midjourney called "Midjourney Medical"
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
Claude Fable's PR is through the roof. You can thank the commerce department for boosting its status to stratospheric levels. Even better, Anthropic didn't have to rent compute!!
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
Today we’re introducing Google AI Threat Defense - a comprehensive AI-powered cybersecurity solution designed to help continuously monitor for and stop AI-powered threats before they can impact your business. Here’s how it works:
1. AI Threat Defense uses our cybersecurity platform @wiz_io to scan and prioritize what applications and systems have the highest security risk.
2. Gemini and other frontier AI models can then autonomously perform continual deep scanning of your applications - starting with those at the highest risk - to identify security vulnerabilities.
3. The capabilities of CodeMender - a new software repair agent - are then used to verify and accelerate the patching of vulnerabilities.
4. And our @wiz_io autonomous agents continuously test your systems to find unknown vulnerabilities before adversaries do so that you can remediate them before you are attacked.
While other model providers focus on using AI to find and flag vulnerabilities, Google AI Threat Defense actively prioritizes your most critical real-world risks and accelerates their remediation using a variety of models since no single model finds a superset of the vulnerabilities found by all other models.
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
I think the article strangely excludes the link to the repo? sorry if i missed it, but anyway here it is: github.com/google/ax
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
I’ve always believed the No.1 application of AI should be to improve human health.
That work started with AlphaFold, and now at @IsomorphicLabs with the mission to reimagine drug discovery and one day solve all disease!
We are turbocharging that goal with $2.1B in new funding.
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
The future of Math is mathematicians and AI agents working together.
Very pleased to introduce @GoogleDeepMind's AI co-mathematician: a multi-agent system designed to actively collaborate with human experts on open-ended research mathematics.
Mathematicians testing the agent across areas as diverse as group theory, Hamiltonian systems, and algebraic combinatorics have reported impressive results.
In autonomous mode evaluation on the rigorous FrontierMath Tier 4 problems, AI co-mathematician scored an unprecedented 48% — a new high score among all AI systems evaluated.
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
Yesterday Fitbit Air launched, but did you know it comes with a new @googlehealth API? You can build AI agents, MCP servers, or CLIs on top of your sleep and heat data.
- 31 different data points from exercise to sleep, heart rate, or SpO2.
- Webhooks push real-time notifications when health data changes.
- Support Read or write data, request only the permissions you need.
- Query by time range, roll up daily summaries, or paginate results.
I am whoop guy, but might be good reason to explore this. Full getting started codelab below.👇🏻
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
Testing LLM safety shouldn't bottleneck your CI/CD. 🚦 Today we're releasing AMS, an open source tool that verifies open-weight model safety in just 10-40s. A big step for a safer AI ecosystem! Will you integrate this into your workflow? 🛠️ goo.gle/ams-activation
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
My favorite part: instead of a dashboard it just updates the README as it works.
Readme is the new dashboard.
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
BIG NEWS! @Amazon, @Meta, @Microsoft, @Salesforce, and @Stripe are joining forces with us (@Shopify, @Google, and other founding members) to truly make UCP the single, universal protocol for commerce in the agentic era. 🎉🚀
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
If you read this and don’t understand why it’s happening it’s an opportunity to reset your understanding of how the real world works.
The real world will need a ton of help actually getting agents going in the enterprise. Companies have legacy tech stacks they need to modernize, data in tons of fragmented tools, knowledge that isn’t captured or digitized, and change management needed to actually utilize agents effectively. And they have to do all this while still running their business day-to-day, unlike startups.
This is why there is so much opportunity for companies (software or services) to actually deploy agents in specific domains and workflows. This remains a big opportunity for both existing services providers but also tons of new startups as well. Every new technology wave produces a new era of consulting firms that can deliver on that technology.
It’s also why the FDE model is going to be alive and well for a long time because companies will want to have their vendor actually help drive the change management and implementation for their new workflows.
The people aren’t going away. Far from it.
Andres Martin Snitcofsky (No soy @rusosnith) retweeted
A CEO from one of our portfolio companies shared this with their team. I’m re-sharing it with their permission, because it resonated and reflects what all founders and CEOs should be communicating.
--
We are living through a period of compounding change. And in moments like this, the biggest risk is no longer making the wrong decision. It is moving too slowly while the world moves around you.
There are two paths. We can play defense:
- Protect what we have
- Optimize what works
- Wait for clarity
It feels safe. It isn’t.
Or we can play offense:
- Learn faster than the environment changes
- Use new tools to solve old problems in better ways
- And create entirely new strategies and businesses
That’s where the opportunity is.
Challenge yourself to do things faster and better than you have ever attempted. Stay uncomfortable. Stay on the front foot.