@Sourcegraph
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Take control of your codebase.
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Joined June 2013
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Agentic Batch Changes is available today.
Describe a change once. It runs across 10 or 10,000 repositories, adapts where they differ, and reacts when CI fails.
Agentic Batch Changes uses outcome-based pricing. You pay per changeset merged into your codebase.
If a pull request doesn't merge, you don't pay for it.
Read more here: sourcegraph.com/blog/introdu…
Sourcegraph retweeted
We launched Agentic Batch Changes this week: the very first coding agent with outcome-based pricing. You only pay when you merge a PR, not per token.
Despite the innovation in other verticals—Sierra, Fin, Decagon, and more all charge per resolution—dev tools have remained firmly tied to seat- and usage-based pricing.
So why are we doing this? We’re confident in the product, and pricing on outcomes is the clearest, most tangible way to prove it. This pricing puts our incentives in lockstep with yours.
sourcegraph.com/blog/agentic…
Sourcegraph retweeted
Today @sourcegraph’s Agentic Batch Changes, the frontier agent for large-scale code changes and migrations, goes live. The Batch Changes engine already helps our customers merge half a million PRs per year for security and remediation, dependency upgrades, and ops migrations. With this release, we are bringing a frontier agent to oversee changes and adapt to the unique requirements of thousands of repos at once.
sourcegraph.com/blog/introdu…
Sourcegraph retweeted
We announced our MCP server a year ago this month! Usage is up 560% in the last 6 months. The acceleration of work being done by agents is just unbelievable, and we’re lucky to be on the front lines @sourcegraph
Context is everything. The best enterprise eng teams in the world are adopting Sourcegraph
Sourcegraph retweeted
Many customers ask me what Code Finder is, and why we introduced a second agentic search on top of Sourcegraph's (deterministic) code graph.
On the 2x2 of cost vs. comprehensiveness, it was important to us to have an offering at the frontier in both the top right and bottom left. Code Finder is NOT for a deep, global investigation like Deep Search. It's faster, cheaper, and a perfect daily driver upgrade over ripgrep (not to mention for high-volume automated workflows).
Code Finder is also our *first* MCP-only product 👀. Humans need not apply.
Code Finder is now generally available.
sourcegraph.com/changelog/co…
Starting December 7, federal agencies will have as little as three days to remediate vulnerabilities in the highest-risk class of flaws.
That urgency extends beyond the federal government. Remediation windows are shrinking while enterprise codebases keep expanding.
At codebase scale, critical gaps emerge between the tools security teams rely on, slowing teams down as the pressure to act increases.
See where enterprise security programs break down and what closing the gaps looks like: sourcegraph.com/blog/vulnera…
For the fifth consecutive year we're on the Inc. 5000's list of fastest growing companies!
"We’re honored to be recognized on the Inc. 5000 again,” said @DanielNealAdler, CEO of Sourcegraph.
businesswire.com/news/home/2…
We traced 517,604 commits across 120 established open source repositories to see how quickly agents are being adopted, where their code lands, and whether it sticks.
A vulnerability discovered in one repository may exist across hundreds more.
Prevention, detection, and response share a hidden dependency. When visibility breaks at repository boundaries, all three weaken together.
AI-generated code and dependency sprawl are making those gaps harder to see and the consequences harder to contain.
See what connects the three and why repository-level security leaves critical gaps across the codebase: sourcegraph.com/blog/detecti…
Sourcegraph retweeted
When shipping code is getting easier than ever.. it's also harder than ever to build the right stuff. Join my team @Sourcegraph as *the* Product Manager!
grnh.se/7hca2iem4us
From the Changelog
Introducing Code Finder Beta and Compare Page GA
youtube.com/watch?v=VR74iU4m…
Not all AI coding tools approach codebase context the same way. Some rely on prompts. Others use indexing, repositories, MCP servers, or long-context approaches. Our comparison breaks down five approaches to codebase context and the tradeoffs behind each so you can determine which is best suited for your team's needs.
sourcegraph.com/resources/co…
Sourcegraph retweeted
Absolutely love this conversation between industry legend and co-creator of .NET, Peter Smulovics (@MountGellert) from Morgan Stanley, and @erikseliger and @bobheadxi on @Sourcegraph's new Agentic Batch Changes tech for large-scale migrations! Thank you @FINOSFoundation for hosting us.
youtu.be/mmqLMkdydIo?si=wq85…
1/2) Most AI coding agent failures aren't model failures. They're context failures.
When an agent can't see across your repos, it has to guess. Wrong paths, missing dependencies, and confident nonsense.
2/2) We tested it on real large-scale codebases (Kubernetes, Apache Kafka) with CodeScaleBench.
The results:
✅ 3x better precision
✅ A cross-file task that took 2 hours now takes 89 seconds
Give your agents the context to get it right: sourcegraph.com/solutions/ag…
What does it take to run coding agents reliably in enterprise codebases?
Not just better models.
Better context. Better workflows. Better systems around the agent.
Running Coding Agents in Enterprise Codebases explores the patterns emerging among teams moving from AI experimentation to production adoption.
Get the guide: sourcegraph.com/resources/eb…
1/
Changing code in one repo is easy.
Rolling that same change across tens or hundreds of repos is a different problem entirely.
3/
What if you could define the migration in plain English, validate it on one repo, then apply it across your whole codebase with deterministic execution and a human in the loop?
4/
That's the workflow we broke down in this webinar.
See how it works: sourcegraph.com/webinars/mod…