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The Engineering Lead's 12 Best AI Tools for 2024
2024 is here, and we have a perfect opportunity as leaders to trial and introduce the artificial intelligence (AI) tools that are going to give us a lasting competitive advantage in 2024.
This year has taught us that the teams embracing AI and getting adoption right are seeing significant competitive gains.
In fact, teams aggressively adopting AI with an adoption strategy are seeing as much as 250% gains in speed.
That’s the equivalent of reclaiming 3 hours a day out of every 8 hour day.
So in this article, from a wide range of available tools, I’m casting the light on 12 of the best AI tools and AI software for software engineering teams to embrace, including…
- 4 tools for the SDLC
- 5 tools for shipping code
- 3 productivity tools
Let’s crack on then, and have a look at some of the very best AI tools for software developers.
Part 1: 4 AI Tools for the SDLC
1. Stepsize AI
Stepsize AI generates weekly sprint reports with the perfect amount of context and detail.
If you use Jira or Linear, you can use Stepsize AI to automatically generate a sprint report with the perfect amount of context and detail to use for all kinds of purposes.
These sprint reviews are perfect for getting everyone on the same page at the start of every sprint review, sending product development updates to stakeholders and more.
At the heart of Stepsize is the Operational Intelligence Engine. It observes everything happening across your issue tracker, like Jira or Linear, and forms connections between data points and generates insights. Based on its advanced contextual understanding of your projects and activities, Stepsize AI generates timely, trustworthy updates product development updates for any stage of your agile cycle, whether you use Scrum, Kanban, FaST or something else.
In the end, everyone stays informed without overwhelming you with raw data.
With Stepsize AI, your teams can:
- Effortlessly Align: Create true visibility of what matters and develop your transparency culture across business units, teams, and contributors.
- Minimise Meeting Time: Prioritise meaningful work by reducing time spent in informational meetings.
- Boost Visibility and Transparency: Emulate the communal atmosphere of the "water cooler," thereby enhancing team cohesion, work habits, and organisational culture.
- Limit Context Switching: Keep workflow uninterrupted by minimising the need to ask others.
Learn more about Stepsize AI here. You can get your first sprint report for free.
2. Mintlify Writer
Mintlify Writer automates your code documentation process.
Instead of treating documentation as an afterthought, this tool makes it integral to the development process by generating comprehensive and context-aware documentation swiftly. It means your engineers can do less of what they – let’s say – like less, and instead concentrate more on coding and problem-solving.
Best Features:
- One-click comprehensive documentation
- Supports a variety of programming languages
- Context-aware algorithms for generating pertinent descriptions
My View: Ideal for large and complicated projects where thorough, accurate, and up-to-date documentation is essential, Mintlify Writer fills a significant gap, enabling engineers to concentrate more on coding.
Check out Mintlify Writer here
3. Bugasura
Bugasura is an AI-powered bug tracker for better bug reporting and resolution.
It streamlines the bug reporting and resolution process and keeps all your bugs in one convenient place. It identifies and links similar bugs so that your developers can spend less time finding bugs or on duplicate reports.
Key features
- AI-powered identification and linking of similar bug reports
- Collaborative features like public/private tracker links and project-based organisation
- Practical add-ons such as a Chrome extension and Android reporter for contextual bug reporting with screen captures and annotations
My view – Bugasura makes bug tracking and resolution efficiency easier. Its emphasis on collaboration makes it especially suitable for teams that handle a large volume of bug reports. Especially when those teams use multiple sources to deal with bugs.
4. WhatTheDiff
WhatTheDiff streamlines your code review process by offering automated suggestions and summaries.
WhatTheDiff simplifies the code review process by providing automated suggestions and summaries. It’s perfect for navigating the often intricate and time-consuming world of code reviews, especially when dealing with extensive codebases or frequent pull requests.
Best Features:
- Immediate code refactoring suggestions
- Simplifies pull requests for easy understanding
- Comprehensive reporting and notification features
My View: Optimal for high-speed development teams that handle frequent pull requests, acting as an additional set of eyes to make the code review process more efficient and effective.
Part 2: 5 AI Tools for Shipping Code
5. Sourcegraph Cody
Cody AI is an advanced AI coding assistant for writing code faster.
Maybe you’re expecting to see GitHub Copilot on this list. But it isn’t here. Why? Because today, there are far more sophisticated tools. GitHub have announced GitHub Copilot X, but it hasn’t arrived yet.
Cody uses advanced AI and machine learning algorithms to deeply analyse your entire codebase, accompanying documentation, and code graph. By doing so, it offers insightful and quick answers to queries about your software. The developers behind Cody claim that, by leveraging its capabilities, software development teams can potentially accelerate their coding processes by up to ten times.
Key Features
- Code Navigation: Simply ask about a code location, and Cody will pinpoint it
- Translate Language: If you've got code in C# and need it in TypeScript, Cody can do it for you
- Code Analysis: Cody acts as a vigilant pair programmer, spotting everything from potential edge cases to suboptimal variable naming.
- Debugging Assistance: Provide Cody with a code snippet and a problem, and it will generate a solution.
My view – Sourcegraph Cody appears to be an indispensable tool for teams managing extensive and intricate codebases. By simplifying code navigation and comprehension, it lets developers emphasize actual coding rather than laboriously deciphering their codebase.
6: Tabnine
Tabnine is an established AI code assistant for engineers.
As of mid-2023, TabNine is built on GPT-3.5 along with TabNine’s own architecture. it was originally built on GPT-2 in 2018. That said, it won’t be news to you that GPT-4 is radically better at reasoning, and competitors are making ths most of that advantage.
In that sense, Tabnine is far less experimental than other coding AI tools in this list. It’s a much better thought-out product, having had five years to evolve, and has a bunch of bells and whistles (many of which are valuable) that organisations might want to leverage. It’s totally transparent about what it’s trained on and is more legally robust. It can also run locally out of the box and accommodates various security and compliance requirements.
My view: Tabnine is a less experimental choice for teams that need reliability and security over cutting-edge tech.
7: Mutable AI
Mutable is another AI code writing assistant.
Mutable AI is one of the newest developer tools. While it’s still being developed, it’s quickly become a best-in-class choice. It strives to expedite software development with the assistance of AI. It primarily focuses on diminishing the requirement for boilerplate code and unproductive searches. It means, ultimately, shipping better code, faster.
Best Features:
- Codebase chat and semantic search
- Multi-file AI edit – you can refactor entire directories
- Repo intelligence, which helps find bugs, track team-mate’s work and more
My View: Mutable is a potent alternative to Cody and TabNine that works on the widest range of IDEs (integrated development environments) at the time of writing. Mutable arguably has the edge in code completion, especially over multiple files.
8: CodiumAI
Codium is an AI test-writing assistant
CodiumAI is a fast-evolving AI testing tool with helps you “write code that works the way you meant it to”. It can suggest tests as you write and helps you expand your codebase without breaking things.
Best Features:
- Intelligent test suggestions during coding
- Visibility of code behaviour and how your changes affect everything else
- Analysis of code, docstrings, and comments for test recommendations
My View: CodiumAI is a frontrunner in AI-assisted test-writing. Because it’s a specialist tool, it knows its own craft and performs it excellently. Engineers benefit from much greater confidence in their code and time saved writing test suites.
9. Grit.io
Grit.io is an automated tool that simplifies code migrations and dependency upgrades.
Grit.io specializes in automating and managing technical debts like code migrations and dependency upgrades, turning daunting tasks into manageable ones. It’s still in beta, but it’s evolving fast and their team claim to have generated tens of thousands of successful changes for their customers.
Best Features:
- Automation of technical debt management tasks
- Assistance in code migrations and upgrades
My View: A top pick for teams managing legacy systems or frequently undergoing code migrations. Grit’s a tool that makes maintaining the pace with evolving technologies easier, without losing focus on existing projects.
Part 3: 3 AI Productivity Tools for Software Developers
10. Otter AI
Otter AI is an AI-powered meeting assistant.
Developers shouldn’t be wasting their time catching up on long meetings or summarising what happened in them. Much-loved Otter AI leverages AI to manage meetings more efficiently by providing features like automated summarisation and live transcript summaries.
Key features
- AI chat for improved meeting communication
- Automated meeting summarizations
- Capturing slides automatically for easy review post-meeting
My View: Otter isn’t just for developers but it can certainly save your devs a whole bunch of busy work. Whether it’s scrolling through videos trying to find the bits that matter, summarising action points or catching up on meeting discussions, Otter has many ways to take meeting pain away.
11. Phind
Phind is a specialised search engine explicitly tailored for developers.
Phind is a developer-focused search engine, offering detailed and accurate responses to coding queries. Because answers are more reliable and precise for engineers, they’ll find what they need more easily, and in turn, they solve problems faster.
Best Features:
- Detailed answers to coding queries
- Provides related search links for additional context
My View: Valuable for pretty much anybody who frequently relies on forums like Stack Overflow and Quora, or generic AI-powered tools like Bard or ChatGPT, for coding-related questions.
12. Quillbot
Quillbot is a simple AI paraphrasing tool for writing better.
For those who find themselves constantly revising and contemplating word choices, Quillbot is a time- and brain-saver. It improves the quality and clarity of writing, so we don’t have to spend excessive amounts of time iterating over our text. Though not strictly an AI tool for developers, it's super for drafting emails, creating documentation, or crafting project descriptions. Some engineers will find their Quillbot tab is always open.
Key Features
- Fast rephrasing for better writing
- Synonym slider for nuanced vocab adjustments
- Works with Chrome, Word and more
My view – Perfect for battling writer's block or those aiming for precise phrasing, whether it’s for writing docs or emails. Saves time and energy.
That’s it.
Did I miss something off this list of the very best AI tools for software engineers? Let me know!
I’ve built Stepsize AI with my team at Stepsize.
It observes everything happening in Jira, Linear and soon other issue trackers and keeps everyone informed with product development reports without lifting a finger.
I’d love to know what you think – you can generate your first report on the house here.
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