Port vs Guild: Governance for Software Factories, Not Just Agent Workflows

Key takeaways

• Guild governs agents. It gives every agent an identity, scopes its credentials, records what it did, and tracks what it cost, across any framework or model.
• A software factory governs more than agents. It governs the services agents change, the teams that own them, the standards every change meets, and the human and deterministic work agents never touch.
• The split is structural. Guild governs each agent, Port governs the service each agent changes. Think of it as a badge system versus a blueprint: both can list the workers, only the blueprint maps the site they work on..
• Guild’s Software Factory ships bounded coding work to a reviewed PR. Scaling across teams is harder, because the bottleneck shifts from writing code to coordinating owners, standards, and non-coding work across the estate.
• Most orgs run both. Guild governs the agent runtime, and Port governs the factory the agents run inside.

Governing your agents is not the same as governing your software factory. Guild (guild.ai) is an agent control plane, and a good one: it runs, secures, and tracks the AI agents your teams ship to production. This guide is for platform and engineering leaders weighing AI agent governance across the SDLC, and it shows where that control plane ends, and the factory begins.

What Guild is Built to Do

Guild is an agent control plane: a vendor-neutral layer that runs, governs, and observes AI agents in production, whatever framework or model built them. Founded in 2025, it gives each agent an identity, injects credentials at runtime, records every action, and tracks cost per agent.

Agents reach Guild through its Bring Your Own Agent model. A team writes an agent in TypeScript, LangGraph, CrewAI, or anything else, and Guild runs it behind one gateway where credentials resolve at runtime and never sit in agent code. Around that runtime sit a Managed Agent Center for versioning and reuse, a public Agent Hub for sharing, a CLI, and token monitoring.

The work its agents take on shows most clearly in Guild’s Software Factory. Add a label to a scoped GitHub, GitLab, or Jira issue, and a planning agent reads it, an implementation agent writes the code in a sandbox and runs your checks, and a separate review agent checks the result before a human approves the merge. Supporting agents handle conflicts, stale jobs, code health, and test triage. The scope is deliberately bounded: well-defined coding tasks that end in a reviewed pull request, not open-ended or cross-team work.

What Guild Handles Well

For running heterogeneous agents safely at scale, Guild is strong, and that is its home turf. It gives every agent an identity, scopes what it can reach, mediates its credentials, records every run, and reports its cost, so you can see and control the agents in production. On its own codebase, Guild reports that 75% of Factory pull requests merge, 91% need no engineer commits, and the Factory writes 56% of all code fixes at Guild. If your problem is running agents safely and shipping bounded coding work fast, Guild answers it.

Governing Agent Workflows is Not the Same as Governing a Software Factory

Guild governs the agent and its run. A software factory governs the work those agents do within your estate, and that is a wider job. The gap shows up the morning after an agent ships something. Picture three moments any team feels while pushing AI into the AI SDLC:

• An agent merged a change overnight, and you are working out which service it touched, who owns it, and whether it met that service’s standard.
• Your agents run under guardrails, but an engineer can still push the same risky change by hand, so only half the changes hitting your estate pass through any policy at all.
• You can see how much your agents shipped and what it cost, but not whether changes started failing or deploys got slower as their output climbed.

Each one is a number you track: how much of your merged work traces to an owner and a standard, how much of all change, agent and human, is governed, and whether change failure rate holds as AI output rises.

Guild closes the agent side of each. What it does not reach is the estate side, because it governs the agent, not the service the agent changed, the team that owns it, or the standard the change had to meet. The overnight-merge question still lands on a person; the by-hand change never passes through the agent layer, and per-agent cost tells you what the agents did, not whether the estate held up as their output rose. Holding up is the practical test: your services stay reliable, changes keep landing cleanly, and delivery speed does not slide as volume rises.

The reason is structural. Guild’s unit of governance is the agent, and a software factory’s unit is the service. Register an agent in Guild, and it knows the agent. Register the same agent in a platform that maps your estate, and it knows the agent and the ground it acts on. Governing the agents is necessary, but it is not the whole factory.

What a Software Factory Covers That an Agent Workflow Does Not

An AI software factory governs five things an agent workflow leaves out:

• The estate. Every service, its dependencies, its incidents, and its owner, kept current from the tools that already hold that data, so any change traces to the ground it touched.
• Ownership. Each service maps to the team accountable for it, so a change routes to a named owner and the record ties the merge to both the actor and the service.
• Standards. A policy checked against live data at the moment of action, so a rule like “no changes to a service with an open incident” blocks the change as it happens instead of catching it in review, and it applies whether an agent or an engineer ships the change.
• The non-agent work. Deploys through an approved pipeline, a change ticket in ServiceNow, a self-service action: the deterministic steps that have to run the same way every time, in the same flow as the agents.
• The people. Service owners, reviewers, security, and the platform team each get a view of the factory, with risker changes routed to the right reviewer, so human judgement lands where it matters without becoming a bottleneck.

Guild governs the agents inside the factory, and those five things are the factory itself.

Port vs Guild, side by side

The table maps the two against each other, capability by capability. Both products register the actors: Port keeps a certified registry of agents, skills, and MCP servers, and Guild’s Agent Hub does the same for its agents and skills. The difference sits a layer below. Port also maps the services, owners, and dependencies those agents act on, in the same graph, which is what separates an agent registry from an agent hub.

The table shows what each does. The harder question is what each should own once both run in the same org.

Where Each One Fits in the Same Organization

Most teams will run both, and the split is clean. Guild owns the agent runtime: it brings any agent, from any framework, under one identity, credential, and cost layer, and its Software Factory ships bounded coding work to a reviewed PR. Port owns the factory around it: the estate the agents act on, the owners accountable for each service, the standards every change meets, the metrics across the SDLC, and the non-agent work. One governs the actors, the other governs the work.

That is why teams build on Port as the platform underneath. dLocal, the payments company clearing more than 500 million transactions a month across 40-plus emerging markets, built an agent called dCoder on Port that takes a ticket to a deployed PR by pulling the services, owners, and patterns it needs straight from Port. Their CTO, Alberto Almeida, says the agent now handles 45% of all their tickets, and Port is where he watches its work and rejection rate. The agent is useful because the factory underneath it knows the ground.

Lead with Guild when one team needs to run agents safely and ship bounded coding work fast. Build on Port when the factory has to scale across many teams, services, and non-coding work under one set of standards, because as factory lines and teams compound on shared context, agents, and standards, the platform underneath decides whether each new line goes live faster or slower than the last. Port is open to try, and you can build your first agentic workflow on the free tier.

Questions to ask during a software factory POC

A handful of questions separate a control plane from a software factory platform in practice. Run them in any POC:

• When an agent merges a change, can the platform tell you which service it touched, who owns it, and which standard it met, without a person looking it up?
• Does the same policy apply to a change an engineer makes by hand, or only to agent actions?
• Can a company-wide rule update reach every factory line at once, or does each line hold its own copy?
• Can a deterministic step, like a deploy through your pipeline or a ServiceNow ticket, run inside the same flow as the agents?
• Can you see whether change failure rate held as AI-authored change rose, not just what the agents did and what they cost?

For a complete checklist, see Port’s guide on how to evaluate a software factory platform during a POC.

FAQ

Is Guild a competitor to Port or a complement?

Mostly a complement. Guild governs the agents, and Port governs the factory those agents run inside: the estate, the owners, the standards, and the non-agent work. Most orgs run both, with Guild as the agent runtime and Port as the platform underneath.

What happens when agents from several vendors run in the same org?

‍You need one place that registers every agent, skill, and MCP server and one policy that applies to all of them. Without a shared registry and actor-neutral governance, each vendor’s agents carry their own identities, permissions, and audit trails, and no one owns the whole picture.

Who is accountable for a change an agent merged?

‍The team that owns the service it changed. That only works if the platform maps ownership to the service, so the change routes to a named owner and the record ties the merge to both the actor and the service. Agent-level logs alone name the agent, not the owner.

Does a factory need its own agent to be useful?

No. The value sits in the governed estate: the catalog, the standards, and the metrics every change runs against. Bring the agents you already run, from any framework or runtime, and let the factory govern what they do. This is the heart of agentic engineering.

How do you compare cost per merged change across tools?

Guild measures cost per merged PR for its Factory agents, which is useful and precise. A factory-level view also counts the cost of human-authored changes and the estate around them, so the number to compare is cost per merged change across every actor, not per agent alone.