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Software developers spend most of their time No Writing code; Recent industry research found that actual coding accounts for less 16% developers working hoursThe rest was consumed by operational and supporting functions. As the engineering teams are pressurized to “do more with less” and the CEOs are bragging about how much of their codebase is written by AI, one question is: What is done to customize the remaining 84% of the remaining 84% tasks that engineers are working?
Keep developers where they are the most productive
A major criminal for developer productivity is the reference switching: constant hopping between the growing equipment and growing array of platforms required to create software and ship. A Harvard Business Review Study found that average digital worker almost flipped between applications and websites 1,200 times per dayAnd every blockage matters. The University of California found that it takes About 23 minutes To focus perfectly after a single obstruction, and sometimes worse, about 30% Disrupted tasks are never resumedReference switching is actually at the center of Dora, the most popular performance is one of the software development structure.
In an era where AI-operated companies are trying to empower their employees to reduce more, some trends are emerging beyond “bus”. For example, Principal Engineer Jarod Rohland in Brakes, Concept This “developers provide their highest value on focusing within their integrated development environment (IDE)”. Keeping this in mind, he decided to find new ways to do so, and the new protocol of anthropic could be one of the keys.
MCP: A protocol in terms of IDE
Coding assistants, such as LLM-operated IDEs like Karsar, Copilot and Windsurf, are at the center of one. Developer RenaissanceTheir adoption pace is ignored. Cursor became the fastest growing mother -in -law in history, reached $ 100 million arrest within 12 months of launch, and 70% 500 of luck Companies use Microsoft Copilot.
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But these coding accessories were limited to only codebase references, which could help developers to write rapid code, but could not help in reference switching. A new protocol is addressing this issue: Model Reference Protocol (MCP). Continued by anthropic in November 2024, it is an open standard developed to facilitate integration between the AI system, especially LLM-based tools, and integration between external equipment and data sources. The protocol is so popular that there is 500% increase New MCP server in the last 6 months, with estimated 7 million downloads in June,
One of the most impressive applications of MCP has the ability to directly connect the AI coding assistants to the equipment developers, relying on every day, streamlinography the workflows and dramatically reduces reference switching.
Take convenience development as an example. Traditionally, this involves bouncing among many systems: reading tickets in a project tracker, looking at a conversation with a team partner for clarification, searching for documents for API details and finally, opening IDE to start coding. Each step lives in a separate tab, which requires mental changes that slow down the developers.
With clouds of anthropic such as MCP and modern AI auxiliary, this entire process can occur inside the editor.
For example, a coding becomes to apply a feature within the assistant:
The same principle may apply to many other engineers workflows, for example an event reaction for Sre:
Nothing new under the sun
We have seen this pattern before. In the last decade, Slack has changed the productivity of the workplace by becoming a hub for hundreds of apps, enabling employees to manage a wide range of tasks without leaving the chat window. Slack platform reduced reference switching in everyday workflows.
For example, the riot games, associated with around 1,000 slack apps, and engineers saw 27% reduction Testing and recurrence code in time, 22% fast time to identify new bugs and 24% increase in convenience launch rate; All were attributed to streamlining the workflows and reducing the friction of tool-switching.
Now, a similar change in software development is taking place, serving as a bridge of all these external devices with AI assistants and their MCP integration. In fact, IDE can become a new all-in-one command center for engineers, a lot of slack has been for general knowledge workers.
MCP Enterprise may not be ready
MCP is a relatively newborn standard, for example, safety Wisem MCP has no underlying certification or permission models, relying on external implementation that are still developed, even around identity and auditing. There is ambiguity-the paint is not clearly separated whether an action was triggered by a user or AI is the responsibility of additional custom solutions and AI is the responsibility of additional custom solutions. Is making it difficult to Lori McVitty, prestigious engineer and CTO’s F5 Network Office, Chief Employee, They say That MCP is breaking the core security beliefs that we have held for a long time. “
Another practical range arises when many MCP tools or servers are used simultaneously, for example, inside a coding accessory. Each MCP advertise a list of tools with server details and parameters, which needs to be considered on the AI model. Flooding models with dozens of available devices may overwhelm its reference window. Performance decreases as the performance of the device grows with some IDE integration, applied to prevent blotting beyond the model, which can handle the model to apply hard limits (~ 20 tools for the cursor IDE), or ~ 20 tools for openAI agents).
Finally, there is no sophisticated method for devices being auto-discovers or relevant suggestions beyond listing them all, so developers often have to manually togle them manually or cure which tools are active to work smoothly. Referring to that example of the riot game installing 1,000 slack apps, we can see how this enterprise can be disqualified for use.
Low Kunda-Kursi, more software
The last decade has taught us the value of working for the worker, which is on the pipe “inbox zero” email functioning and integrated platform engineering dashboard in updated from slack channels. Now, with AI in our toolkit, we have the opportunity to empower developers to become more productive. Suppose the slack became the center of commercial communication.
In that case, coding assistants are well deployed to become the center of software construction, not only the code where it is written, but where all references and collaborative coal are. By placing the developers in their flow, we constantly remove mental gear-shifts that have affected engineering productivity.
For any organization that depends on software delivery, take a difficult look at how your developers spend their days; You may be surprised by what you find.
Silvan Kalche led AI Labs With bread,
