Agentic Software Development: The Hard Part Is Leadership

Agentic software development isn’t science fiction. It’s already reshaping how teams build, test, and ship software. Autonomous agents generate boilerplate, suggest architecture, write tests, and even push code. Throughput is up.

However, for engineering leaders, the real challenge isn’t the tools, but rather transformation. Not just “can we use AI,” but how do we re-architect our systems and teams to support agentic velocity safely and strategically?

This post is for engineering leaders navigating that shift. Those who know that real leadership is about change management. And that agentic development might be the biggest change of all time.

We’ll cover:

• What agentic development actually means
• The technical architecture decisions that support it
• The cultural mindset shift it demands
• Why runtime control is the foundation that lets you lead both

What Is Agentic Software Development?

Agentic Software Development refers to a mode of building software where autonomous agents work alongside humans throughout the Software Development Life Cycle (SDLC), from design and implementation to release and monitoring.

This framing echoes what Microsoft CTO Kevin Scott described at Build 2025: the agentic web,an open, modular system composed of reasoning engines, memory layers, multi-agent protocols like MCP, and runtime execution environments.

In this context, agents are more than copilots. They’re autonomous collaborators, delegated actors that take input, make decisions, and ship change. That delegation introduces speed. But without the right foundation, it also introduces risk.

Strategic Considerations: What You Can (and Should) Control

The really hard part about agentic software development isn’t the agents, it’s the humans.
But let’s start with what’s easier to shape: architecture, systems, and control layers.

How Modular Should Your Architecture Be?

Composable architecture is a strategic choice, not a universal law. For large-scale organizations, modular systems — where each SDLC stage is owned by decoupled tools or services — create flexibility and resilience. They support:

• Independent agent integration
• Faster iteration without global impact
• Easier tool/vendor substitution
• Less risk of lock-in

However, composability comes with trade-offs: increased complexity, higher integration overhead, and more systems to coordinate. For smaller orgs, tightly coupled “one-stop-shop” platforms may be more pragmatic.

What’s important is that leaders evaluate the level of modularity their org actually needs to enable agentic workflows without overwhelming coordination cost.

Are You Ready to Think in Terms of Organizational Observability?

Fullstack observability is more than just metrics, it’s about aligning decision-making across functions.

In an agentic SDLC, the question isn’t just “Did the deployment succeed?” It’s: “Is this change better: for users, for the business, and for the system?”

That means bringing together three traditionally separate perspectives:

• The Voice of Engineering (latency, reliability, cost)
• The Voice of the Business (revenue, conversion)
• The Voice of the Customer (feedback, NPS, support load)

The strategic shift is not just capturing these signals but creating a culture where teams share accountability for them. For small changes, that may mean developers learning to think in terms of all three voices. For larger initiatives, it could mean new cross-functional processes entirely.

Have You Defined Runtime Control and Delegation Boundaries?

Agents don’t second-guess. They don’t tap a colleague on the shoulder to double-check logic. That’s why runtime control becomes essential infrastructure, not just an ops convenience.

At the leadership level, this isn’t about managing access yourself. It’s about ensuring the right guardrails are defined, delegated, and enforced.

Questions to consider:

• What types of changes are agents allowed to propose or ship?
• What approval workflows are required based on impact or scope?
• Who owns oversight, and what is logged, reviewed, or alerted on?

This is the foundation for safe agent autonomy, and it’s a discussion that needs to happen before agent output hits production.

Are You Investing in Feature Flags as a Runtime Control Mechanism?

At the center of this execution environment is the feature flag system.

Feature flags are not just deployment tools. In the context of agentic systems, they become:

• A way to separate delivery from exposure
• A mechanism for fine-grained rollout and rollback
• A kill switch for hallucinated or unstable behavior
• A programmable surface for agents to modify functionality within bounds

If you’re going to delegate autonomy, you need runtime control primitives that allow safe iteration. Feature flags are how you do that.

Cultural Shifts: The Hard Part You Can’t Skip

You can’t re-architect your teams like you re-architect your systems. Culture isn’t modular. Change must be led.

You won’t get it right all at once. And you shouldn’t try.  Start small. Learn fast. Scale what works. Fail openly so others can learn, too.

Who Owns What in a Multi-Agent World?

When an agent pushes a change that breaks something, who is accountable?

Engineering leaders must define:

• What level of oversight is needed for different types of agent behavior
• How accountability is shared between human and machine contributors
• How escalation works when things go wrong

Clear accountability isn’t just a management requirement; it’s a precondition for safe delegation.

How Will Roles and Teams Evolve?

Agents won’t eliminate roles, they will reshape them.

Manual testing may give way to runtime instrumentation. Infrastructure engineering may shift toward behavioral tuning. Developers may take on agent configuration and review.

It’s up to leadership to:

• Anticipate which skills are becoming more strategic
• Invest in retraining and growth paths
• Celebrate the new value being created

Are You Leading the Change from the Front?

This transformation won’t succeed by decree. It needs visible, credible leadership.

That means:

• Running a small pilot
• Trying the tooling yourself
• Celebrating early adopters
• Sharing learnings. Even when they’re messy

The goal isn’t perfection. It’s momentum.

Are Human Guardrails Built Into the Process?

Agents move fast. However, not every change should be implemented immediately.

You need intentional stop-points based on:

• Change size or scope
• User impact
• Confidence thresholds from metrics

This is where Controlled Feature Releases matter. Let systems ship continuously but expose changes when the context is right.

Are You Planning for Hallucinations?

Even good agents hallucinate. You won’t catch everything in code review.

Build for resilience:

• Protect every critical path with flags
• Make rollbacks instant and isolated
• Monitor for behavioral anomalies, not just failures

The June 2025 Google Cloud outage is a perfect example: 

It wasn’t just a coding bug. It was a missing flag. A malformed policy change triggered a null pointer exception in Google’s Service Control infrastructure. The impact? Catastrophic.

Ninety-five Google services were affected, including Gmail, Google Meet, and GCP Identity and Access. Customers like Cloudflare, OpenAI, and Shopify experienced cascading disruptions.

Google’s postmortem was blunt: “If this had been flag-protected, the issue would have been caught in staging.”

As a leader, your job is to build safety into velocity. That starts with runtime controls.

Final Word: What You Build Today Enables What You Change Tomorrow

You can’t solve culture with tooling. But you can’t tackle culture without runtime safety nets, either.

Composable architecture, full-stack observability, runtime control, and feature flags give you the infrastructure for learning and resilience. They don’t just support agents. They give humans the confidence to evolve. Because in this shift, the hardest part isn’t the agents. It’s us.

Ready to start applying these patterns in your own org? Get started with Unleash or talk to our team about what it looks like to adopt agentic software development at scale.