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BackJack Dorsey's Block Unveils AI Tool That Handles 15% of Production Code Changes
Jack Dorsey's Block Unveils AI Tool That Handles 15% of Production Code Changes
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Cointelegraph18.06.2026تقنية3 dk okuma

Jack Dorsey's Block Unveils AI Tool That Handles 15% of Production Code Changes

نظرة سريعة

  • Jack Dorsey's Block has launched Builderbot, an AI tool capable of executing 15% of production code changes.
  • The system understands the company's entire codebase, allowing engineers to make changes across services and significantly speeding up the development process from months to days.

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لماذا يهم

Block has introduced Builderbot, an AI tool that can execute a significant portion of production code changes, streamlining development and potentially explaining recent layoffs.

حجم الخط

Jack Dorsey’s financial services firm Block rolled out a new suite of AI-native tools on Wednesday, which it says can execute around 15% of all production code changes across the company.

The new AI tooling, Builderbot, is able to execute over 200,000 operations per day and merges approximately 1,500 pull requests per week, said the company.

“The best way to think about Builderbot is as the missing layer between AI coding tools and how engineering actually works at scale,” said Brad Axen, head of AI capabilities at Block. “What used to take months now takes days,” the company added.

The figures show that autonomous AI agents are now able to execute a measurable share of the actual work that ships to production. It is a scaling signal as basic AI coding assistants have evolved into AI software engineers capable of much more than churning out code.

The AI tool also sheds new light on Block's decision to lay off 40% of its staff in February, which Dorsey attributed to the rapid acceleration of AI at the company.

Builderbot understands Block’s full codebase

Builderbot is an orchestration layer that coordinates multiple AI agents across the company’s entire codebase.

Unlike typical coding assistants limited to a single repo, Builderbot understands Block’s full codebase, every service, API and convention, allowing any engineer to make changes anywhere in the company’s systems.

“An engineer working on Cash App can use it to make a change in a Square service they’ve never touched, because the system already knows how that service works,” the company said.

This means that production can also be significantly scaled up with the AI handling the repetitive work, and engineers making the decisions that shape the product.

“It means an idea can go from backlog to live in front of millions of customers in days instead of months,” added Axen.

Related: AI agents with crypto could escape and become ‘unstoppable,’ experts warn

Block said it is sharing details of Builderbot because it believes the shift from AI-assisted coding to AI-native engineering is “one of the most important conversations happening in technology right now.”

“The problems we're solving aren't unique to Block: orchestrating AI agents across a massive codebase, maintaining quality at speed, keeping humans focused on judgment and taste rather than scaffolding.”

AI agents are doing more coding

Block isn’t the only firm to use AI agents for its software development. Engineers at Spotify have been using a background coding agent called Honk, which runs a version of Claude via Anthropic’s Agent SDK.

Co-CEO Gustav Söderström said in a February earnings call that Spotify’s best developers “have not written a single line of code since December.”

Google CEO Sundar Pichai said in April that three-quarters of the company’s new code is AI-generated.

Meanwhile, Microsoft CEO Satya Nadella revealed in 2025 that the company now uses AI to write between 20% and 30% of the code powering its software.

ما الذي يجب مراقبته

توقعات الذكاء الاصطناعي — احتمالات وليست حقائق

  • Other major tech firms will adopt similar AI orchestration layers for code development.

    مرجح · خلال أشهر

  • Further acceleration of AI integration in software engineering roles.

    مرجح جداً · خلال أشهر

أسئلة مفتوحة

  • What is the long-term impact on human engineering roles?
  • How will quality control be maintained at scale?
  • Will other companies adopt similar AI orchestration layers?

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This article was originally published by Cointelegraph.

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