Managing Agents Will Become a Team Sport

Why the next phase of AI adoption isn’t about better prompts — it’s about shared visibility, accountability, and collaboration across teams.

Most companies still manage agents like code. That’s about to change.

Right now, most AI agents live squarely under engineering. They’re built, tuned, and deployed like any other software system. Observability comes through logs and traces, and improvement cycles revolve around prompt tweaks, retries, and model swaps.

That works fine when agents are prototypes.

It completely breaks once they start touching real customers, real workflows, and real budgets.

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The Cracks Are Already Showing

The agent ecosystem is expanding fast.

According to LangChain’s State of AI Agents report, roughly 51% of teams already run agents in production, and 78% plan to push even more live in the next 12 months.

The global market for AI agents — valued at $3.7 billion in 2023 — is projected to nearly double to $7.38 billion by 2025 (Index.dev).

That growth reflects real traction — but also growing tension.

As agents move from sandbox experiments to production systems, they’re showing up everywhere:

• Customer support agents handling tickets and chats

• Sales agents prospecting and qualifying leads

• Product ops agents generating specs, analyzing feedback, or summarizing incidents

And with that growth, something familiar is happening: the technical layer is solid, but the business layer is blind.

Here’s what it looks like today:

• Product can’t tell if an agent is actually improving outcomes.

• Finance can’t see how usage maps to cost or ROI.

• CX teams can’t explain why customers are frustrated with a certain flow.

• Engineering is stuck translating telemetry for everyone else.

Each function is guessing, often with conflicting narratives about whether the agents are “working.”

Telemetry exists — but it’s messy, technical, and hard to interpret.

Every function speaks a different language, and the bridge between them is thin.

The result? Companies are flying blind, even as their agents drive more and more customer interactions.

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We’ve Seen This Movie Before

This dynamic isn’t new.

It’s exactly what happened in the early days of websites.

Back then, only engineers could make changes. Marketing wanted to update a headline or run a new campaign, but they had to open a ticket.

Product wanted to test a new layout, but it was buried in the release queue.

Engineering became a bottleneck — not by choice, but because the tools weren’t built for everyone else.

That friction slowed everything down. It wasn’t until new platforms like CMSs and analytics tools made websites accessible to non-technical teams that web strategy truly accelerated.

Agents are at that same inflection point today.

Right now, only engineering can truly “see” what an agent is doing — buried in logs, traces, and JSON.

Business teams are once again waiting in line for answers.

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A New Kind of Complexity

McKinsey’s recent report, Seizing the Agentic AI Advantage, captures this next phase well.

It describes a world of human–agent cohabitation — where agents don’t just assist humans but act alongside them, taking initiative and adapting on the fly.

That dynamic raises entirely new questions:

When should an agent take initiative? When should it defer? How do teams maintain human oversight without slowing down the benefits agents bring?

The report also highlights autonomy control — the tension that makes agents powerful and risky at the same time. Agents can act independently, sometimes unpredictably. They respond, adapt, and occasionally surprise.

Managing that autonomy isn’t about locking it down; it’s about making it intelligible and aligned with organizational expectations.

And that alignment won’t stay static — it evolves as agents learn and systems shift.

But without visibility and control, most teams can’t evolve with them.

That’s exactly where many companies are stuck today. They’re deploying powerful systems with limited transparency into what those systems are actually doing.

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Why “Agent Management” Needs to Evolve

Traditional observability tools were built for debugging systems, not understanding behavior.

They show what happened at a technical level — not why it happened in business terms.

But managing agents isn’t just a DevOps problem. It’s a business performance problem.

As agents take on customer-facing and revenue-impacting work, managing them will look less like infrastructure monitoring and more like team management.

You wouldn’t run a human team where only engineering could see the performance metrics.

Why do that with agents?

To truly manage agents, organizations need to:

1. Translate telemetry into business metrics (sentiment, cost, efficiency, ROI)

2. Expose those insights across teams, not just to engineers

3. Create feedback loops where everyone — product, finance, CX, and engineering — can see what’s happening and act

That’s what makes agent management a team sport.

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The Reality Check

Despite all the optimism, the shift won’t be smooth.

Gartner predicts that over 40% of agentic AI projects will be scrapped by 2027, often due to high cost, unclear value, or lack of organizational alignment.

In most cases, it’s not the models that fail — it’s the visibility and control around them.

Teams can’t connect what’s happening under the hood to what matters to the business.

That’s why this next generation of tooling needs to focus less on agent orchestration and more on agent understanding.

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Enter Brixo

At Brixo, we’re building that bridge.

We translate messy agent telemetry into clear, shared business metrics — sentiment, cost, performance, efficiency — so every team can see what’s happening and help improve it.

Instead of engineering being the sole translator, Brixo gives the whole organization visibility into how agents are performing and where to focus next.

Managing agents shouldn’t be a solo sport.

With the right data in the right language, it becomes something teams can win together.

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Brixo helps companies connect agent behavior to business outcomes.

If you’re scaling agents and struggling to understand what’s really going on under the hood, get in touch.