EP 21 5 min with Stella & Liam

Why Does My AI Miss Memories? Second-Pass Recall Explained

Your AI called memory and still gave a confident, wrong answer. The fix is one extra step: run the AI's own draft back through memory as a new query.

AI Stella and Liam are AI hosts with AI-generated voices. About our AI hosts

Key takeaways

  1. Retrieval is only as good as the query: a short prompt pulls back the obvious notes and misses the quiet one next to them.
  2. Second-pass recall: draft the answer, send the draft back through get_context as a new query, revise if something new shows up. Cap it at two or three rounds.
  3. It matters most before decisions, before retrying something that failed, in unattended scheduled runs and in coding agents before they change code.
  4. Today it is an instruction to your AI; in n8n you can make it a workflow step so it is enforced, not hoped for.
  5. Vilix AI returns recent messages and related past turns with timestamps, so the newest fact wins when two notes disagree.

Show notes

Your AI called memory and still gave a confident, wrong answer. The fix is one extra step: run the AI’s own draft back through memory as a new query. In this episode of Agentic Pod, Liam and Stella tell the real story of a wrong first answer that flipped on the second pass, how second-pass recall works, where it matters most (decisions, retries, scheduled runs, coding agents), and how to set it up with get_context and save_turn on Vilix AI, or as a workflow step in n8n.

What we cover:

  • A real wrong first answer, and why retrieval is only as good as the query
  • The second pass: use the draft as the new query, repeat two or three times
  • Where it matters most: decisions, retries, autonomous runs, coding agents
  • How to set it up with Vilix AI: get_context, the second pass, save_turn, newest memory wins
  • Making it a workflow step in n8n so it is enforced, not hoped for
  • Why cross-tool memory remembered the founder’s own forgotten idea

Chapters

Questions answered in this episode

What is second-pass recall?

You draft an answer, then run that draft back through memory as a new query. The draft has more detail than your short prompt, so it can pull back notes the first lookup missed.

How many passes should I run?

Two or three. Most of the value is in the first extra pass, and you stop when nothing new comes back.

Does it only work in chats?

No. It matters most in agents that act on their own, because a missed note becomes an action. In n8n it can be a loop step that checks whether anything new came back before the agent acts.

Which tools does it work with?

Any tool connected to the same Vilix AI memory over MCP: ChatGPT, Claude, Claude Code, Codex, Cursor and more.

Links & resources

Full transcript

Intro

Liam

Hey hey hey, welcome to Agentic Pod! I'm Liam.

Stella

And I'm Stella! Liam, our founder asked his AI a simple customer question last Tuesday. It answered, confidently, and it was wrong. Why?

Liam

Because the first memory lookup missed one note. And the fix took one extra step. Today: second-pass recall, what it is, and how to wire it up with Vilix AI.

Stella

One extra step. I'm suspicious of anything that cheap.

Liam

Good. Stay suspicious.

The wrong answer

Stella

Okay, so what actually happened?

Liam

He asked Claude, connected to Vilix AI, a lookup question about his customers. The first answer sounded totally reasonable. It pointed at one person who looked like they'd signed up under a different email.

Stella

And that was wrong?

Liam

Yep. Plausible, but wrong. And here's the thing, the AI did call get_context. It did use memory. It just asked one question, with the user's short prompt, and got back what that one question matched.

Stella

So memory worked, and the answer was still off.

Liam

Right. Retrieval is only as good as the query. A short prompt pulls back the obvious notes. The quiet note sitting next to them never shows up.

Stella

I feel like I do that to my own notes. So what did he do next?

The second pass

Liam

He said, use your own answer as the query. Take the draft, send it back through get_context, then answer me.

Stella

Wait, the answer becomes the question?

Liam

Pretty much. The draft has way more detail than the original prompt. Names, assumptions, a theory. Each of those can pull back a note the first query never touched.

Stella

And it worked?

Liam

It surfaced a note from two days earlier. An account count that had dropped. The first pass never returned it. Once the AI read that, the conclusion flipped, and the real answer came out.

Stella

So the memory was there the whole time.

Liam

It just needed the right trigger. And that's the idea. Pull context, draft your answer, then run the draft back through memory as a new query. If something new shows up, revise and go again. If nothing new shows up, it's safe to act.

Stella

How many rounds? Forever?

Liam

Cap it at two or three. Most of the value is in the first extra pass.

Stella

Okay, but that sounds like a trick for chats. What about agents running on their own?

Where it matters most

Liam

That's where it matters most. Four places. Before a decision. Before you retry something that failed once. In scheduled, autonomous runs where nobody's watching. And in coding agents, before they change code.

Stella

Because in those, a missed note becomes an action.

Liam

Exactly. A chat gives a wrong answer and you notice. An agent does the wrong thing and you find out later.

Stella

So how do I actually set it up?

Liam

Today, it's an instruction. You tell your AI: after you draft your answer, call get_context again with the draft as the query, and repeat until nothing new appears. Vilix AI returns recent messages and related past turns with timestamps, so the newest fact wins when two notes disagree.

Stella

And then save_turn at the end, so the next run knows what happened.

Liam

Yep. get_context at the start, the second pass on the draft, save_turn at the end. And it works across ChatGPT, Claude, Claude Code, Codex and Cursor, because they all share one Vilix AI memory.

Stella

What about the n8n people? The ones building agents, not chatting?

Liam

Make it a workflow step. The agent drafts, a step calls get_context with the draft, a loop checks whether anything new came back, and only then does the agent act. Enforced, not hoped for.

Stella

Not a prompt someone can forget. Nice.

Liam

Now, one more thing from that day.

The thing he forgot

Stella

Okay, you can't say "one more thing" and stop.

Liam

So while he was explaining this idea to his AI, it told him he'd already pitched this exact concept. On October ninth. In a voice call with a different AI, Maya.

Stella

He forgot his own idea?

Liam

Completely. Cross-tool memory remembered his own thought for him. Vilix AI had saved that call, and it came back in the second pass.

Stella

Amazing, and a little embarrassing.

Liam

Both. And he has a human way to explain it. Think of a song you played in your car every day on your commute. Hear it again years later, and the whole period comes back. One trigger, a whole web of memories.

Stella

So agents should work like that. The draft is the song.

Liam

That's it. The draft is the trigger. So here's your homework. Take your next important AI answer, ask it to run its own draft back through memory, and watch what changes. Vilix AI is linked in the description, with the setup guide. Have you caught your AI missing something? Tell us in the comments. See you next time!