Sourcegraph is the code intelligence platform helping developers locate, understand, fix, and automate their code — across every host, language, and repository.
They’re trusted by everyone, from physicists at CERN to coders at Uber, Dropbox, Yelp, and more.
We sat with Beyang Liu, Co-Founder and CTO of Sourcegraph, to learn how information search tools like Sourcegraph and Dashworks supercharge engineering productivity. We cover:
- Why enterprise code search is highly undervalued
- How saving developer time drives massive ROI
- The future of search and knowledge retrieval
“Both startup and enterprise-scale engineering teams need search tools that enable them to work productively with high volumes of information streams.”
Use Cases for Code Search: From Startups to Enterprises
The core pain point that Sourcegraph solves is what they call "big code" and how it affects countless unique developers and teams differently.
As an individual developer, it isn't easy to progress in a codebase where there are a lot of legacy structures and work they need to understand.
They might be inside a vast company with an old codebase. They must contextualize that code to build a new feature or fix a bug. Unfortunately, doing so costs time and money.
Beyang and his co-founder Quinn experienced this firsthand while working at Palantir.
The company had a solid development organization with smart people, but they still experienced these dev struggles daily despite that.
They also witnessed Palantir working with large banking clients who struggled to ship software. It seemed everyone was having trouble getting their base code up and running.
How Sourcegraph Turbocharges Search Functionality
Beyang points out that Sourcegraph doesn't have many competitors, to begin with.
There are open source utilities published by various developers building for themselves, but they’re only adjacent to Sourcegraph.
The table stakes feature set for code search is regular expression search plus string literals; it’ll work on a reasonable scale codebase. That's where many organizations using code search start and end.
Sourcegraph is unique since it builds on that foundation in several ways.
1. Advanced Search Function
Sourcegraph utilizes its extensive query language, which allows users to filter precisely for what they're looking for, search over symbols and package names, and scope it to specific files.
That is impossible with more typical open source code searches.
2. Precise Code Navigation
Sourcegraph runs compiler-accurate or IDE-accurate code navigation — that works.
Most code search engines only deal with the search but lack the navigation component. And, even if they do navigate, it's more of an approximate exercise.
Why Startups Need to Adopt Search Tooling
If Sourcegraph was built with enterprise legacy systems, what can it do for startups establishing their codebases from zero?
While the platform’s early adopter market was mainly teams of at least 50 devs, code search is universally appealing and impactful.
For Sourcegraph’s early-stage clientele, teams commit new code and make growth moves at a rapid pace — and people have to understand the code their teammates are adding.
Otherwise, the product could be stunted before it’s even launched.
In response, Sourcegraph facilitates harmony for dev teams. It hooks into code reviews, the dependency trees they’re pulling in, and the debugging process.
“If you're a startup developer, there's a giant universe of code we're all living in now. So it's time-consuming to understand something someone else built.”
The ROI of Centralized Search: Engineering Productivity
When companies are on board with Sourcegraph, they see engineering benefits right out of the gate.
Developer productivity and velocity increase because the vast majority of their job these days is the actual development. It's not just writing code; it's reading and understanding existing code.
Sourcegraph tackles that part of the job head-on. It ensures you’ll understand the current base quickly and effectively as possible, so you’re ready to build and introduce new facets.
Around this use case, developers find the platform especially helpful in four adjacent areas.
1. Remediating Security Vulnerabilities
Let’s say portions of your codebase are vulnerable due to an outdated version of Log4j.
You’ll need to upgrade ASAP, but that requires finding and fixing every instance where that vulnerability occurs. Sourcegraph reduces that time to identification and resolution.
2. Reducing Instant Response Time
Along those lines: If your site goes down and there's a bug in the logs, you need to get to the root cause and solve it to get your site back online immediately.
Again, that’s made possible by Sourcegraph’s incident response functionalities.
3. Improving Code Quality
You can leverage Sourcegraph to ensure a concerning collection of anti-patterns will not be added to your codebase. Or, you can ensure you’re making the necessary changes to your base over time to pay down tech debt.
4. Streamlining Onboarding Flows
Across every team, onboarding is usually a waste of time and resources for established team members running training and new hires being put through outdated flows.
When hiring developers, that time suck comes in getting them up to speed on your codebase.
Even after that initial period, developers rarely stop onboarding because there's always a new part of the base to understand.
Sourcegraph critically accelerates the process by facilitating codebase access, navigation, etc.
“Part of being a software engineer is continuously processing new code. Centralized search provides a critical path to helping you get up to speed quickly.”
The Future of Reliable Enterprise Code Search
When pitching Sourcegraph to a client that may not understand the current difficulties of code search, the team can highlight the platform’s ROI in two significant areas.
1. Saving on Downstream Costs
Oftentimes, there are workflows requiring an enormous effort that Sourcegraph could streamline.
For instance, many of their clients are undergoing cloud migrations, so they're trying to move from on-prem legacy services to the cloud.
Countless changes must occur within the source code as part of that process. There might be a significant refactoring effort to update all indications of this legacy API to a cloud-native one.
Every company would want this job done right the first time to save on downstream costs. On that front, Sourcegraph is the best possible tool for targeting and tackling these tasks.
2. Accelerating Developer Speed
This is a catch-all attraction. Regardless of a company's priorities, everyone aims to save developer time because it has a clear price tag.
It's the most non-fungible resource due to the specificity of software domain knowledge.
A new developer can't just jump in and be as productive as the original developer who's years deep in that particular codebase area.
As such, the time Sourcegraph saves is crucial and quantifiable.
Every action on the platform — a search, a jump to definition, or finding references to look up examples — is assigned a lower bound for time saved.
Sourcegraph aggregates and displays this on the admin dashboard as minimum dev time saved.
It’s Time to Replace Your Internal Code Search Engine
If a customer has an in-house version of code search, it's usually because a single engineer felt these pain points severely enough to build one themselves.
Over time, more and more people at the company likely started using that tool — until hundreds of devs were using a code search running off a single development machine.
Companies usually look to move off these in-house solutions because something as simple as the engineer being OOO can shut the site down and stonewall productivity.
A productized solution avoids these blockers and frees up engineering resources.
“Software teams want their engineers working on core competency because developer time is non-fungible and worth more than the money you pay for it.”
Predicting the Next Wave of Search
Traditionally, exploring code has entailed cloning specific repos, opening them in an editor, maybe visiting GitHub, and generally struggling with code navigation.
Today, Sourcegraph fundamentally changes how people and enterprises interact with code.
Sourcegraph (alongside search peers like Dashworks) is the best code search product on the market, rapidly evolving core functionalities while expanding languages, integrations, etc.
In the next 2–3 years, Beyang anticipates Sourcegraph being able to map out the entire universe of code — meaning it’ll understand every codebase at an accurate compiler level.
It’ll support a seamless, web browser-style interface to essentially any world of code.
Beyang highlights a few use cases he’s particularly excited to see within 5–10 years:
- Code quality lending — Teams use open source lenders but struggle to enforce clear, consistent code quality. Sourcegraph can be that single view for engineering leaders.
- Day-to-day use — Overall, Sourcegraph aims to make codebase info retrieval and processing as seamless as running a Google search and clicking around results.
- Software supply chain security — Devs can and will be able to use Sourcegraph to search through a dependency graph for vulnerabilities and other auditing purposes.
“Sourcegraph wants to eliminate sources of friction, so anyone on a team can go into a codebase, navigate it easily, and get up to date painlessly.”
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