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Everyone’s talking about it: AI is changing how we work. And nowhere is that more true than in the field of software engineering.

If you’re just getting started as a developer, you might be wondering: is AI ruining my chances of getting a junior-level role? After all, a 2023 study by ServiceNow and Pearson projects that nearly 26% of tasks performed by [current] junior application developers will be augmented or fully automated by 2027. 

In a word: No. Quite the contrary. New learners are well positioned to thrive as junior developers because they’re coming into the workforce already savvy with AI tools, which is just what companies need to adapt to the changing ways software is being developed.

Our CEO Thomas Domke says:

We’re entering an era where interns and junior developers are showing up already fluent in the best tools for AI code-gen on the market. Why? They vibe with AI. They build with it. Fresh talent ➡ better ideas ➡ the best tools. :robot_face:

Thanks @GergelyOrosz for the story on how we’re… https://t.co/Sj6KAbq7dz

— Thomas Dohmke (@ashtom) May 27, 2025

Hear more from Thomas on The Pragmatic Engineer podcast > 

So what does that mean for you? According to Miles Berry, professor of computing education at the University of Roehampton, today’s learners must develop the skills to work with AI rather than worry about being replaced by it. As a junior developer, you need to think critically about the code your AI tool gives you, stay curious when things feel unfamiliar, and collaborate with AI itself in addition to senior team members. 

As Berry puts it:

“Creativity and curiosity are at the heart of what sets us apart from machines.” 

With that in mind, here are five ways to stand out as a junior developer in the AI era:

1. Use AI to learn faster, not just code faster 

Most developers use GitHub Copilot for autocomplete. But if you’re just starting out, you can turn it into something more powerful: a coding coach.

Get Copilot to tutor you

You can set personal instructions so Copilot guides you through concepts instead of handing you full solutions. Here’s how: 

In VS Code, open the Command Palette and run:

> Chat: New Instructions File

Then paste this into the new file:

---
applyTo: "**"
---
I am learning to code. You are to act as a tutor; assume I am a beginning coder. Teach me concepts and best practices, but don’t provide full solutions. Help me understand the approach, and always add: "Always check the correctness of AI-generated responses."

This will apply your tutoring instructions to any file you work on. You can manage or update your instructions anytime from the Chat > Instructions view.

Ask Copilot questions

Open Copilot Chat in VS Code and treat it like your personal coach. Ask it to explain unfamiliar concepts, walk through debugging steps, or break down tricky syntax. You can also prompt it to compare different approaches (“Should I use a for loop or map here?”), explain error messages, or help you write test cases to validate your logic. Every prompt is a learning opportunity and the more specific your question, the better Copilot can guide you.

Practice problem solving without autocomplete 

When you’re learning to code, it can be tempting to rely on autocomplete suggestions. But turning off inline completions — at least temporarily — can help strengthen your problem-solving and critical thinking skills. You’ll still have access to Copilot Chat, so you can ask questions and get help without seeing full solutions too early.

Just keep in mind: This approach slows things down by design. It’s ideal when you’re learning new concepts, not when you’re under time pressure to build or ship something.

To disable Copilot code completion for a project (while keeping chat on), create a folder called .vscode in the root of your project, and add a file named settings.json with this content:

{
  "github.copilot.enable": {
    "*": false
  }
}

This setting disables completions in your current workspace, giving you space to think through solutions before asking Copilot for help.

Read our full guide on how to use Copilot as a tutor >

2. Build public projects that showcase your skills (and your AI savvy)

In today’s AI-powered world, highlighting your AI skills can help you stand out to employers. Your side projects are your portfolio and GitHub gives you the tools to sharpen your skills, collaborate, and showcase your work. Here’s how to get started: In VS Code, open Copilot Chat and type:

/new

Copilot can scaffold a new project inside your editor to help you get started. Once it’s scaffolded, ask Copilot:

“Add the MIT license to this project and publish it as a public project on GitHub.”

Open a command line in VS Code and send the following prompt to manually push:

git init && git add . && git commit -m "Initial commit" && git push

Or create a new repo using the GitHub web interface and upload your files.

From there, you can:

• Track progress with issues, commits, and project boards.
• Document your journey and milestones in the README.
• Iterate and improve with feedback and AI assistance.

Read our full guide on prompting Copilot to create and publish new projects and start building your public portfolio > 

3. Level up your developer toolkit with core GitHub workflows

Yes, AI is changing the game, but strong fundamentals still win it. If you’re aiming to level up from student to junior dev, these core workflows are your launchpad:

• Automate with GitHub Actions. Automating builds and deployments is a best practice for all developers. Use GitHub Actions to build, test, and deploy your projects automatically.
• Contribute to open source. Join the global developer community by contributing to open source. It’s one of the best ways to learn new skills, grow your resume, and build real-world experience.
• Collaborate through pull requests. Coding is a team sport. Practice the same pull request workflows used by professional teams: Review others’ code, discuss feedback, and merge with confidence.

Read our full guide on understanding GitHub workflows >

4. Sharpen your expertise by reviewing code

One of the fastest ways to grow as a developer is to learn from the reviews given by your peers. Every pull request is a chance to get feedback — not just on your code, but on how you think, communicate, and collaborate.

GitHub staff engineer Sarah Vessels has reviewed over 7,000 pull requests. She advises not to be afraid to ask questions during code reviews. If you’re unsure why a suggestion was made, speak up. If something isn’t obvious, clarify. Code review is a conversation, not a test.

Here’s how to make the most of it:

• Ask questions. Use comments to understand decisions or explore alternate approaches. It shows curiosity and builds shared knowledge.
• Look for patterns. Repeated suggestions often point to best practices you can internalize and reuse.
• Take notes. Keep track of feedback you’ve received and how you’ve addressed it, which is great for personal growth and future reference.
• Be gracious. Say thank you, follow up when you make changes, and acknowledge when a comment helped you see something differently.

Read our full guide on code review best practices and learn how to grow from every review >

5. Debug smarter and faster with AI

Debugging is one of the most time-consuming parts of software development. But with GitHub Copilot, you don’t have to do it alone.

Use Copilot Chat to:

• Ask “Why is this function throwing an error?” and get real-time explanations.
• Use /fix to highlight code and generate a potential fix.
• Run /tests to create test cases and verify your logic.
• Try /explain on cryptic errors to understand the root cause.
  

You can even combine commands for deeper debugging — for example, use /explain to understand the problem, then /fix to generate a solution, and /doc to document it for your team.

Read our full guide on how to debug code with Copilot >

The bottom line

Whether you’re writing your first pull request or building your fifth side project, GitHub is the place to sharpen your skills, collaborate in the open, and build a portfolio that gets you hired.

AI may be reshaping the software world, but, with the right tools and mindset, junior developers can thrive. 

The post Junior developers aren’t obsolete: Here’s how to thrive in the age of AI appeared first on The GitHub Blog.

For business leaders building with AI, the conversation has moved beyond chat. The bar is higher: can your AI generate, reason, and deliver measurable outcomes—safely and at scale?

Today, we’re announcing general availability of OpenAI’s new flagship model, GPT-5, in Azure AI Foundry. This is more than a new model release; it is the most powerful LLM ever released across key benchmarks. GPT-5 in Azure AI Foundry pairs frontier reasoning with high-performance generation and cost efficiency, delivered on Microsoft Azure’s enterprise-grade platform so organizations can move from pilots to production with confidence. 

GPT-5 in Azure AI Foundry: Built for real-world workloads

In Azure AI Foundry, the GPT-5 models are available via API and orchestrated by themodel router. The GPT-5 series spans complementary strengths:

• GPT-5, a full reasoning model provides deep, richer reasoning for analytics and complex tasks, like code generation, with a 272k token context.
• GPT-5 mini powers real-time experiences for apps and agents that require reasoning, tool calling to solve customer problems.
• GPT-5 nano is a new class of reasoning model which focuses on ultra-low-latency and speed with rich Q&A capabilities.
• GPT-5 chat enables natural, multimodal, multi-turn conversations that remain context-aware throughout agentic workflows, with 128k token context.

Together, the suite delivers a seamless continuum from rigorous agentic coding tasks, to relatively simple Q&A—all delivered with the same Azure AI Foundry endpoint using model router in Foundry Models.

Under the hood, GPT-5 unifies advanced reasoning, code generation, and natural language interaction. It combines analytical depth with intuitive dialogue to solve end-to-end problems and explain its approach. Agentic capabilities allow multi-step tool use and long action chains with transparent, auditable decisions. As a frontier-level coding model, GPT-5 can plan complex agentic workflow, build migrations, and refactor code, as well as produce tests and documentation with clear rationale. Developer controls—including parameters like reasoning_effort and verbosity—let teams tune depth, speed, and detail, while new freeform tool-calling features enable broadens tool compatibility without rigid schemas.

Orchestrate with the model router—then scale with agents

Introducing GPT-5 to Azure AI Foundry is more than a model drop: it’s a leap forward for the platform. Starting today, developers can use the model router in Foundry Models to maximize the capabilities of the GPT-5 family models (and other models in Foundry Models) while saving up to 60% on inferencing cost with no loss in fidelity. Powered by a fine-tuned SLM under the hood, the model router evaluates each prompt and decides the optimal model based on the complexity, performance needs, and cost efficiency of each task. Let the model router pick the right model so that you can build your AI-powered applications with ease.

And orchestration doesn’t stop at routing—Foundry carries the same intelligence into agents. Coming soon, GPT-5 will be available in the Foundry Agent Service, pairing frontier models with built-in tools including new browser automation and Model Context Protocol (MCP) integrations. The result: policy-governed, tool-using agents that can search, act in web apps, and complete end-to-end tasks—instrumented with Foundry telemetry and aligned to Microsoft Responsible AI.

Accelerating business impact with GPT-5

These capabilities map directly to business impact.

In research and knowledge work, GPT-5 accelerates financial and legal analysis, market intelligence, and due diligence—reading at scale and producing decision-ready output with traceability. In operations and decisioning, it strengthens logistics support, risk assessment, and claims processing by pairing robust reasoning with policy adherence. Copilots and customer experience teams benefit from multi-turn, multimodal agents that reason in real time, call tools, resolve tasks, and revert to humans with more helpful context.

In software engineering, GPT-5 excels at code generation, application modernization, and quality engineering—improving code style and explanations to compress review cycles.

And for use cases which are cost or latency sensitive, GPT-5-nano’s ultra‑low‑latency architecture delivers rapid, high‑accuracy responses, making it the ideal target for fine‑tuning and the go‑to model for high‑volume, straightforward requests.

GPT-5 customer spotlight

Customers are unleashing GPT-5 across complex, mission-critical workloads—accelerating decision-making, supercharging coding, and catalyzing product innovation.

SAP

SAP is excited to be among the first to leverage the power of GPT-5 in Azure AI Foundry within our generative AI hub in AI Foundation. GPT-5 in Azure AI Foundry will enable our product team and our developer community to deliver impactful business innovations to our customers.

—Dr. Walter Sun, SVP and Global Head of AI, SAP SE

Relativity

The GPT-5 in Azure AI Foundry raises the bar for putting legal data intelligence into action… This next-generation AI will empower legal teams to uncover deeper insights, accelerate decision-making, and drive stronger strategies across the entire legal process.

—Dr. Aron Ahmadia, Senior Director, Applied Science, Relativity

Hebbia

The partnership between Hebbia and Azure AI Foundry gives financial professionals an unprecedented edge. With GPT-5’s advanced reasoning in Hebbia, they can pinpoint critical figures across thousands of documents and structuring complex financial analysis with speed and accuracy.

—Danny Wheller, VP of Business and Strategy

Building with AI in GitHub Copilot and Visual Studio Code

GPT-5 begins rolling out today to millions of developers using GitHub Copilot and Visual Studio Code, applying the flagship model’s advanced reasoning capabilities to increasingly complex problems—from sophisticated refactoring to navigating large codebases more effectively. GPT-5 helps developers write, test, and deploy code faster, while supporting agentic coding tasks with significant improvements to coding style and overall code quality. With GPT-5, developers not only code faster, but code better.

With today’s VS Code release, developers also gain a more powerful agentic coding experience directly within the editor: GitHub Copilot’s coding agent has an improved experience for autonomously tackling tasks in the background. Additionally, the GitHub Copilot chat experience brings increased productivity, including support beyond 128 tools for a single chat request and chat checkpoints allowing users to restore workspace changes to a prior point. Today, we are also announcing an updated extension to develop agents using the Azure AI Foundry extension all within VS Code environment.

These announcements extend Microsoft’s strategy to transform software development with AI, bringing advanced AI capabilities to the entire software lifecycle.

Security, safety, and governance by design

In all domains, security and safety is a layer cake of protections, which together provide protection for risk scenarios—and AI is no different. For AI, we think about layers with the model as the core. With GPT-5, the core is safer than before:

The Microsoft AI Red Team found GPT-5 to have one of the strongest safety profiles of any OpenAI model, performing on par with—or better than—o3.

—Dr. Sarah Bird, Chief Product Officer of Responsible AI, Microsoft

As we think about the safety, security, and governance layers around this core—Azure AI Foundry provides a number of additional controls:

• Azure AI Content Safety protections are applied to every prompt and completion, such as prompt shields, which help to detect and mitigate prompt-injection attempts before they reach the model.

• Finally, security signals integrate directly with Microsoft Defender for Cloud, and runtime metadata and evaluation results are integrated to Microsoft Purview for audit, data-loss prevention, and regulatory reporting, extending protection and governance across the entire GPT-5 lifecycle.

Bringing AI into every workflow with GitHub Copilot and Visual Studio Code

Starting today, GPT-5 begins rolling out to millions of developers who use GitHub Copilot and Visual Studio Code who will be able to select GPT-5 to write, test, and deploy code—and develop agents using the Azure AI Foundry extension all within VS Code environment. GPT-5 supports complex agentic coding tasks with significant improvements to coding personality, front-end aesthetics, and code quality, highly desired improvements for the developer community.

Our evaluations show OpenAI GPT-5’s reasoning capabilities and contextual awareness exceed o3, enabling developers to tackle more complex problems—from refactoring to navigating large codebases. With GPT-5, users in the Visual Studio family can not only code faster, but code better.

VS Code and our recent decision to open-source GitHub Copilot, represents our commitment to open tools and standards and demonstrates our ability to meet the rapid pace of model innovations while keeping the developer experience at the forefront. In today’s release of VS Code, developers can. In today’s VS Code release, developers have even more control over their experience in chat—with improvements to the reliability of terminal tools, updates to the tool picker and limits, new checkpoints, and more.

Today’s announcement extends Microsoft’s strategy to transform software development with AI, bringing advanced AI capabilities to the entire software lifecycle.

Start building today

GPT-5 is available via our Standard offering in Azure AI Foundry, with deployment choices optimized for cost-efficiency and governance needs, including Global and Data Zone (United States, European Union) deployment options for data residency and compliance.¹

With Azure AI Foundry’s first-class reliability, realtime evaluations, built-in observability, and secure deployment options, you can confidently move from pilot to production—all aided while unique tools like Model Router optimizes quality, latency, and cost across workloads.

---

¹Pricing is accurate as of August 2025

The post GPT-5 in Azure AI Foundry: The future of AI apps and agents starts here appeared first on Microsoft Azure Blog.

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Steve Klabnik wasn't a fan of AI. He knows how to code at high and low levels...but then he tried again. Now he's making more, shipping more, coding more, and having more fun. Is this a moral choice or a techincal one or both? 

Download audio: https://r.zen.ai/r/cdn.simplecast.com/audio/24832310-78fe-4898-91be-6db33696c4ba/episodes/b4a689eb-62c4-4010-9827-351ba261b828/audio/d7798615-5bd2-4011-b9f7-baaadbb42bdc/default_tc.mp3?aid=rss_feed&feed=gvtxUiIf

OpenAI officially launched its new GPT-5 models today, and Microsoft is now bringing GPT-5 to Copilot, Microsoft 365 Copilot, Azure AI Foundry, GitHub Copilot, and more. It’s part of a big simultaneous release of GPT-5 that will show up in Copilot as the new smart mode that I detailed in Notepad last month.

The new smart mode in Copilot allows the AI assistant to switch models for you to use deeper reasoning or quickly respond based on the task. Much like how OpenAI is making GPT-5 available to free users of ChatGPT, Copilot will also have free access to GPT-5.

Microsoft 365 Copilot users will also get access to GPT-5 today. “With GPT-5, Microsoft 365 Copilot is better at reasoning through complex questions, staying on track in longer conversations and understanding the user’s context,” explains Microsoft in a blog post. Copilot Studio will also get access to GPT-5 as part of today’s releases.

GitHub is also bringing GPT-5 to all paid GitHub Copilot plans today, allowing developers to try out the code writing improvements to OpenAI’s latest model. OpenAI’s new GPT-5 model comes in four different versions, and has big improvements in reasoning and code quality. GPT-5 is designed for logic and multi-step tasks, while GPT-5-chat is tuned for enterprise applications with multimodal context-aware conversations.

Finally, Microsoft is also making GPT-5 available through Azure AI Foundry, so developers can utilize it in AI-powered apps. Developers will be able to use the model router in Azure AI Foundry “to ensure the right model is used” for the task or query.

The third part of this five-part series on stopping prompt injection attacks describes how an attacker can use prompt injection exploits to reveal hidden database structure.