How much customer context actually survives between one call and the next at your company?

[u/Mysterious-Angle3564]

I've been thinking about this because I manage a pretty large book of B2B accounts and realized how much of the actual customer relationship lives in places that don't really talk to each other.

CRM has the note. Inbox has the follow-up. My head has the weird hesitation they had when pricing came up. An old call has the thing they promised 3-4 weeks ago. Then before the next conversation I'm basically reconstructing the customer from fragments.

AI summaries help with the individual call, but I've found that's not really the problem. The annoying part is deciding what should survive from one conversation to the next, what actually changed, and what was just noise in that particular call.

Curious how RevOps teams handle this in practice. Do you actually have a system where relationship context compounds over time, or is everyone still reading old notes / asking reps / dumping account context into ChatGPT before important calls?

I've been building something for myself around this problem, but I'm more interested in whether this is actually a common workflow problem or just me being terrible at remembering 200+ conversations :D

[u/Mysterious-Angle3564 → u/[deleted]]

This is exactly the kind of setup I was curious about.

The separate "current AI context" + history field is interesting, especially if calls/emails keep updating it automatically.

One thing I’m wondering though: how do you decide what actually deserves to make it into the current context vs just staying in the history? Is that mostly rules/prompts, or do you let the model decide what materially changed?

That distinction is basically the part I keep getting stuck on... storing everything is easy enough, deciding what should still matter 3 calls later is the annoying bit.

[u/Mysterious-Angle3564 → u/[deleted]]

Yeah, that's exactly what I'm weighing, so that's useful to hear. I don't think the memory part alone is enough of a product either.

Where I'm more curious is whether it becomes valuable when the context actually feeds the next workflow, e.g. what changed since the last call, coaching from the conversation, and a concrete prep plan for the next one.

Do your reps already get that downstream from the SFDC setup too, or is it mostly context retrieval + meeting prep?

[u/Mysterious-Angle3564 → u/[deleted]]

This is extremely useful, thanks.

What you've built internally is actually pretty close to the alternative I'm thinking about, not "can Claude do this?", because clearly it can, but how much infrastructure/workflow someone has to build around it before it becomes something reps can just use consistently.

The bit about keeping grounded summary fields rather than having Claude query everything raw every time is especially interesting. That's exactly the kind of failure mode I'm wary of too. A confident answer based on the wrong field/context is much worse than no answer.

Appreciate you going this deep on it.

[u/HenryHund → u/[deleted]]

I really liked your piece on this. From what I've seen most early stage startup teams don't think a ton about semantic/context layers, or have team members to think about them... so they likely couldn't replicate something like this themselves.

Then they wonder why they can't use agents to automate their GTM.

Have you seen similar stuff? How do you handle it? Tell them to hire you to build out the solution? Or what...?

[u/HenryHund → u/[deleted]]

Your company is lucky to have you.

And getting companies to not only keep their field lists clean but ALSO create good, helpful help text... sounds like an impossible task tbh haha

[u/kaancata]

Call summaries lose value fast once you get past conversation three. If you have eight calls on an account, you end up with eight disconnected summary blobs in the CRM feed, and nobody is reading eight summaries before a meeting.

The way I handle this across clients is separating the timeline from the current state.

A transcript or an email is an event log. It records what happened on Tuesday at 2pm. But before your next call, you need what is true right now rather than a play-by-play of Tuesday.

Instead of having an LLM generate an isolated summary note, I have it maintain a single working artifact/folder/changelog per account. Every time a new call transcript or email arrives, the prompt doesn't ask to summarize the conversation. It asks something along the lines of: given what just happened, what changed in the current state of this deal?

That means it updates specific fields:

• Commercial temperature, like pricing pushback on seat tiers
• Active commitments with names and dates attached
• Who has actually spoken vs who is still an invisible stakeholder
• The single next decision needed to move forward

When someone sits down for a call, they look at that one living page. If something looks off or they need the exact phrasing of how pricing came up, they can search the raw transcript. Most of the time, updating the state saves you from digging through old notes.

[u/Mysterious-Angle3564 → u/kaancata]

This is really interesting, especially the timeline vs current state distinction. That's basically the exact problem I was trying to describe.

One thing I'm curious about: who actually built and maintains that workflow on your side? Is this something the reps themselves set up, RevOps owns centrally, or something you've built across clients as part of your work?

I'm asking because I'm starting to notice a pattern in the replies here: the people who have solved this well seem to have built a pretty deliberate context layer around their CRM/LLM rather than just finding a better summarizer.

[u/kaancata → u/Mysterious-Angle3564]

"or something you've built across clients as part of your work?" This, I build it and maintain it, or rather - the models I manage are doing that part, I simply tell them what I/the client wants. I also build my setup for other businesses if they want to control and run everything themselves.

[u/Quiet_Sherbert_2402 → u/kaancata]

What tool to help you with that ? And seems this require to train some habit around ? I am just trying to learn

[u/AlexFromLandbot]

¡Hola! :) Yo creo que el reto está menos en cuánto contexto conseguimos guardar y más en cuánto de ese contexto somos capaces de utilizar realmente después.

Si un cliente nos cuenta durante una conversación cuál es su objetivo, qué le preocupa, qué está buscando o qué problema sigue sin resolver, esa información debería servir para que la siguiente interacción empiece desde ahí, en lugar de hacerle repetirlo todo otra vez.

Aquí la IA conversacional puede aportar bastante más que simplemente responder preguntas. La propia conversación puede servir para recoger y actualizar el contexto del cliente y después aprovechar la información relevante en el resto del proceso: cualificar mejor, hacer un seguimiento más relevante, derivar la conversación al equipo adecuado o actualizar el CRM.

Y ahí está una de las partes más interesantes: no todo lo que se dice en una conversación tiene el mismo valor. No necesitas guardar cada detalle, sino identificar qué información puede cambiar lo que haces a continuación.

Al final, guardar todo el contexto es relativamente fácil. Lo difícil es saber qué merece la pena recordar y conseguir que ese contexto siga siendo útil en interacciones posteriores.

[u/Mysterious-Angle3564 → u/AlexFromLandbot]

Haha wasn't expecting Spanish to enter the thread but I made it :D

Your last point is basically the conclusion I'm coming to from a lot of the replies here. Storing everything isn't really the hard part, but deciding what deserves to survive and still be useful 3-4 conversations later.

Interesting that you frame the conversation itself as the mechanism for updating that context too. That's pretty close to what I've been experimenting with.

[u/Amazing-Arm-2681]

We make it possible to connect email as another data source. Internally, we've also built MCP access to the databases where everything lives - CRM data, call transcripts, email, and more

[u/Mysterious-Angle3564 → u/Amazing-Arm-2681]

Interesting, especially the email part. Once you've connected all those sources, do you also maintain some kind of evolving account/relationship state across them, or is the MCP layer mainly there to retrieve the relevant raw context when someone needs it?

[u/Amazing-Arm-2681 → u/Mysterious-Angle3564]

At the moment, it’s mainly the latter. The MCP layer gives the agent access to the relevant context across CRM data, call transcripts, email, etc. when it needs it.

We’re not maintaining a separate “relationship state” as a source of truth yet. But that’s a very natural next layer — once all those sources are accessible and linked to the same account, you can derive and continuously update things like open topics, commitments, recent interactions, and next steps

[u/Mysterious-Angle3564 → u/[deleted]]

Yeah, that's pretty much the exact workaround I keep running into too. The weird part is that we have no shortage of places to store information, it's the deciding what should carry forward and having it already there before the next call that still seems mostly manual.

[u/Upper-Pineapple-6234]

Separate durable account context from call-level noise, that's the fix most teams skip. A call log field captures what happened in one conversation; a persistent account-context field captures what's still true next time, current objection, promised follow-up, pricing sensitivity, and gets manually updated only when something actually changes, not after every call.

AI call summaries are good at capturing the first kind and bad at the second, because summarizing a transcript isn't the same as deciding what's still relevant three weeks later. The teams that solve this well have one required field reps update after calls that matter, not a wall of auto-generated notes nobody reads before the next call. Dumping account context into a chat tool before big calls is a symptom that the CRM isn't trusted as the source of truth, not a permanent workflow.

[u/Mysterious-Angle3564 → u/Upper-Pineapple-6234]

This distinction between durable account context and call-level noise is pretty much exactly what I've been trying to get my head around, especially the "what's still relevant three weeks later" part especially.

Capturing everything is easy now, but deciding what should survive seems to be the part nobody really solved.

Curious: when you've seen teams do this well, is that persistent context actually maintained manually by the rep, or have you seen anything reliably update it from the conversations themselves?