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Simplifying finance to help every business in the world become more productive.
Articles by Eric
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Introducing Paribus 2.0 for iOS
Introducing Paribus 2.0 for iOS
Introducing a stunning new interface optimized for iOS 9, including 3D Touch, Apple Pay, native sharing, and more…
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The double whammy of being poor — making less and getting charged more
The double whammy of being poor — making less and getting charged more
Mr. Robot has kicked off a huge discussion in the tech community about the wealth divide.
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A Startup Responds to The Economist
A Startup Responds to The Economist
Last month, The Economist published a column [1] which alleged that store "guarantees to match competitors' prices"…
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37K followers
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Eric Glyman shared this7 years ago, we built Ramp to save businesses time and money. But we won't build the future of finance by looking backwards. That's why we're thrilled to announce Rampwards. A gamified points system that goes against everything we stand for. Time is money. Waste both on points. Now available to our 50,000+ customers, who were all automatically opted in this morning. Enjoy.
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Eric Glyman shared thisWe only hire builders (and we’re on a hiring spree)! Reply with something you've built. I'll read them personally. We’re interviewing the best ones. You’ll be a good fit if you: - work best without permission - default to “how could I automate this” - had weird teenage hobbies - spend your sunday making side projects - have more Claude agents than cousins - shipped something this week - make prototypes, not powerpoints - don’t like hierarchy - are good at games: chess, monopoly, poker - would take dinner with Elon over $100k Good luck, Eric
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Eric Glyman shared thisThere is a person at every company holding the chaos together. They book flights for candidates, hotels for customers, cars for contractors. They field the "can you also add a leg to Denver" text at 10pm. They are operationally gifted, deeply relied on, and running everything on a spreadsheet and goodwill. That person deserves far better tools. That's why all of us at Ramp are so excited today. Devon Tivona, Sam Felsenthal, and Kate Porter started Juno 18 months ago because they knew this problem cold — they'd built Pana, sold it, watched what didn't get finished, and came back to work even harder. That kind of conviction comes from genuine care for the customer and a refusal to accept that this is just how it has to be. What they built in 18 months is exceptional. Some of the largest companies in the world are using it. Customers love it. The team executes with focus and craftsmanship. Joining Ramp means one thing for Juno's customers: more. More engineering. More integrations. More resources to go deeper on the larger mission and solving the complexity that makes guest travel actually hard. We succeed when our customers save time and money. Devon, Sam, Kate, and the Juno team wake up every day with that same orientation. Grateful to be working together with the Juno team, we're committed to delivering for our customers. For more, see Karim's note below and coverage by Business Travel News: https://lnkd.in/eBsy8fie
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Eric Glyman shared thisIf you’re running a business in Europe or the UK, we bring good news from across the Atlantic. Ramp launches locally this summer. We’re setting up shop and the waitlist is open. The median Ramp customer saves 5% and grows revenue 16% in their first year. Europe’s most ambitious companies deserve the same. If you're interested, click here so you're first on our list to support: https:// ramp.com/europe-waitlist Grateful to Emily Mason and the Bloomberg News team for their detailed coverage: https://lnkd.in/e4SMbmdS. Looking forward to joining Edward Ludlow at 11:20a ET to discuss more live!
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Eric Glyman shared thisMost finance teams didn’t choose their workflows — they inherited them. Expense reports. Manual categorization. Month-end scramble. Reconciliation after the fact. Software digitized these processes, but it didn’t fundamentally change them. Humans still do most of the operational work. AI changes the constraint. For the first time, software can reliably do large parts of finance operations itself — capturing context, applying policy, coding transactions, and improving decisions continuously. Finance shifts from retrospective reporting toward systems that run alongside the business in real time. We’ve started calling this idea “zero-touch finance.” I recently spoke with McKinsey & Company about what that means in practice, what we’ve learned building Ramp, and why we think the role of finance teams is about to change meaningfully over the next decade. I’m grateful to Maurice Obeid for leading a fantastic and wide ranging conversation. If you’re curious where operational finance is heading, I hope you enjoy the conversation. https://lnkd.in/eZApi4vM
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Eric Glyman shared thisThere are two non-negotiables in accounting: the books must be correct, and they must be ready on time. For decades, companies have satisfied those constraints through an extraordinary amount of manual effort. Highly trained professionals code transactions, re-approve familiar expenses, reconcile mismatches after the fact, and compress all of it into the ritual of month-end close. It works. But it is fundamentally retrospective. Today, Ramp introduced an Accounting Agent designed around a different premise: what if bookkeeping happened as the business operated, rather than after it? The agent captures, codes, reviews, validates, accrues, and reconciles spend continuously. It learns directly from the people who understand the nuances best, the accounting team itself, and applies that context in real time. At Perplexity, where velocity is core to the company’s identity, this allowed their team to stop choosing between speed and accuracy. The majority of transactions are now coded automatically and audit-ready, enabling close to start on day one instead of day thirty. What’s been most striking is how the system learns the subtle, company-specific logic that historically lived only in human judgment. As Jim Romano, CFO at Stateside Brands, described it, the agent is already identifying patterns like when spend belongs in samples rather than travel and entertainment — the kinds of decisions that typically require institutional memory. As he put it, the goal is simple: finance teams should focus on exceptions, not the easy stuff. We’re also seeing the second-order effects emerge quickly. Teams report spending dramatically less time reviewing transactions and substantially more time on planning, analysis, and growth. As one CFO told us, “What used to take hours of manual review now happens. I’m spending nearly all of my time thinking about where the business should go, not retracing where it’s already been.” There is a broader shift underway in accounting. The central question is moving from “what parts of close can be automated?” to “should close even be an event at all?” One belief that guides our work at Ramp is that information latency inside companies is an invisible tax. When financial truth lags behind operational reality, organizations make slower and often worse decisions. As transaction data becomes inherently digital and systems become capable of learning institutional context, continuous close stops being aspirational and starts becoming inevitable. One thing that surprised us while building this: accounting isn’t constrained by a lack of rules — it’s constrained by how many of those rules are unwritten. Seeing software begin to absorb and apply that tacit knowledge has been a clear signal that accounting is entering a new phase. Accounting has always been the record for business reality. Our goal is to help it become closer to real-time truth. Proud of the team, and grateful to the customers building this alongside us.
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Eric Glyman shared thisYou thought the box stunt with Brian was nuts? Wait till you see this one.
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Eric Glyman shared thisMeet Brian. Brian’s been carrying accounting on his back for a long time. Super Bowl Sunday, he finally gets backup.
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Eric Glyman shared thisLooking back at 2025, our focus at Ramp was simple: automate the tedious parts of finance. Grateful to serve 1.25M+ people daily across 50,000+ businesses. Thanks for doing finance ™ with us. Still early.
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Eric Glyman liked thisEric Glyman liked thisI'm excited to share that Pontus Abrahamsson and Viktor Hofte, the co-founders of Midday are joining Ramp They are builders through and through, and share the conviction that financial software should be technically serious and genuinely delightful. A minute someone spends on Ramp is a minute they're not doing their actual work. The best tool disappears into how you run your business. Midday is a beautifully designed, AI-native, open-source business management platform serving a community of operators and builders who chose it for the same reason our customers choose Ramp: it lets them run their finances with minimal effort. I wrote about it on our blog. https://lnkd.in/e5VUeNwp
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Eric Glyman liked thisEric Glyman liked thisIntroducing: TaxBench. We tested 16 frontier AI models on real tax work. None of them can reliably do the job yet. We're Rivet, an AI-enabled accounting firm filing returns for Cursor, Cognition, and hundreds more. Today we're publishing TaxBench, a reliability-first benchmark built from the actual questions our clients ask us every day. Methodology: every model scored on pass@1 (right on the first try) and pass^5 (right five times in a row), across three categories: Tax Knowledge, Tax Calculations, and Data Retrieval. Pass^5 matters more, because clients don't give you five chances. They don't know you're wrong until correction notices arrive from the IRS. The headline result: top pass@1 scores of 84.2% / 77.2% / 74.5% collapse to 42.3% / 27.5% / 22.9% on pass^5. No model clears 50% on pass^5 anywhere. Why a 50% bar matters: every engagement is a chain of judgment calls. Ten calls per client at 99% accuracy is a ~10% chance of error per return. 50% is useless. 75% is unusable. Even 99% isn't good enough. "Almost always right" is just another way of saying "wrong often enough to get fired." A frontier model isn't a tax practice. You can't hand an accountant a Claude subscription and expect returns to ship. The model is one layer. The rest of the stack – accountants who know where models fail, a platform that captures every workflow as structured data, a benchmark that tells us when an agent is ready to take a step unsupervised — is what turns capability into a working firm. Models are commodities. We'll run whichever frontier release is best each month. What isn't commodity is the stack around them. Full writeup and leaderboard in the comments.
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Eric Glyman liked thisEric Glyman liked thisAt Ramp, AI usage is no longer a side experiment. 99.5% of employees are now using AI tools, and for many, it has become the default way work gets done. Tasks that once took hours are being compressed dramatically, with teams finding ways to automate, iterate, and move faster across functions. One example: a complex underwriting process that previously required hours of manual work was reduced to under an hour after someone mapped the workflow and automated it. Eric Glyman also highlighted why Ramp invested in building internal tools. The models are powerful, but context matters just as much. Connecting tools to internal systems, data, and workflows makes them far more useful from day one, especially for new team members. *For educational purposes for company founders and executives. This is not investment advice or an offer to invest. Refer to Outreach Disclaimer link in profile.
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Eric Glyman liked thisEric Glyman liked thisToday is a huge milestone for Atlar! Atlar is the first platform globally to use J.P. Morgan Payments’ new API, connecting AI agents to real-time banking data. It’s fitting that Lovable, one of the most recognized AI companies in the world, is the first joint customer to take it live. J.P. Morgan choosing Atlar as their launch partner reflects how far we've come: the leading AI agents in treasury, and the trust we've built across the ecosystem. It also reflects how much the data and connectivity layer matters in the age of AI. Slow, patchy data wasn't a major concern when finance ran on overnight cycles with manual logins and Excel, and accounting processes spanned days if not weeks. But poor bank connectivity doesn’t cut it for agents -- to reach their full potential they need access to the right context in real time. That’s what this partnership unlocks: joint customers can be live on Atlar in seconds, no IT work required, with the data quality that humans and agents need to do real work. Lovable is the kind of customer we're building Atlar for. At the bleeding edge of AI, they're operating the way most finance and treasury teams will be in 12 months. With the speed that Matias Salonen and team move at, manual treasury work isn’t an option. We’ve long believed that for AI in finance, the bottleneck isn’t the model; it’s the data and tools underneath. The more capable AI gets, the more that’s true. Lisa Davis, Santiago Alcaraz Sanchez, and the wider J.P. Morgan Payments team -- thanks for trusting Atlar with this. We can’t wait to see many more joint customers take this live. Read our joint press release: https://lnkd.in/dFWGKnPn
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Eric Glyman liked thisEric Glyman liked thisBusiness purchasing is broken. Today we're fixing that. We're giving every Ramp customer access to AI agents that can source vendors, review contracts, run approvals, negotiate pricing, check compliance, and handle payments and renewals. This is more important than ever when AI adoption has crossed 50% of US businesses and the average AI contract has gone from $39K to over half a million in two years. The complexity outgrew the process. Here’s what we built: 1. AI-powered vendor sourcing — describe what you need in one sentence, Ramp researches options, generates the RFx, scores responses 2. Conversational intake - employees tell Ramp what they want to buy and the agent pre-fills everything, routing it to the right team 3. Workflow engine rebuilt from scratch - parallel approvals, vendor onboarding, AI-triggered compliance checks, bidirectional integrations with CLM/TPRM/ticketing tools 4. Automated compliance reviews - security, legal, and financial assessments run before the request hits an approver, with full citations attached 5. Negotiation playbook - pricing benchmarks, renewal flags, and renegotiation recommendations surfaced automatically 6. PO visibility and reporting - open to closed, budget tracking, and custom reports generated by asking Ramp in plain language 7. Vendor management and renewals - single view of all your vendors, usage, satisfaction, duplication, and upcoming renewals pre-vetted and negotiated. Early results: customers saving 16% annually on vendor spend. 46 hours per month of manual purchasing work eliminated. Approved requests moving 3x faster. This one has been a long time coming. Excited to say that the new era of Ramp Procurement is now available to over 50,000 teams.
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Eric Glyman liked thisEric Glyman liked thisOn my first day at Ramp, I walked to work and was amazed to see the office was located above a huge Home Depot in the middle of Flatiron. Almost everyone in NYC knows that Home Depot. And two years later, many of them now know Ramp as well. The company has gotten bigger, the work has evolved, but many of the core principles from the startup days remain. Grateful to work somewhere that values velocity and ownership. As I celebrate 2 years at Ramp, I’m also excited to share that I’ve been promoted to Lead Technical Product Marketing Manager. Thanks to the many amazing people, teams, and leadership I get to work alongside every day. Lots more to do.
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Eric Glyman liked thisEric Glyman liked thisMy boi Will Koh top of the page! 🥲 beefy, smart model. Go try it! ps. gotta wait if you are a dev and want to try for real >For API developers, gpt-5.5 will soon be available in the Responses and Chat Completions https://lnkd.in/gx9BuDRq
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Eric Glyman reacted on thisEric Glyman reacted on thisThanks Ramp, Jake Farmakis, and Justin Harrod for the opportunity to attend the Masters! It was an unbelievable experience. We’re hitting our 1 year anniversary on Ramp and we’re thrilled with the results. 900 cards and customized workflows. Improved compliance, best in class user experience, and a policy AI agent that works while we sleep!
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Eric Glyman liked thisEric Glyman liked thisOur accounting team is shipping faster than some product teams right now. Floortje de Rouw was one of the first Merge team members to get AI-pilled early last year, and has been enthusiastically building AI agents for our accounting team. Just a few examples: Month-end close - Standardizing and streamlining close tasks - Preparing working papers and reconciliations - Running MoM and YoY analytics and flagging anomalies AR collections - Weekly summaries with customer context, actions taken, and recommended next steps - Cash application agent that matches incoming payments to open invoices and flags exceptions AP - Slack-native spend bot that: ---- Calculates spend limits based on request inputs and policy ---- Routes approvals to the right people ---- Provisions virtual cards in Ramp (pictured below)
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Education
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Harvard University
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Activities and Societies: Harvard College Global China Connection, Global China Connection, Massachusetts Small Claims Advisory Service, Harvard College in Asia Program, Veritas Financial Group, Harvard Financial Analysts Club
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Jason Shuman
I’ve spoken to over 2 dozen MDs at PE firms I can confidently say that the arb of figuring out how to implement Vertical AI at portfolio companies is very real right now It will fundamentally change underwriting for those who can do it predictably and unlock generational returns. Most are aware they need to act. Very few have.
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JT Benton
Hot take: lot's of #LP's are growing underwhelmed with traditional venture investing. 💰 Fees are high given the level of engagement with the company operators. ❓ Access is opaque - LP's are unclear on the portco operations and outcomes. Outcomes are scattered - power law investing can certainly work, but many feel that venture capital investing is just a numbers game. There's another way. I'm biased, but I think it's better: #VentureStudios as an asset class. They blend: 🤜 🤛 Control and ownership 💡 Thematic focus 👬 Partnership with operators Studios offer a fund-like structure — but with more alignment, higher value conversion and less noise. If you're interested in understanding more about the studio model, we have resources to share. Please reach out and let's connect!
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JT Benton
Here's a problem we see all the time in early studios: they copy-paste a VC fund's operating cadence and wonder why nothing feels right. Weekly deal flow reviews. Portfolio monitoring calls. Valuation-focused LP reports. All borrowed wholesale from a fund playbook. But a VC fund's primary activity is deal selection -- source, evaluate, check, board, wait. A studio's primary activity is venture creation -- generate, validate, recruit, build, launch. Those are fundamentally different jobs. When you run a studio like a fund, things break in specific ways: Your meetings are wrong. You're reviewing deal flow instead of venture build progress -- milestones, blockers, resource allocation. The work is building, not sourcing. Your team is wrong. Studios need builders at every level -- operators, designers, engineers. Not just investment professionals. You can't build companies with a team designed to pick them. 📉 Your metrics are wrong. Entry valuations and markups don't tell you anything useful. Cost-to-build-a-venture, time-to-market, and venture survival at 18 months -- those are the numbers that actually measure whether the studio is working. Your LP reporting is wrong. Report operational progress -- what's building, what's launching, what's been killed and why. Not just portfolio movements. Here's the lesson -- the studios that struggle most are the ones that adopted VC templates without modifying them for fundamentally different work. The portfolio companies don't exist until the studio creates them. Not a fund that happens to build things. A builder that happens to have a fund. The operating rhythm should reflect which one is primary. 🎯
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Arteen Arabshahi
SF VC Takeaway #2: Pricing expectations, performance bars, and what’s actually getting funded. One theme that came up repeatedly in SF was how far pricing expectations and performance bars have shifted, even compared to just a few years ago. A few things investors kept anchoring to: 1️⃣ Median Series A valuations are higher than their 2021 peaks, but fewer of them are getting done. 2️⃣ Capital is being concentrated into fewer and fewer companies (and lots of capital!) 3️⃣ “Good” progress is no longer enough and the bar for standout performance has moved in an AI-native world So what does “top performance” mean right now? One investor told me that top quartile seed companies in their portfolio are going from $0 to $2M in ARR in <12 months. Outside of pure traction numbers, a few other themes that came up to describe "top performance": 📈 Explosive early revenue ramps (or a very credible path to them) 📊 Strong velocity and momentum for 2 quarters in a row, even if the baseline is small. 🚀 Clear signals of category leadership, not just product-market fit. Sometimes shown by either domain expertise, speed of product optimization, or by lack of competition in the category. This creates a counterintuitive dynamic where it can be easier to fund a company with strong pedigrees in a hot space and no traction yet than a company that went from 0 to $1M ARR at what used to be considered a rapid pace. Pricing today is driven by trajectories, not moments in time. We used to say investors invest in lines not points; I think that's more true than ever now because crossing certain milestones doesn't carry as much influence as it once did. Finally, investors still say that valuation matters, but many of them are acting differently. Pace and belief in category-defining companies really sets the price; while slower growth gets scrutinized rather than discounted. One silver lining in the camp of durable growth: Series A rounds are happening so fast that many companies don’t yet have meaningful history of retention data. Large bets are being made on velocity before the durability is proven. Several investors told me the same thing: we may soon swing back to a market where retention, not growth, becomes the defining metric. Let's hope so. I'll share my third SF VC takeaway tomorrow!
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Uche Aniche
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Maddi Holman
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