Does GetResponse Remember Between Runs?

No. A GetResponse workflow holds no memory of its own between runs. When a contact enters a workflow, that workflow reads the contact exactly as the record stands at that moment: the tags currently assigned, the custom fields currently stored, and the score currently on the contact. Anything an earlier run worked out survives only if that run wrote it back first, as a tag, a custom field update, or a score a later condition can check.

That distinction is easy to miss because GetResponse feels continuous. Contacts, tags, and workflows are all still there tomorrow. The continuity lives in stored records and workflow definitions, not in a memory one run hands to the next.

What does a GetResponse contact actually hold?

GetResponse stores several different kinds of data about a contact, and the split matters. Custom fields are current state: the values the account currently believes about someone, such as a name, a plan, a signup source, or a preference. A form, an import, an API call, or a workflow action sets a custom field, and a later write replaces the earlier value. The contact card shows the latest value, not the history of values.

Tags work differently. A tag is a label assigned to a contact, such as a product interest, a customer status, or a workflow name used to mark who started or finished a workflow. Tags accumulate until they are removed, and conditions, segments, and workflow filters can all check whether a contact carries a tag right now. A tag records that a label applies. It does not record why it was applied, what was checked before it was added, or what an earlier run decided and then set aside.

Scores add a third kind. A workflow can add or subtract points, and conditions can branch on the score reached. Engagement scoring adds a separate 1 to 5 read of email interaction. A number can trigger the next step. It cannot explain how it was earned or what a previous run learned along the way.

What happens inside one workflow run?

Inside a single workflow, the path is clear. A starting condition admits a contact, actions such as Send message, Tag, Score, Copy, Move, or Remove act on that contact, and conditions such as Tag assigned, Custom field changed, or Score given branch the path based on the stored record. Wait elements hold the contact, and the workflow resumes that contact at the right element when the wait ends.

That resume is workflow progress, not run memory. Once the contact exits or completes, the workflow keeps no working notes from that journey. The next entry starts from the contact record and the workflow definition, nothing else.

A second workflow sees even less. Workflows do not share working state with each other. A workflow can only react to what a previous workflow left on the contact: a tag it assigned, a field it changed, a list it moved the contact to, or a score it adjusted. If the earlier workflow never wrote its conclusion to the contact, the later workflow has no way to recover it.

Where the gap shows up for scheduled and AI work

The gap stays hidden in simple welcome and abandoned cart flows, because those flows only need current state. It appears when a scheduled agent or an AI step is added next to GetResponse and the work starts to depend on reasoning, not just records.

Consider a weekly re-engagement job. An agent reviews quiet contacts, decides who gets a new angle and who should be left alone, and prepares the next send. Next week GetResponse can show the tags, fields, and scores written back. It cannot show why a contact was skipped, which angle was already tried and rejected, or what was planned next. Unless that reasoning was forced into a tag or a field, the next run can repeat a decision that was already discarded.

The same pattern appears in lead qualification and onboarding sequences that span several workflows. The record answers what is true now. The work also needs what was tried, what was decided, and what was promised, and none of that lives in a tag, a field, or a score. Forcing it into fields makes fields multiply and values get overwritten, so only the latest conclusion survives.

The missing layer is shared agent memory

The fix is not another tag or another custom field. The fix is a memory layer that sits next to GetResponse and holds the full context of the work, so a scheduled run or an agent can read what happened before it acts again.

Vilix AI is that layer. Vilix AI is cloud-hosted with zero infrastructure to run, so there is no database to provision, no server to maintain, and no storage layer to wire into every workflow before memory starts working.

The same memory is available everywhere over MCP. A workflow in GetResponse, a scheduled agent, and a chat tool can all read and write the same Vilix AI memory, so context created in one place is present in the next place the work runs. The memory follows the work, not one tool.

Vilix AI also stores full conversation history, not just facts. That matters for the re-engagement example. A later run can revisit the actual earlier conversation and reasoning: which contacts were reviewed, which angle was chosen, which one was rejected and why, and what the next step was meant to be. A tag can only say that something happened. Full history shows what actually happened.

Access stays simple. There is a free plan forever, and a 7-day Pro trial with no credit card, so a memory layer can be tested against a real workflow before any commitment. Data stays portable as well: everything can be exported or deleted anytime, so the memory built up around GetResponse work remains under the account owner's control.

Watch: Liam and Stella break this down on Agentic Pod, with the full technical guide on GitHub.

A practical way to combine the two

Keep GetResponse doing what GetResponse does well: storing contacts, holding tags, fields, and scores, and running the workflow elements that send and branch. Add Vilix AI for the part the contact record was never built to hold: the reasoning across runs.

Each time a job finishes a pass, it saves a short record to Vilix AI: who was reviewed, what was decided, what was sent, and what should happen next. At the start of the next pass, it reads that memory first, then checks the current GetResponse record. Current state comes from GetResponse. Continuity comes from Vilix AI.

That split answers the original question cleanly. GetResponse remembers the contact: the latest field values, the tags, and the score. It does not remember the work between runs. With Vilix AI holding the full history next to it, the next run no longer starts blind, and no decision has to be made twice because the reason for the first one was never stored.

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