# AI-accelerated development: how GitHub is shaping the future of software engineering | LinearB Blog

> Learn how GitHub's Martin Woodward is leading the charge in AI-accelerated development, and how new tools like GitHub Copilot are "tricking" engineering teams into adopting best practices and a stronger DevOps culture.

_This is a markdown rendering of a live HTML page on linearb.io, generated for AI/LLM consumption — it is not a markdown-only site. To get the full HTML page instead, request this URL with an explicit `Accept: text/html` header (no wildcard, no markdown preference)._

[Blog](https://linearb.io/blog)

/

AI-accelerated development: how GitHub is shaping the future of software engineering

# AI-accelerated development: how GitHub is shaping the future of software engineering

![Photo of Andrew Zigler](https://assets.linearb.io/image/upload/c_limit,w_2560/f_auto/q_auto/v1/Headshot3_d7231cbda7?_a=BAVMn6ID0)

By [Andrew Zigler](https://linearb.io/blog/github-ai-accelerated-development#andrew-zigler)

|

August 22, 2025

![Blog_AI_Accelerated_Development_2400x1256_07554b4b5c](https://assets.linearb.io/image/upload/c_limit,w_2560/f_auto/q_auto/v1/Blog_AI_Accelerated_Development_2400x1256_07554b4b5c?_a=BAVMn6ID0)

The rise of AI in software development comes with a surprising secret: it's not just making us faster; it's making us better. While many predicted AI would lead to sloppier work, the opposite is proving true. AI tools are subtly "tricking" engineering teams into adopting the fundamental best practices - like smaller pull requests, test-driven development, and clearer specifications - that have long been the gold standard of the craft.

As the VP of Developer Relations at GitHub, [Martin Woodward](https://linearb.io/dev-interrupted/podcast/you-can-t-have-ai-without-dev-ops) is at the forefront of this transformation. He sees the evolution from simple auto-complete to sophisticated autonomous agents not just as a technological leap, but as a powerful catalyst for improving engineering culture.

This article explores Woodward's insights on how the new generation of AI agents work, the unexpected ways they are improving development loops, and why a strong DevOps culture is the essential foundation for harnessing this revolution.

## **The evolution of AI development tools**

GitHub Copilot's journey reflects the rapid [maturation of AI in software development](https://linearb.io/blog/ai-in-software-development). What began as an auto-complete function operating in microseconds has evolved into chat interfaces working in seconds and now to autonomous agents that can tackle complex tasks in minutes.

This progression allows developers to "iterate more quickly, which then allows us to put that flow of value to the end user more quickly," Woodward notes. Each step has extended what AI can accomplish while respecting the iterative cycles that are fundamental to good software engineering.

## **Autonomous copilot agents: changing how we work**

The new GitHub Coding Agent represents a significant leap, able to tackle issues independently by analyzing codebases and proposing solutions. Rather than forcing developers to sit and watch the AI code, it works in the background. A developer can now say, "'Hey, Copilot, create me a pull request that does this,' or 'Here's an issue... Copilot, why don't you make a start on it first for me?'"

This approach is powerful because the agent operates within existing workflows and respects established guardrails and tests, making it safer for teams with good practices. The process remains iterative, with the developer always in the loop to review and guide the agent's work. AI also serves as a powerful reviewer. As Woodward puts it, it can describe what the code _actually_ does "ridiculously well," often better than a human can explain their own intent.

## **A surprising side effect: smaller, better pull requests**

One of the most counterintuitive findings is that AI assistance is leading to [smaller, more focused pull requests](https://linearb.io/blog/pull-request-best-practices-our-tips). The need to review AI-generated code encourages developers to work in smaller increments—a best practice many teams have long struggled to adopt.

This shift feels "accidental, but also cool," Woodward observes, as it organically encourages the very habits that lead to higher-quality, more maintainable codebases.

## **The secret sauce: custom instructions**

To truly unlock the power of these tools, teams must go beyond default settings. According to Woodward, "Custom instructions are... the secret sauce that not enough people know about yet."

These instructions—which can specify personal coding styles, team standards, or technical requirements—guide the AI to generate code that aligns with where a team _wants_ their codebase to go, rather than just mimicking what already exists. The teams that get the most out of Copilot are the ones that master this feature.

## **DevOps culture: the foundation for AI success**

Teams with [established DevOps practices](https://linearb.io/blog/devops-transformation) are proving far more successful in adopting AI. They already have the guardrails, testing practices, and rapid feedback loops that make working with probabilistic AI tools both safe and effective.

This foundation allows AI to act as an accelerant for good habits. Because AI works better with clear instructions, teams are naturally motivated to improve their documentation and write clearer specifications. The impact is measurable: Woodward notes that for security vulnerabilities, the time to merge a fix has gone from "weeks to hours."

## **The AI catalyst for engineering excellence**

The evolution of AI in software development is proving to be less about replacing human engineers and more about augmenting their craft. As Martin Woodward's insights reveal, the rise of autonomous agents is not a shortcut around good practices, but a powerful catalyst that accelerates their adoption.

By encouraging smaller pull requests, demanding clearer specifications, and rewarding strong DevOps cultures, AI is "tricking" us into becoming the engineers we've always aspired to be. The most successful teams will be those that embrace a "learn-it-all" culture, continuously adapting as these tools evolve.

For leaders, the path forward is clear: invest in the cultural and technical foundations that allow AI to thrive. By doing so, you can harness this revolution not just to ship code faster, but to [build a more disciplined, collaborative, and excellent engineering organization](https://linearb.io/blog/strategic-lessons-google-engineering-teams).

To dive deeper into the future of AI-accelerated development, listen to Martin Woodward discuss these ideas in depth on the Dev Interrupted podcast.: 

## Improve developer productivity with LinearB

Find us on

[](https://www.linkedin.com/company/linearb)
[](https://devinterrupted.substack.com/)

![Headshot3_d7231cbda7](https://assets.linearb.io/image/upload/c_limit,w_2560/f_auto/q_auto/v1/Headshot3_d7231cbda7?_a=BAVMn6ID0)

## Andrew Zigler

Andrew Zigler is a GTM Engineer at LinearB and the host of Dev Interrupted, a twice-weekly podcast and newsletter where 40k+ builders decode the transition to AI-native development and agentic orchestration. A classicist by training with a degree from The University of Texas at Austin, Andrew spent his early career teaching in Japan before channeling his interdisciplinary instincts into the tech world. His polymath background informs everything he builds, from automated workflows to the stories he tells about the seismic shifts reshaping software creation.

### Connect with

[](https://www.linkedin.com/in/andrewzigler)
[](https://substack.com/@zigler)
[](https://x.com/andrewzigler)

## Your next read

[![Cover image for Code generation is faster than ever, but shipping value isn't](https://assets.linearb.io/image/upload/c_limit,w_2560/f_auto/q_auto/v1/Blog_AI_code_review_bottleneck_2400x1256_d73333ea46?_a=BAVMn6ID0)](https://linearb.io/blog/code-generation-faster-shipping-isnt)

DevEx

[Code generation is faster than ever, but shipping value isn't](https://linearb.io/blog/code-generation-faster-shipping-isnt)

Your team writes more code than ever, but less reaches production. AI moved the bottleneck to code review. Here's how to measure it and unblock your pipeline.&n...

[![Cover image for What to look for in an engineering productivity platform](https://assets.linearb.io/image/upload/c_limit,w_2560/f_auto/q_auto/v1/Blog_Developer_productivity_platform_2400x1256_0d47bff68e?_a=BAVMn6ID0)](https://linearb.io/blog/what-to-look-for-engineering-productivity-platform)

DevEx

[What to look for in an engineering productivity platform](https://linearb.io/blog/what-to-look-for-engineering-productivity-platform)

AI made dashboards trivial, but the data foundation underneath still matters. How to evaluate an engineering productivity platform across four key outcomes.

[![Cover image for Why OpenAI Codex builds the agent first, not the product](https://assets.linearb.io/image/upload/c_limit,w_2560/f_auto/q_auto/v1/Blog_Redefining_agentic_autonomy_2400x1256_98ff8e15fc?_a=BAVMn6ID0)](https://linearb.io/blog/openai-codex-thibault-sottiaux-agentic-autonomy)

DevEx

[Why OpenAI Codex builds the agent first, not the product](https://linearb.io/blog/openai-codex-thibault-sottiaux-agentic-autonomy)

OpenAI’s Thibault Sottiaux reveals how the Codex team ruthlessly simplifies agent design by removing manual scaffolding, solving context compaction at the...

## Structured data

_Machine-readable metadata (JSON-LD) embedded in the page for search/AI context — not content rendered on the page itself._

```json
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "LinearB",
  "url": "https://linearb.io",
  "logo": "https://assets.linearb.io/image/upload/v1715628027/logo-mark-lg.svg",
  "description": "LinearB is the engineering productivity platform that helps engineering leaders prove AI is improving throughput without sacrificing delivery confidence, flow efficiency, or developer experience.",
  "sameAs": [
    "https://www.linkedin.com/company/linearb"
  ],
  "award": [
    {
      "@type": "Award",
      "name": "LinearB is a Leader in the 2026 Gartner® Magic Quadrant™ for Developer Productivity Insight Platforms",
      "dateAwarded": "2026",
      "awardedBy": {
        "@type": "Organization",
        "name": "Gartner®"
      }
    },
    {
      "@type": "Award",
      "name": "Great Place to Work Certification",
      "dateAwarded": "2025-2027",
      "awardedBy": {
        "@type": "Organization",
        "name": "Great Place to Work"
      }
    },
    {
      "@type": "Award",
      "name": "America's Best Startup Employers 2025",
      "dateAwarded": "2025",
      "awardedBy": {
        "@type": "Organization",
        "name": "Forbes Magazine"
      }
    }
  ],
  "hasCertification": [
    {
      "@type": "Certification",
      "name": "SOC 1 Type 2"
    },
    {
      "@type": "Certification",
      "name": "SOC 2 Type 2"
    },
    {
      "@type": "Certification",
      "name": "GDPR Compliance certification"
    },
    {
      "@type": "Certification",
      "name": "ISO 27001"
    }
  ]
}
```

```json
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "AI-accelerated development: how GitHub is shaping the future of software engineering",
  "url": "https://linearb.io/blog/github-ai-accelerated-development",
  "author": {
    "@type": "Person",
    "name": "Andrew Zigler"
  },
  "datePublished": "2025-08-22T07:00:00.000Z",
  "dateModified": "2025-08-22T07:00:00.000Z",
  "image": "https://assets.linearb.io/image/upload/v1755898093/Blog_AI_Accelerated_Development_2400x1256_07554b4b5c.png",
  "publisher": {
    "@type": "Organization",
    "name": "LinearB",
    "logo": "https://assets.linearb.io/image/upload/v1777485755/linearb-logo-2026.png"
  },
  "description": "Learn how GitHub's Martin Woodward is leading the charge in AI-accelerated development, and how new tools like GitHub Copilot are \"tricking\" engineering teams into adopting best practices and a stronger DevOps culture."
}
```

## More on linearb.io

### Top navigation

- [Book a Demo](https://linearb.io/book-a-demo)
- [AI Code Reviews — Catch security risks, bugs, and spec mismatches](https://linearb.io/platform/ai-code-reviews)
- [AI & Productivity Insights — See how AI tools affect cycle time and delivery speed](https://linearb.io/platform/ai-developer-productivity-insights)
- [Measure AI Impact — Track AI adoption and tie it to delivery outcomes](https://linearb.io/use-case/measure-ai-impact)
- [MCP Server — Chat with your data to spot patterns and boost output](https://linearb.io/platform/mcp-server)
- [Resource Allocation — Cost initiatives and shape your investment strategy](https://linearb.io/platform/resource-allocation)
- [Cost Capitalization — Capitalize engineering costs with audit-ready reports](https://linearb.io/platform/cost-capitalization)
- [Dev Team Management — Set targets and tie throughput to business outcomes](https://linearb.io/platform/goals-and-reporting)
- [DevOps Workflow Automation — Policy-based PR routing, approvals, and tests](https://linearb.io/platform/ai-workflow-governance)
- [AI Powered Support — Unify AI and human code delivery in one clear view](https://linearb.io/use-case/ai-powered-support)
- [Optimization — Surface friction with feedback and MCP insights](https://linearb.io/platform/developer-experience)
- [Reporting — Spot what's working and what needs attention](https://linearb.io/use-case/measuring-developer-experience)
- [Surveys — Turn developer feedback into actionable signals](https://linearb.io/platform/developer-surveys)
- [Platform overview](https://linearb.io/platform/overview)
- [Register now](https://linearb.io/event/engineering-productivity-gap)
- [Customers](https://linearb.io/customers)
- [Pricing](https://linearb.io/pricing)
- [Why choose LinearB — Explore your data. Measure performance. Act to improve it.](https://linearb.io/why-linearb)
- [APEX framework — The operating model for AI-era engineering teams](https://linearb.io/resources/apex-framework)
- [Anti-FAQ — The questions other vendors won't answer](https://linearb.io/why-linearb/anti-faq)
- [Security — Enterprise-grade compliance and zero code access](https://linearb.io/security)
- [Build vs. buy — The hidden cost of building it yourself](https://linearb.io/resources/build-vs-buy)
- [Dev Interrupted Podcast — Conversations with engineering leaders](https://linearb.io/dev-interrupted/podcasts)
- [Reports & Guides — Deep dives on productivity and delivery](https://linearb.io/resources)
- [Webinars — Expert sessions on productivity and AI](https://linearb.io/resources?category=workshops)
- [Metrics Benchmarks — See how your engineering org stacks up](https://linearb.io/resources/software-engineering-benchmarks-report)
- [Blog — Product updates and practical insights](https://linearb.io/blog)
- [Help Center — Documentation, setup, and support](https://linearb.helpdocs.io)
- [API Docs](https://docs.linearb.io/api-overview)
- [Status](https://www.linearbstatus.com/)
- [Integrations](https://linearb.io/integrations)
- [LinearB is a Leader in the 2026 Gartner® Magic Quadrant™ for Developer Productivity Insight Platforms](https://linearb.io/resources/gartner-magic-quadrant-dpi-platforms-2026)
- [Sign in](https://app.linearb.io/login)
- [Enterprise](https://linearb.io/solutions/enterprise)
- [Contact](https://linearb.io/contact-us)
- [About us](https://linearb.io/about-us)
- [Careers](https://linearb.io/careers)
- [Service agreement](https://linearb.io/services-agreement)
- [Privacy policy](https://linearb.io/privacy-policy)
- [DPA](https://linearb.io/data-processing-agreement)
- [Security FAQ](https://linearb.io/security-faq)
- [Substack](https://devinterrupted.substack.com/)

### Footer

_Additional links from the site footer, not repeated from the top navigation above._

- [GitHub](https://github.com/linear-b)
- [LinkedIn](https://www.linkedin.com/company/linearb)
- [Twitter](https://twitter.com/LinearB_Inc)