TOP 7 AI Tools Every Developer Needs to Know
Until very recently, the shift to AI in our lives as devs has been gradual. Now, the creep is ready to become more of a rush.
Here are 5 of the very best AI tools for software engineers.
1. What The Diff
What does it do? It streamlines code reviews and improves team communication.
This AI-powered tool enables teams to write better pull request descriptions, review them faster, and keep all members - technical or otherwise - in the loop. Just comment on the lines of source code that need refactoring, describe the changes you want, and What The Diff will suggest those changes within the pull request. The tool can even generate summaries of your pull requests, devoid of technical jargon, to keep everyone updated.
Good for: Teams that are frequently reviewing and merging code. The automatic refactoring and summarizing features can be real time-savers, especially for larger teams working on complex projects.
2. Sourcegraph Cody
Cody AI is an AI assistant designed to radically speed up your coding process.
Make you, and your team, ten times faster at creating software, with Code AI, an AI assistant that uses machine learning to read, understand, and answer questions about your entire codebase, documentation, and code graph.
3. Mintlify
Automatically generate code documentation, saving you valuable time.
It integrates with your favorite code editor and generates documentation for your code in an instant.
Some of the best features:
- One-click documentation – it’s that simple
Good for: Developers and teams looking to save time on documentation and improve their code's readability. It shines in situations where clear, precise documentation is needed, especially for complex functions.
4. Grit.io
An automated tool that simplifies code migrations and dependency upgrades.
This powerful developer tool uses AI to automatically manage your technical debt, including automating tedious tasks like code migrations and dependency upgrades. It can generate pull requests following best practices, with a built-in radar for detecting regressions.
Good for: Teams dealing with legacy systems and frequent code migrations. It's a lifesaver for organizations trying to keep pace with evolving technologies without losing sight of their existing projects.
5. Otter
At the core of OtterPilot is a highly sophisticated AI engine that understands and documents meetings with remarkable accuracy. OtterPilot records audio, transcribes speech in real-time, captures slides, and allows users to comment and highlight key points live. Post-meeting, it generates and emails a comprehensive summary of the meeting, making it easier to recall, share, and action key information.
Some of the best features:
- Automated meeting notes – It can automatically join and record your Zoom, Teams, and Google Meets.
- Automated slide capture – captures and inserts slides into the notes
- Automated summary – generates and emails a summary to everyone involved
Good for: Any team with too many meetings, and anyone that wastes time catching up on them.
Alternatives: Comparable tools offering similar functionality include Fireflies.ai, Clara, and Voicea.
6. Adrenaline AI
Adrenaline AI is a more lightweight tool that serves as an expert guide to your codebase.
Designed to understand your codebase, it’s an expert consultant available at your beck and call. With Adrenaline AI, you can quickly get insights into how features work or find out where something is implemented. It reduces time wasted in seeking answers externally.
Good for: situations where quick orientation and code understanding are a common requirement. It can be a game-changer in environments with high developer churn or for onboarding new team members.
7. Stepsize AI
Stepsize AI monitors everything happening in your Jira board or Linear team. It enables intelligent connections between your tasks, activities, and goals, and develops a rich context of what's happening.
The goal behind this is to create highly accurate, automatic weekly sprint reports with the perfect amount of context and detail.
Good for: Agile software project teams, from product managers and Scrum Masters to software engineers and DevOps professionals. It's specifically effective for remote teams where communication and project tracking can be challenging.
Takeaway
Many more tools continue to emerge in the AI sphere. As this technology revolutionizes the industry, it is vital to keep learning and leveraging its potential as much as possible.
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What do you think about these tools?