AI Agents Are Eating the Developer Stack—Here’s What You Need to Know This Week

TL;DR OpenAI launched AgentKit at Dev Day 2025 and shipped GPT-5 Pro and Sora 2 in the API . GitHub Copilot evolved from a high-powered autocomplete tool to a powerful, multi-model agentic assistant . Azure AI Foundry Agent Service is now generally available, with Multi-Agent Orchestration debuting for connected agents and multi-agent workflows . Meanwhile, Anthropic claims Claude Sonnet 4.5 is “the best coding model in the world,” scoring 77.2% on SWE-bench Verified . The race is on, and your 2025 roadmap needs to account for agentic workflows.

The Big Picture: Agents Are No Longer Experimental

If you shipped code in 2024 using AI as a fancy autocomplete, welcome to a different world. OpenAI is no longer just building AI—it is building the world where AI will live—a world of intelligent apps, autonomous agents, and new physical devices . If 2024 was about showing what’s possible with AI, 2025 is about making it practical . That shift has massive implications for how you architect systems.

GitHub: Your New CI/CD Partner Wears a Copilot Badge

What changed this week: Copilot now takes on cross-file tasks, runs commands, refactors entire modules, and suggests terminal operations—all without leaving your editor. The Coding agent can be assigned an issue and drafts a pull request with code, tests, and context from your project .

More concretely:

- GitHub is delivering suggestions with 20% more accepted and retained characters, 12% higher acceptance rate, 3x higher token-per-second throughput, and a 35% reduction in latency . - Claude Sonnet 4.5, Anthropic’s most advanced model for coding and real-world agents, is now available in public preview in GitHub Copilot CLI . - Most Copilot responses now render in under 400 ms (fast enough that you stop noticing them) .

For .NET teams specifically: The .NET team is addressing context awareness by providing added context to GitHub Copilot for each query, now available in Visual Studio 17.14 and VS Code with C# Dev Kit . When you add the doc comment notation (///) to the top of your class or method, GitHub Copilot will generate the full comment, complete with summary and descriptions for each parameter .

Practical step:
Update your VS Code extensions and enable the Microsoft Learn function in Copilot settings to get better context-aware suggestions for your .NET projects.

Azure: Agent Infrastructure Is Production-Ready

Azure AI Foundry Agent Service is now generally available, helping more companies like JM Family, Fujitsu, and YoungWilliams automate some of the most complex business processes .

Key capabilities rolling out:

- Agentic retrieval is now possible through Azure AI Search, using advanced techniques to improve answer relevance by up to ~40% on complex, multi-part questions in early tests . - Model router in Azure AI Foundry allows developers to automatically select the optimal Azure OpenAI models for different prompts—boosting quality while reducing costs . - The Realtime API (preview) now supports WebRTC, enabling real-time audio streaming and low-latency interactions. This feature is ideal for applications requiring immediate feedback, such as live customer support or interactive voice assistants .

For cost-conscious teams: Azure Developer CLI (azd) now supports layered provisioning to solve complex infrastructure dependency scenarios. This alpha feature lets you define multiple provisioning layers in azure.yaml for sequential or independent deployment .

.NET: Agents Are Now First-Class Citizens

Microsoft isn’t hiding its bet on AI agents for .NET developers. Microsoft has gone all-in on making AI development in .NET easy and powerful. The tooling around LLMs, Microsoft Extensions for AI (now generally available), Semantic Kernel, and AI agents is getting really mature .

What’s shipping:

- Microsoft Agent Framework is an open-source SDK designed to simplify the creation and deployment of artificial intelligence agents. The framework represents a significant consolidation effort, unifying capabilities from Semantic Kernel and AutoGen . - Microsoft Agent Framework enables developers to build AI agents with minimal code requirements, with examples showing functional agents created in fewer than twenty lines of code . - Microsoft has released the A2A .NET SDK, a new developer toolkit that enables building AI agents capable of communicating and collaborating using the Agent2Agent (A2A) protocol. With support for both client and server roles, the SDK allows .NET-based agents to interact with others across ecosystems .

Getting started:

# Install the .NET AI Chat Web App template
dotnet new install Microsoft.Extensions.AI.Templates

# Create a new AI chat project
dotnet new aichatweb -n MyAIAgent

The update introduces .NET Aspire Orchestration, which facilitates powerful integrations with both local and cloud-based AI models, enabling the creation of cloud-native applications with this template .

The Model Wars Heat Up (And Your Wallet Notices)

Anthropic’s play: Claude Haiku 4.5 is billed as offering similar performance to Sonnet 4 “at one-third the cost and more than twice the speed” . Anthropic is making Haiku 4.5 available for all free users of its Claude.ai platform, effectively democratizing access to what the company characterizes as “near-frontier-level intelligence” .

OpenAI’s response: OpenAI introduced new tooling for agents, AgentKit, and shipped fresh model options, GPT-5 Pro and Sora 2 in the API . With a preview of the Apps SDK, third-party software can render interactive UI directly in the chat and share context through the Model Context Protocol .

What this means for you:
Model pricing and performance are shifting monthly, not annually. The rapid pace of model improvements—with new versions launching monthly rather than annually—provides organizations with expanding AI capabilities while vendors compete aggressively for their business .

Heads Up: Model Deprecations Incoming

Selected Claude, OpenAI, and Gemini models were deprecated across all GitHub Copilot experiences on October 23, 2025 . If your team has hardcoded model IDs, now’s the time to audit and switch to the latest stable versions.

2025 Readiness Checklist

  • Audit your AI integrations. Are you still using deprecated models? Update your .env files and CI/CD pipelines.
  • Plan for agents, not just completions. Single-turn chat is yesterday’s architecture. Invest time in agentic workflows—GitHub Copilot agents, Azure AI Foundry agents, or Semantic Kernel orchestration.
  • Lock in cost controls. Model router lets you automatically select the cheapest model that meets quality thresholds . Use it.
  • Embrace multi-model strategies.