Why We Take Routing Decisions Away from the Model

Why do AI agents skip steps? A prompt is a set of instructions the model usually follows, and “usually” is the problem on a payment or an identity check. Conversation Paths move those high-stakes decisions out of the model and into the platform, so a payment cannot run before the caller confirms the amount.

Why does an LLM-based AI agent skip steps?

Most LLM-based AI agents receive their rules as instructions in a prompt. A line such as “do not proceed until the caller confirms the amount” is usually followed. When the model is confused by a caller who changes topic, interrupts, or when the conversation grows long, it can jump past a required gate, act before authorization, or repeat a step it already completed.

Each of these failures is rare. Across millions of calls, rare becomes daily.

What is a Conversation Path?

A Conversation Path is an ordered set of tasks with explicit completion criteria and required gates between them. It is declared in the AI agent’s configuration, so the rules live in the workflow rather than in the prompt. Five components do the work:

• Ordered tasks: the AI agent moves through steps in sequence.
• Completion criteria: each step defines what “done” means, such as a stored and confirmed value or a successful API response.
• Required gates: a step cannot advance until its criteria are met.
• Structural enforcement: the platform blocks a jump to a task that is not yet allowed, whatever the model generates.
• Maintainable configuration: the path is declared once and is readable by everyone who works on the AI agent.

Inside each step, the model still does what it does well: phrasing, follow-up questions, empathy, and callers who give three pieces of information in one sentence. It cannot leave a step before the step is complete, and it cannot return to a step that is finished.

What happens on a payment call?

Take a balance payment on a Conversation Path:

• Collect: the AI agent asks for the amount and stores it.
• Confirm: the AI agent reads the amount back, and the caller accepts, rejects, or corrects it. A correction overwrites the stored value. This behavior, Honor Caller Corrections, now runs on all traffic.
• Gate: the AI agent cannot proceed until an explicit confirmation is stored.
• Execute: the payment runs against the confirmed value.

The path is the same when everything goes to plan. It matters when a caller says “actually, make it two hundred” halfway through the read-back. In a Conversation Path, that correction has exactly one place to go.

What does the caller experience?

The conversation stays natural. Callers speak freely, interrupt, correct themselves, and volunteer information out of order, and the AI agent captures all of it. What becomes enforced is the AI agent’s progress through the steps where a wrong value has a cost. Most steps have no gate at all. Gates are declared where a mistake is expensive, such as:

• Payments
• Authentication
• Dispatch
• Transfers

Which AI agents use Conversation Paths?

Every new AI agent Replicant builds uses Conversation Paths. Existing AI agents are migrated case by case, starting with those that have documented instruction-following issues. Conversation Paths are in beta today, and beta feedback is shaping the broader release.

What is at stake when an AI agent skips a step?

A skipped step can mean a payment posted at the wrong amount, an account accessed before identity is confirmed, or a dispatch sent to the wrong address. Those errors cost money and trust, and sometimes compliance standing. A stronger prompt does not fix them. Replicant enforces the steps that matter in the platform, so the AI agent can be fast and conversational without being trusted to remember every rule. If your AI agents handle payments, authentication, or scheduling, talk to our team about where a Conversation Path would take the guesswork out of your highest-stakes calls.

FAQ

Does determinism make the AI agent sound robotic?
No. Determinism applies to task order and gating, not to language. The model still generates every sentence and handles the unexpected in each step. Callers notice fewer repeated questions, not stiffer ones.

Can an existing AI agent be migrated to Conversation Paths?
Yes, and it is being done case by case, starting with agents that have documented instruction-adherence issues. New AI agents use Conversation Paths from day one.

How is a Conversation Path different from an IVR?
An IVR limits what the caller can say ("press 1 for billing"). A Conversation Path limits what the agent can skip. The caller experience stays conversational; the agent's progress through required steps becomes enforced.

What about steps that are not high-stakes?
Most of a conversation does not need a gate, and most steps do not have one. Gates are declared only where acting on a wrong value has a cost: payments, authentication, dispatch, transfers.