Shahab Mousavi

Working on AI applications to real-world problems | PhD @Stanford

[Abhishek Malani @abhishekm1636]

POV: you're in SF during a once-in-a-generation shift in technology. You just graduated, or you came out for the summer. AI billboards everywhere, models getting smarter every week, equal parts exciting and daunting. And somewhere this summer, you meet your future friends and cofounders.

We're bringing them together for a night in SF with @sequoia. You'll be in the room with some of the founders defining this moment too. July 30th. Invite only. DM me for an invite.

[Shahab Mousavi @ssmousav]

@NeelGuha @ColumbiaLaw Congratulations Neel!! 👏👏

[Shahab Mousavi @ssmousav]

@talaei_shayan Really cool work, great job @talaei_shayan & team! 👏

[Nnamdi Iregbulem @whoisnnamdi]

https://t.co/ENR1Wq0icE

[Shahab Mousavi @ssmousav]

@whoisnnamdi Very interesting, thanks for compiling the data and sharing in such a visually appealing way as always! 👏

[Shahab Mousavi @ssmousav]

@talaei_shayan @RicursiveAI @annadgoldie @Azaliamirh Nice, congrats Shayan!! 👏

[Aaron Levie @levie]

This is a critical post to read if you’re building an applied AI company right now.

“An application earns its place in the untrainable corner by doing unglamorous work: arranging a company's private reality so a model can act on it, handing the model the tools to act, working with the customer to change the reality of its workforce. A company that brings the translation is tough to copy – and the translation never ends. Integration and maintenance run as long as the relationship does, won by teams that put domain-specialized engineers and tools next to the customer.”

There’s still an insanely large gulf between model capabilities and what it takes to apply them to specific corporate workflows. Some of that is technology that needs to be built, a lot is access to (and formatting of) the right data to work with, and a ton more is on the change management and specific implementation work (FDEs, etc.) it takes to make AI work in any specific corporate setting.

2 things can be very true at once: frontier models and labs will continue to grow an incredible amount, and there will be a vast ecosystem of software and services companies that emerge to bring the power of these models to real enterprises. This makes room for new infrastructure provides, applied AI companies in every vertical, new versions of system integrators, and more players.

Incredibly exciting time on all fronts.

[Leo Mehr @LeoMehr]

Services are the future. Today we launched Ramp’s AI services motion.

It's easy to buy an AI subscription. It's hard to transform your company to actually run on agents.

Here’s our entire strategy.

1) Why now

Services are the new software (Sequoia)

Human labor TAM >> software license TAM. The market is bearish on seats and subscriptions.

Every enterprise AI company is doing this -- the labs have poured billions into services partnerships and their own deployment functions. Superintelligent models alone are not enough.

Palantir proved this is a strong business model: deeply embed engineers, build on top of a powerful platform, and customize extensively.

2) The real problem

Companies want AI. But the gap between "we have AI tools" and "agents run our workflows and we spend way less time" is enormous.

What we've found across over 50 companies we engaged with: agents start replacing real work when there is: complete data, read/write access across systems, agent-friendly policies. Most big companies struggle because:
- processes live in operators' heads
- dozens of disconnected systems (legacy ERPs, endless one-off excel sheets, etc.)
- archaic software with poor or no API access

Good data in the right place is a hard prereq to working agents.

Also, vibing in localhost ≠ a production system your enterprise can rely on. You still need hosting, ci/cd, observability, feedback loops, good interfaces. And taste to know what's even worth automating.

Everyone has a bulldozer, but most jobs just need a shovel pointed at the right spot.

What companies usually need is to be made agent-friendly. That's exactly what we do.

3) What we do

We focus on what Ramp does best -- finance.

And we embed FDEs that:
-> understand your problems
-> identify high-leverage, high-impact workflows that fit agents
-> scope the solution
-> connect your data
-> capture your context
-> deploy agents and often bespoke software for humans to collaborate with them
-> drive the business metrics that matter

Discovery and scoping are crucial. Building is easier than ever and thus judgement about what to build is more important than ever.

We're not a generic AI services arm, we're finance domain experts. Across the spectrum of financial operations, we help companies find and frame the problems worth automating -- similar to the taste a founder has in choosing which problems are worth solving (ex-founders make great FDEs).

Here’s the stack we deliver:

- Production infrastructure. Shipping an index.html from Claude isn't the same as creating a repo, hosting in a cloud service, ci/cd, testing, setting up evals, managing memories and skills, adding feedback loops, ensuring uptime, incident management, etc. Agents don't one-shot production systems yet. Production software is hard -- we build, host, and run it for you in a single-tenant, dedicated cloud environment. Most operators don’t have the time, knowledge, or experience to do this e2e. We help abstract the low-leverage plumbing so they can focus on the essential parts of their jobs.

- Data connectivity. Most enterprises have data lakes, but data is often incorrect, stale, or entirely missing. And write interfaces vary dramatically. Ideally we can use MCPs or CLIs, but usually it’s poorly documented APIs, SFTP, manual uploads, and email.

- A context layer. Things people have done for years aren't written down, so an agent can't do them until we capture that context -- ranging from simple policies to complex decisions. This usually involves creating policy documents, shared agent memories, and skills.

- Evals and feedback loops. How you know an agent is doing a good job, and how it improves over time.

4) Why Ramp AI Solutions

We focus on finance because it’s the vertical we know deeply, have structural advantages, and are most differentiated:

- Data. 70k+ customers use our core product, over $200B in annual payments, years of vendor data, millions of transactions and bills monthly.

- Money-movement primitives and partnerships. Global money movement rails, partnerships with banks, Visa, Stripe, etc. You don’t want to vibecode international wires for bill payments.

- An intelligence layer on top: fraud detection from hundreds of millions of expenses, PO-to-invoice matching, state-of-the-art OCR, and fine-tuned models for accounting coding, spend routing, policy review, etc.

Unlike the labs, we’re not incentivized to sell tokens.

Ramp is an AI fiduciary and an impartial broker to deliver AI that is:
- model-agnostic -- we benchmark all the leading models (labs, open source) and fit the right one to each task
- and token-efficient by design

Our main incentive is business outcomes -- which is Ramp’s mission, to save our customers time and money.

I’m extremely bullish about our motion, and the broad industry growth of AI-native services.

If you're a finance leader trying to be more agent-native,

If you’re interested in joining our FDE team,

I’d love to talk 🙂

[Brian Halligan @bhalligan]

Sasan, the CEO of Intuit grew their market cap from $50billion to $180billion.  Learnings on:
1. How to scale a 2nd channel w partners (90% of rev's) 2. Scaling the sh-t out of SMB
3. The downside of analytics in product management
4. My favorite CEO question
5. How to keep the coal face on the customer as you scale.
6. Why shadowing is better than mentoring
7. A case study in 2nd acts -- app to platform
8. Sasan's #1 hiring criteria
9. What non-founder scaleup CEOs have in common.

If you want the 3 minute tl;dr, it is 43minutes in.

[Shahab Mousavi @ssmousav]

@abidlabs @thinkymachines @TrackioApp +1

[Shahab Mousavi @ssmousav]

@LiyuanLucas @MSFTResearch @thinkymachines Congratulations 👏🎉

[Shahab Mousavi @ssmousav]

Great talk by @JeffDean at @Stanford last week, highly recommend checking it out for those interested in staying up to date with AI trends -- many thanks to the @stanfordaiclub for organizing it and making it publicly available beyond Stanford too! 👏

[Stanford AI Club @stanfordaiclub]

Checkout @JeffDean's (Chief Scientist, Google DeepMind) talk on Important AI Trends (11/20). Thanks Jeff for an insightful talk!

Posted on our Youtube:
https://t.co/UmfJCdK1Ie

[Shahab Mousavi @ssmousav]

@adambain @micro1_ai 💯

[Shahab Mousavi @ssmousav]

Amazing work thus far & exciting times ahead for micro1!! 👏🥳🤩
Proud of you @aliniikk 🔥

[Ali Ansari @aliansarinik]

Today I’m excited to introduce micro1 Intelligence, the world’s most advanced platform for training frontier AI models.

Achieving AGI is bottlenecked by one main thing: high-quality data.

Data based on real-world environments that capture human expert workflows, complex decision-making, and reward signals models need to learn.

With micro1 Intelligence, frontier labs can train on RL environments across every subject matter all in one place.

[Shahab Mousavi @ssmousav]

@aliniikk Amazing work thus far from the team & exciting times ahead for @micro1_ai!! 👏🥳🤩

[Shahab Mousavi @ssmousav]

Proud of you @aliniikk and the whole @micro1_ai team 👏🎉

[Ali Ansari @aliansarinik]

I’m excited to announce micro1 has raised a $35M Series A, valuing us at $500M. This round was led by 01A with @adambain joining our board of directors.

We’re grateful to be partnering with leading AI Labs & fortune 10s, such as Microsoft, to train frontier LLMs.

We’re just getting started building the infrastructure layer for AGI, with the ultimate goal of answering the very fundamental question: “where should humanity spend its time?”

[Shahab Mousavi @ssmousav]

@aliniikk @adambain Awesome news!! 🤩
Can't say I'm surprised though, very well-deserved 👏🙌

[Shahab Mousavi @ssmousav]

@joshpxyne @khoslaventures @natfriedman Cool tweet & awesome product -- What more could one ask for? :)
Congrats @joshpxyne & the @coframe team! 🎊👏
Onward & Upward 😎

[Shahab Mousavi @ssmousav]

@lateinteraction Congratulations, well-deserved indeed 👏
Looking forward to hearing of all the great work you & your lab will be doing at @MITEECS

[Shahab Mousavi @ssmousav]

It was a pleasure to collaborate on research with you @thisisOlamide  -- To many more! :)

[Olamide O., Ph.D. @thisisOlamide]

Had a fantastic time at the @RealAAAI Fall Symposium Series! 🚀 Learned about amazing advancements and presented our work on AI for sustainability. Big thanks to @Stanford for this opportunity. #AAAI #Sustainability #AI