Honeycomb is building agents to automate tasks across the entire software development lifecycle. Our agents are state-of-the-art, achieving 22% on the SWE-Bench coding benchmark.
Autonomous Software Agents
Title: Honeycomb: Autonomous Software Agents | Y Combinator

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Honeycomb: Autonomous Software Agents | Y Combinator
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Honeycomb
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Autonomous Software Agents

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### Autonomous Software Agents

Honeycomb is building agents to automate tasks across the entire software development lifecycle. Our agents are state-of-the-art, achieving 22% on the SWE-Bench coding benchmark.



Honeycomb

Founded:2024

Team Size:2

Location:San Francisco

Group Partner:[Jared Friedman](

 []( "LinkedIn profile") []( "Twitter account") []( "Github profile")

### Active Founders

### Andrew Liu, Founder

Hi, I'm Andrew! CS & EECS + Math at MIT. 



Andrew Liu

[Honeycomb](

 []( "LinkedIn profile")

### Ishank Agrawal, Founder

I'm Ishank, CS @ MIT. 



Ishank Agrawal

[Honeycomb](

 []( "Twitter account") []( "LinkedIn profile")

### Company Launches

[### 🍯 Honeycomb — Bringing autonomy to software engineering](

**TLDR: Honeycomb is building agents to help automate tasks across the entire software development lifecycle.**

We’re building agents that can automate tasks across the software development lifecycle—bug fixing, pull request reviews, knowledge retrieval, and more. Our coding agents are state-of-the-art on SWE-bench, a benchmark for evaluating AI-driven workflows on GitHub issues.

**The Problem**

On average, developers spend more than a third of their time on maintenance, testing, documentation, code review, and other tedious work. This work is necessary but contributes to slower cycles—this problem is exacerbated with larger engineering teams.

While many large companies are working to automate their development processes with AI, this integration is challenging. Creating robust, functional workflows requires significant time and effort. We're developing a solution that works for everyone.

**The Solution**

We’ve built a coding engine that allows our agents to make efficient, precise, and accurate changes to large codebases.

[

Here, we’ve asked our agent to make some quick improvements to its own UI. This is just one use case for our engine; we’re capable of implementing agents across the entire software stack, from testing, documentation, and code reviews to more complex bug fixes and even 0-to-1 development.

We’ve been working hard to ensure that our agents deliver on real-world issues. We evaluated our system on SWE-Bench, a dataset that tests the capabilities of agentic systems against GitHub issues:



Our engine resolved **22.06% of the 2,294** issues in SWE-bench's test set, surpassing the previous state-of-the-art Amazon Q Developer Agent (19.75%). We additionally resolved **40.6% of the 500** issues in SWE-bench’s verified set, also surpassing previous state-of-the-art (38.8%).

**Our Initial Set of Developer Tools Includes:**

*   Automated bug fixing from issue tickets
*   Automated bug tracing from code reviews
*   Automated code reviews on pull requests
*   Knowledge search and sharing

Honeycomb also seamlessly integrates with GitHub, GitLab, Slack, and Discord— with more to come—allowing teams to solve bugs or query their code with just a single command.

**The Team**

👋 Hey, it’s [Andrew]( and [Ishank](



We met during our first year at MIT. Since then, we’ve done research spanning statistics, machine learning, algorithms, and astrophysics. Through research and side projects, we’ve spent a lot of time thinking about ways to program better and eventually realized that the intersection between AI and programming is a future that we’d like to build towards.

**Our Ask**

If you’ve encountered repetitive or tedious problems in software development, we’d love to talk! We would also love to talk to any engineering managers looking to accelerate their development process. Reach us at [founders@honeycomb.sh](mailto:founders@honeycomb.sh), or join the [waitlist](

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