Somewhere inside a large company, an important process is being held together by a spreadsheet nobody planned to make important. It began as a temporary fix. Then it absorbed the exceptions, the workarounds, the names of the people who know which number to trust. Eventually, the file became part calculator, part instruction manual, and part institutional memory. Alex Yaseen has spent his career thinking about the person sitting behind it.
That person may work in finance, supply chain, sales, or operations. They understand the business in a way an outsider cannot. They know why two systems disagree, which customer needs special handling, and what must happen before a shipment can move. Yet when they want to improve the process, the usual choices are narrow: keep doing the work by hand, wait for an engineering team, or stretch the spreadsheet a little further.
Parabola, the company Yaseen formally launched in 2017, is built around changing that choice. Its central idea is that expertise and the ability to implement should live closer together. The product began as a browser-based canvas where people could connect data, arrange transformations, and run a workflow without writing conventional code. It became collaborative. In 2025, it added a conversational interface that can turn a plain-language request into a working, inspectable flow.
01 / The overlooked expertThe solution was already in the room
Yaseen arrived at the idea through strategy consulting. After graduating from the University of Southern California with a degree in finance and management, plus a focus on programming and web development, he joined Deloitte. The assignments varied, but one pattern held. Even large companies ran consequential work through manual processes and sprawling spreadsheets.
The stranger discovery was human. The people closest to a process often knew what was wrong. They could describe a better sequence, name the edge cases, and explain the compromises that had accumulated over time. What they lacked was a practical way to turn that understanding into software. Budget, technical skill, and engineering bandwidth sat somewhere else in the organization.
“If you think it, you can build it.”Alex Yaseen, on the promise behind Parabola
This is the worker Yaseen calls a “knowledge point person” - the teammate who can answer the obscure question because they have lived through the process. Companies depend on these people while often leaving their knowledge undocumented. The spreadsheet becomes their unofficial programming language. It is flexible enough to start, familiar enough to spread, and fragile enough to become a problem once the business depends on it.
02 / FormationEntrepreneurship without a clean ending
The impulse to build a company did not arrive from nowhere. Yaseen was born in Chicago and grew up in Seattle in a household where entrepreneurship was ordinary. His parents built and sold businesses in the food category. He also watched businesses fail. That gave him an early view of entrepreneurship without the polished ending: the creation and the uncertainty, the momentum and the loss.
He founded his first company while still in college. Later, consulting supplied the problem he could not stop seeing. He left a stable job, raised seed funding, and spent roughly two years developing the product that became Parabola. The company name fit a tool meant to give non-programmers more leverage, but the earliest version still needed its own education. Broadly useful software can be difficult to explain because every prospect sees a different possibility.
Over time, the company narrowed its language around operators and the specific work they do: reconciling files, auditing invoices, moving data between systems, monitoring inventory, and assembling recurring reports. During a 2024 branding exercise, the team adopted a corrective whenever the copy drifted into foggy software language: “Just say the thing.” The phrase became a useful test. Could Parabola explain the work as clearly as it wanted customers to document theirs?
03 / ScaleThe pivot from utility to shared system
One important change came when Parabola moved beyond the single-player tool. Teams that shared flows, results, and responsibility received more value and showed more willingness to pay. The product shifted toward collaboration. A workflow could become something colleagues reviewed and reused, rather than a clever construction known only to its original builder.
That change made the product more consequential. A personal shortcut saves an afternoon. A shared system can reshape how a team handles a close, an inventory check, or a freight audit. It also creates a record. The logic can be seen, adjusted, and handed to another person. For Yaseen, that visibility is part of the point. Automation should give operators control over their work, not bury the work inside another black box.
The 2023 Series B was led by OpenView and brought publicly reported funding to $34.2 million across four rounds. The capital arrived as Parabola was working with teams at companies such as Flexport, Sonos, Uber Freight, and Bain. Yet the underlying customer remained recognizable: a person whose business context is rich, whose process is messy, and whose access to engineering is limited.
Yaseen's public language keeps returning to that person. He argues that operations work is often behind the scenes even when it holds the company together. He has also linked good automation to career agency. When an operator can build a process, prove its impact, and make it usable by others, their knowledge becomes visible to the rest of the organization.
04 / AIA sentence becomes the starting point
The arrival of large language models changed how people expect software to behave. For Parabola, the practical question was not whether to add a chatbot. It was whether conversation could shorten the distance between intent and a reliable workflow without taking control away from the operator.
The rebuilt product introduced in May 2025 lets a user describe what they want to automate. Parabola creates the structure and configures the steps on its visual canvas. The user can inspect the logic, approve changes, ask why something is failing, and edit the result. The prompt is the entrance. The visible flow remains the artifact.
Speed matters, but so does authorship. Yaseen's version of AI assistance keeps each transformation visible so the process owner can review the work and remain responsible for the rule.
That distinction leads into Yaseen's 2026 idea of operational legibility. An AI system cannot reliably help a business if the business itself cannot explain how it runs. Rules need to be explicit. Data from separate systems must be connectable. Decisions and exceptions should become durable context rather than disappearing when an employee leaves.
“The companies that figure this out won't just use AI. They'll compound with it.”Alex Yaseen, writing on operational legibility
It is a less theatrical AI argument than replacing entire departments. The prerequisite looks like operational hygiene: documentation, connected systems, and institutional memory. Those practices already help humans. AI raises the value of having them in place. A model may be capable, but capability is not the same as understanding which invoice field is authoritative or when a vendor exception applies.
Yaseen's latest public comments push the analogy further. Software engineers now use AI to move from an idea to a pull request with unusual speed. He expects operations teams to create standard procedures, complete month-end processes, and reconcile multiple data sources with a similar rhythm. The ambitious part of the prediction is not only faster work. It is a shift in who gets to build systems inside a company.
05 / The personLooking closely, then making it visible
Away from the company, Yaseen lists photography, tennis, sailing, and new technology among his interests. His personal website is devoted mainly to photographs. It is tempting to force a tidy metaphor onto those pursuits, but the documented connection is simpler: he likes tools and practices that reward attention.
That same attention shows up in his stories about customers. A cookware brand comparing carrier discrepancies. A customer-experience leader matching support tickets against logistics data. Operations dinners where attendees trade details about sourcing materials or navigating customs. The examples are specific because operational work becomes understandable through the exception, not the slogan.
In 2025, Parabola marked its conversational launch by sending custom mechanical keyboards to customers. The gift was a physical joke about the new interface: type what you want to automate. The response caught Yaseen off guard. Customers posted photographs and notes, and the team spent a day watching the messages appear. For a company built around people whose work often stays invisible, the moment made the community visible.
Parabola's form will keep changing. It has already moved from visual building to collaboration to conversational assistance. Yaseen's founding concern has been steadier: the expert should not have to surrender the problem in order to implement the solution. The closer software gets to ordinary language, the more plausible that idea becomes. The important part is preserving the expert's judgment when the building gets faster.
The spreadsheet hidden in the middle of a company will not disappear because someone announces its replacement. It disappears process by process, when the person who understands the work can finally express the rules in a form the team can run. Yaseen has spent years betting on that person. Now AI is making the bet easier to see.