Nimrod Kor of Baz
episode
Israeli Technology Founders Speak: Conversations with Successful Israeli Hitech and Biotech Entrepreneurs
27 min
1 speaker
8 chapters
transcribed 13 days ago
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What problem does Baz’s AI code‑review tool aim to solve for software teams?
This is Israeli Technology Founders Speak, a podcast of conversations with successful Israeli high tech and biotech entrepreneurs. With your host, Avraham Hermon.
Nimrod Core is the co founder and CTO of Buzz, an AI code agent that helps teams ship better software faster by automating code reviews, making software development smoother, faster, and more reliable. Avraham sat down with Nimrod to discuss how their technology works, how he came up with the idea, how he got funded, how he's marketing their product, tips. for startup founders and much more. This podcast is a creation of JMB Davis Ben David, an intellectual property law firm serving clients around the world. You have great innovations. We keep them safe. It's not enough to just have a great startup idea or innovation. If you don't legally protect your innovations, products, and brand, anyone can claim them as their own.
We keep your great innovations secure. Learn more by going to jmbdavis.com. That's JMB D A V I S dot com. So thank you, Nimrod. I'm happy to be here in your offices in Tel Aviv. And you're the CTO of Baz and we're gonna hear a little bit about what you guys do. So first of all, can you tell me what problem you guys solve?
Sure. When we started out Buzz, we realized that there is a gap and the gap is only widening between how fast software can be delivered, can be built. Especially the age of AI where I can do front end stuff all of a sudden versus the tooling. The git and the GitHubs of the world, like GitLab, Bitbucket, all of those names, they give you something which is very generic but also very simple. And you have in every company at least a team to do the GitOps, to do all the glue that makes the application go to production. Mm-hmm. And we realized that if we have something that can do this by itself, because it understands languages, because it's an LM based, suddenly teams can deliver faster and it will be a lot simpler to build in the new world.
So let's just talk a little bit about the new world. Just expand on that. What's different today than let's say five, ten years ago?
So I'll let me explain from my my own experience. The previous company I worked at called Bridge Crew, we built a cloud security for developers tool. There's an open source Chekhov which blew up, and it is all based on AST. What is AST? App Store syntax tree. That means that you take the file and you parse it into the building blocks of the code. So there's a program, inside the program there might be classes and functions, and inside the Function, you have the function signature and the function body or whatever it is. So it's a different modeling of the same things that we have in today in our software. But then once we leverage that, you could ask questions about stuff like Does my S3 bucket have encryption key?
That's what we used to be able to ask. And when we opened Buzz approximately two years ago, it was right about when we were writing each other birthday cards. in ChatGPT, which were funny, and little haikus. And what we realized is this is the first time that we have a tool that can understand the semantics, the meaning of the code that I find. Because with ASCs we also we always had the problem that we only got as far as identifying specific values. I know what true is, I know what two is, but if something has a description, I don't know to evaluate whether it's good or bad. And that's something something I can do now with LLMs. So we realized that if we take what we already know how to build, which is the AST, and integrate it with LLMs or make it more holistic with LLMs, we can actually
LMs are language learning models. Yes, the
large language models. Those are the models that you can send them text and they reply like Chat GPT. So they un actually understand the semantics and that allows us to bridge a gap that we had it with our previous tool, which was great for security, but it wasn't good enough for developers.
See, so you're aiming towards developers and you're making their lives easier now.
Yes, development teams especially.
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Chapters
8 chapters
1
What problem does Baz’s AI code‑review tool aim to solve for software teams?
0:00–4:24
2
How does Baz combine AST analysis with large‑language models to automate code reviews?
4:24–7:47
3
What challenges did the team face with AI hallucinations and how did they fix them?
7:47–10:24
4
How did Nimrod and his co‑founder Guy turn their previous startup experience into the idea for Baz?
10:24–13:51
5
What strategies does Baz use for hiring, team building, and scaling during the war in Israel?
13:51–16:47
6
Which investors backed Baz and what advice do they have for securing AI funding?
16:47–19:58
7
What is Baz’s approach to intellectual property, patents, and open‑source contributions?
19:58–23:22
8
Where does Nimrod see Baz in the next year and in five years within the software development ecosystem?
23:22–27:26