Zack

cli / mcp @ ramp

[Zack @zack_field]

@krrishd Not bad

[Zack @zack_field]

@krrishd (Ofc it’s a sketchy streaming reseller)

[Zack @zack_field]

@krrishd brb securing https://t.co/DrxAdOv5MU

[Zack @zack_field]

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

Outcomes >>> tokens

[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 🙂

[Zack @zack_field]

@josephpalbanese @tryramp 🪙

[Zack @zack_field]

@sebgoddijn From 99.5% of Ramp using AI daily -> 99.5% of the world

[Zack @zack_field]

@vral spot on with outcome-based as the (only?) way to align incentives, other than having token spend be entirely orthogonal to revenue

[Zack @zack_field]

> Ramp, find me the best swag vendor and get my purchase order approved

[Teddy Riker @teddy_riker]

We just published the top use cases of our most AI-native customers who use our CLI and MCP to our website.

Every playbook contains a custom prompt tailored to whatever agent runtime you use: Claude, ChatGPT, Codex, and more.

Get started in one prompt👇

[Zack @zack_field]

@sanjayamirthraj @fliptexts @a16z @speedrun @notolegv @ajiang_xyz > hey flip, show me the money

[Zack @zack_field]

@andon_market @andonlabs let's get Luna a Ramp card

[Zack @zack_field]

Visited @andon_market today. Surreal to see a store entirely run by an AI agent, Luna.

[Zack @zack_field]

My mom was one of the 300K CPAs that left the profession, and the folks I know who studied accounting have all moved into new careers. This isn’t just a new AI product, we’re solving for a mismatch between supply and demand in the labor market.

Very different than the AI job replacement theory you usually hear about! Congrats @krishnanc_ and team!

[Eric Glyman @eglyman]

Introducing Stack.

The AI operating system that lets accounting firms take on more clients without hiring. Learns your firm's process, runs the close, posts the journals. Fully auditable.

We’re living through the biggest shift in accounting since the spreadsheet.

[Zack @zack_field]

through Big Model secondaries at least hundreds of thoughtful, AGI-fearing researchers/engineers are now post-economic. who is banding together to form a NewCo delivering on OAI's original mission of truly open machine intelligence?

SSI, nope. ThinkingMachines, nope.

[Zack @zack_field]

📈

[Juan Herrera @JuanHerr19]

@tryramp daily MCP/CLI adoption in the last few months.

A few things people are building with it:
- CFO dashboards, automatically refreshed
- accounting codes, missing receipts, memos on a schedule
- procurement workflow automation

[Zack @zack_field]

my job is now to find hills and then climb

[Zack @zack_field]

> unpack this chrome extension we're developing.

> That's not something I should do. -- Claude Code
> On it! -- Codex

didn't expect adherence/compliance to be a differentiator

[Zack @zack_field]

creativity*

[Zack @zack_field]

consistently impressed with creative of folks adopting the Ramp CLI / MCP

some usecases just this last week:
- building dashboards for finance leaders informed by spend / AP data
- automations to triage reimbursement requests daily
- daily spend briefs
- duplicate spend detection

[Teddy Riker @teddy_riker]

50+% of Ramp MCP and CLI users are building recurring reports to summarize things that need their attention on a given day

We now have a single tool that will aggregate:

- transactions, reimbursements, bills pending approval
- expenses missing receipts, memos, and accounting codes
- procurement tasks
- upcoming contract renewals
- payment runs
- vendor updates

and other Ramp homepage action items into one prioritized feed.

Just ask "show me Ramp tasks requiring my attention"

(note: if you are using Claude or ChatGPT, you will need to reauthorize the Ramp connector to get access)

[Zack @zack_field]

nice try

[Zack @zack_field]

nice. what are they going to do on week two of YC?

[Tyler Bosmeny @bosmeny]

A mic drop moment @ycombinator tonight

@sama just offered $2M in OpenAI tokens to EVERY YC startup in the current batch in exchange for equity

Just like Yuri Milner offering to invest in every startup back when Sam was a YC partner

I can't wait to see what's unlocked when you let the most driven, creative and formidable founders tokenmaxx