I’ve been following the agentic development space around Claude Code and similar tools and the last couple months have been interesting. Here’s what I’m seeing as we move through March and April 2026.

From Solo Agents to Coordinated Teams

The biggest shift is that more people are moving away from trying to build one agent that does everything. Instead, we’re seeing coordinated teams of specialized agents managed by an orchestrator, often running tasks in parallel. I think this is the more proper use of these systems, and it’s great to see the community arriving here.

If you’re curious about the different levels of working with agentic software development, I created an agentic maturity model on GitHub that goes into more detail on this progression.

Long-Running Autonomous Workflows

Early on, agents handled what were essentially one-shot tasks. Now in 2026, agents can be configured to work for days at a time, requiring only strategic oversight at key decision points. Doesn’t that sound fun? You’re still the bottleneck, but at least now you’re a strategic bottleneck.

Graph-Based Orchestration

Frameworks like LangGraph and AutoGen are converging on graph-based state management to handle the complex logic of multi-agent workflows. I think this makes sense when you consider the branching and conditional logic of real-world tasks could map naturally to graphs.

MCP Is Everywhere

MCP (Model Context Protocol) has become the industry standard for tool integration. All vendors fully support it, and there’s no sign of slowing down. Every week there are new MCP servers popping up for connecting agents to different services and tools.

Unified Agentic Stacks

The developer tooling is becoming more consistent. Cursor is becoming more like Claude Code, and Codex is becoming more like Claude Code. Maybe you see a pattern there… might tell you something about who’s setting the pace.

What is also noteable, people are experimenting with using different tools for different parts of the workflow. You might use Cursor to build the interface, Claude Code for the reasoning and main logic, and Codex for specific isolated tasks. Mix and match based on strengths.

Scheduled Agents and Routines

Claude Code recently released routines or scheduled or trigger-based automations that can run 24/7 on cloud infrastructure without needing your laptop. Microsoft with GitHub Copilot are working on similar capabilities? Cursor had something like this a while back too.

Security Gets Serious

Two things happening here. First, people are getting better at leveraging agents for security reviews and monitoring. Tasks that previously required highly specialized InfoSec expertise. You no longer need to be a hacker to find vulnerabilities; you can let your AI try to hack you.

However, the same capabilities that harden defenses can also be used for offensive attacks. We’re seeing a major push for security-first architecture as a requirement for all new applications, specifically to defend against the rise of agentic offensive attacks. Red team and blue team are both getting AI-pilled.

FinOps: Watching the Bill

Last on the list is financial operations. Inference costs now account for over half of AI cloud spending according to recent estimates. Organizations are prioritizing frameworks that offer explicit cost monitoring and cost-per-task alerts. Getting granular about how much you’re spending to solve specific problems and optimizing at the task level. I think that’s pretty interesting and something we’ll see a lot more tooling around.

The common thread across all of these trends is maturity. We’re past the “wow, an AI wrote code” phase and into “how do we make this reliable, secure, and cost-effective at scale.” That’s a good place to be.