/ask Swimm, a GenAI coding assistant, provides the next step in the evolution of code understanding by pairing human input with AI for multilayered contextual awareness that utilizes knowledge from the codebase and non-code related information
Swimm, the leading GenAI-powered coding assistant for contextualized code understanding, announced the launch of /ask Swimm, the most comprehensive solution available for enterprise software development teams that combines an AI-powered chat and human input to provide personalized and accurate code knowledge instantly.
Software developers are continuously trying to ship code faster yet often struggle to find accurate answers to their questions due to a lack of good code documentation hygiene and limited contextualized code understanding which can render answers that are too generic and unhelpful. In a recent survey conducted by Swimm, 73% of developers surveyed said that code documentation is important to their organization’s productivity; however, 37% said they spend 5 or more hours a week looking for information to understand code or to answer questions about it. This highlights the current gap that exists between the need for effective code understanding and documentation, which is often required when debugging issues with code or when onboarding new developers, and the tools that are currently available.
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/ask Swimm is an AI-powered coding assistant providing developers with a multilayered contextual understanding of code, enabling them to significantly boost productivity across the entire development lifecycle. The chat is dynamic and personalized to an organization’s specific codebase, documentation, user interactions and other 3rd party tools. A fully contextualized conversational chat within the IDE instantly enables developers to answer any questions about documentation, code, files, repos, or even entire software ecosystems. To gain context, /ask Swimm incorporates factors that are not evident in the code itself, such as business decisions, product design considerations, limitations that were the basis for roads not taken, etc. /ask Swimm automatically captures and updates code-related knowledge in the process, while improving over time with continuous feedback and user-generated documents.
“Some of the biggest names in tech, including Microsoft (Copilot), Google (Duet AI), Amazon (CodeWhisperer), are building code assistance tools. They’re competing on the merits of their analysis capabilities and the LLMs they’re using, but no matter how good they are, a tool doesn’t know what it doesn’t know because it’s lacking the relevant context,” said Oren Toledano, CEO and Co-founder at Swimm. “To provide the most complete picture to engineers, we’ve developed /ask Swimm which is the logical next step in the evolution of code understanding. Context is invaluable especially when refactoring legacy code or trying to understand complex flows and processes in a codebase. By keeping documentation and context up to date with existing code, processing it and feeding it in time to the LLMs, Swimm has solved one of the biggest challenges developers face today.”
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“The Swimm leadership team understands software engineers and their pain points intimately as they’ve lived it themselves. They’ve taken the historically manual and outdated process of code documentation and completely reimagined it using AI,” said Lonne Jaffe, Managing Director at Insight Partners. “If large language models can suggest helpful code, shouldn’t Swimm be able to leverage LLMs to suggest helpful code documentation? Shouldn’t the code documentation captured in Swimm be able to improve future code suggestions and help answer software engineering questions about legacy code? Swimm is doing just that.”
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