Using Glean Chat as a software engineer – Assistance & debugging

As a Software Engineer at Glean, I have some wonderful opportunities to both work on and with Glean. Since July 2022, I've worked on the Backend Features team, and have contributed significantly to our autocomplete and Glean Chat features. 

My daily tasks extend beyond just coding – on any given day, I might be implementing new features, debugging existing ones, or enhancing the software's functionality. I frequently collaborate with other teams, contributing to documents and discussions that help track the status of various projects, along with roadmap planning that ensures projects stay on track and are adjusted as necessary. 

Across many of these workflows, Glean Chat has been nothing short of transformative. The way it has seamlessly integrated into my workflow, especially with the proactive bot feature in Slack, has been a game-changer. It feels like I have a truly personalized work assistant that meets me where I am, helps me find information efficiently, and saves me valuable time. 

In this blog, I’ll be exploring more about how I make the most of Glean Chat, along with how I integrate AI for work into my day-to-day tasks – helping me achieve my best work and productivity as a software engineer.

An insider perspective

Glean Chat is built to be truly useful rather than just ‘usefully wrong’. It’s an enterprise-ready generative AI assistant that synthesizes actionable insights and precise answers for any work-related questions you may have. 

Glean Chat's ability to understand code effectively based on natural language queries, along with its capability to surface any and all context required regarding code and documentation, enables engineers to stay quickly informed, up-to-date, and empowered to deliver great code in less time. 

Bottom line? This means that I can write and understand code better without having to dig around so much for the right documentation and context. I can get reliable answers directly sourced from all the information within my enterprise's corpus. That doesn’t just mean code – it includes documents, wikis, tickets, tasks, emails, and so much more.

Putting it into practice 

What has truly set Glean Chat apart for me is how it understands the context of my queries. This capability has been instrumental in providing more accurate results, even when my queries are complex or involve multiple elements. Information that may take me conventionally half an hour to cobble together takes Glean Chat just minutes – and delivers it to me in an easily digestible format with full references to back it up.

This not only makes my workflow more efficient, but also gives me more time and attention to focus on the more critical aspects of my work. Rather than sifting through and verifying documentation, I can spend more time in code – and when I’m in a flow state, Glean helps me stay in the zone. 

Another significant benefit has been Glean Chat's capability to interact with code. The tool felt like a true coding expert assisting me in understanding, writing, and fetching code snippets – all within the context of my projects and workplace. Its ability to provide contextually relevant assistance was impressive, especially when debugging errors or understanding recent changes. It creates a search query from my question, fetches diffs from indexed documents, and summarizes them, reducing the friction usually involved in finding the right information. 

The tool also offered invaluable guidance when I needed to implement a piece of code but didn’t know where to start. It was able to generalize from similar changes in the past and provided guidance on the files and code that needed to be changed.

Generative AI that’s ready for the enterprise – today

Glean Chat has been uniquely and immensely beneficial for my productivity. It made code-related tasks both more manageable and less time-consuming. The unique combination of code helper and work assistant improves my productivity and efficiency significantly. When it comes to dealing with code-related tasks, its capability to provide quick and accurate answers to technical questions has significantly reduced coding and debugging time. It also assists me in understanding and generating code based on context and existing documentation, making it easier to start new projects. 

Glean Chat is an incredibly valuable tool for any software engineer looking for a true workplace assistant that’s knowledgeable in both enterprise and coding knowledge – and I haven’t even scratched the surface of how it works and what it can do. Learn more about Glean Chat and how software engineers can make the most of it in our latest eBook. 

If you’re looking to supercharge your or your team’s productivity with a generative AI solution that’s truly enterprise-ready, sign up for a demo today!