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Last year, Knowledge the AI agent wave started with a so-called product Do – the first in the world AI Engineer. The offer was under wraps for several months, but now it's generally available and learning new chops very quickly. Case in point: the Scott Wu-led startup has just released Devin 1.2, which brings a bunch of new capabilities to take an AI engineer's ability to handle entire development projects to a whole new level.
The highlight of Devin 1.2 is the improved in-context reasoning, which makes the agent better at manipulating and reusing code. It also includes the ability to take voice messages through Slack, which gives users a smoother way to tell Devin what to do.
The development comes at a time when AI-powered agents are being touted as the future of work today. Experts believe that there will soon be a time when people and agents will work together, with the former handling repetitive tasks without notice (which is already starting to happen). Recently, at CES, the head of Nvidia Jensen Huang said that in the future enterprise IT departments would become “HR departments” for AI, responsible for commissioning and maintaining agents working across different roles within the company.
What does Devin 1.2 bring to the table?
Although it is not a major update, Devin 1.2 introduces some interesting capabilities to make the agent better at its job. The key feature here is the enhanced ability to reason in context in a source code. This basically means that Devin can now better understand the structure and content of a store.
With this understanding, the agent can identify which file is relevant to a particular task, recognize and reuse existing code and patterns, and be more accurate in recommending edits or ' creating pull requests (PRs), reducing errors and manual changes.
For developers, this capability would mean accelerated workflows and reduced cognitive load from searching for files, understanding code bases or fixing inconsistent code.
The other notable update with Devin 1.2 is the introduction of voice messages. Devin can also take voice commands from users, via Slack.
All you have to do is tag Devin in a Slack chat, hit the “Record audio clip” button and describe the action or feedback the AI engineer should implement. Devin will prepare a step-by-step function and start executing the command using his developer tools – his own shell, code editor and browser.
The move simplifies how a person interacts with the agent, saving the hassle of typing natural language prompts into Devin's chatbot-style interface.
Improved login process, new campaign controls
Experience has also made some usability improvements in Devin.
For example, in the new release the company includes machine images to simplify the login process for Devin's workspace.
“If you log in for Devin while on board with Devin's browser, we will save the cookie for future sessions (if the cookie expires, you will also need to provide credentials for Devin in Secrets ). This also resolves authentication processes that require visiting a URL on Devin's device,” the company wrote in its blog post.
Cognition also includes enterprise accounts, where group administrators get a centralized console to manage multiple Devin workspaces, including members and their access controls, as well as billing for them .
Finally, the company is adding a usage-based billing model, allowing users to pay for additional capacity beyond their subscription limits. This way, once the users have used up their monthly allocation of ACUs, they can continue to build beyond that limit by paying for additional usage. .
The model has been active since January 9, with users able to set their additional usage budgets according to their needs. This allows users to control consumption while ensuring uninterrupted service when they need additional capacity.
Currently, Devin is generally available for engineering support at a starting price of $500 per month – with no seat limits. Multiple enterprises are already incorporating it into their workflows, including Lumos, OpenSea, Curai Health, Nu Bank and Ramp.
Devin's new capabilities come as competition in the field of AI engineering heats up. From Copilot at GitHub widespread adoption of Magic and Poolside AI raises substantial funding to develop cutting-edge capabilities, the race to create the ultimate AI code assistant getting more intense. Each player is trying to redefine software development, promising faster workflows, reduced cognitive load, and seamless collaboration between humans and AI.
As these AI powerhouses continue to evolve, they're not only changing how developers work but shaping today's work itself, where is efficiency and innovation driven by a partnership between people and machines.
By 2028, Gartner According to estimates, 33% of enterprise software applications will include agent AI, enabling autonomous decisions in 15% of daily work.
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