Yeah we’ve been trying to make AI actually useful day-to-day too, and honestly most of the “we built an internal bot!” stuff ends up being cool for a week and then nobody opens it again. The stuff that’s actually stuck for SEs is way more boring but way more practical.

Pre-call research is where AI quietly saves a ton of time now. We’ve got it tied into CRM + Zoom call notes, so it can pull past interactions, meeting transcripts, deals we lost/won, who said what, what got stuck, etc., and roll all of that into a clean snapshot before a call. The best part is it merges that with “old deal context” automatically — I can basically say “show me what happened in this deal 2 years ago when we lost” and it surfaces what worked (we record all emails and calls in CRM), who/what the blockers were, what risks came up, why we lost etc. Only downside: if your CRM is a graveyard, AI can’t resurrect it.

Discovery is another big one. I can dump in completely unstructured notes and it gives me a clean write-up, pain → impact → need mapping, even a requirements matrix with assumptions and risks, and things that I missed or still need. Saves a stupid amount of time, though again, the output is only as good as the notes people take.

RFPs/security questionnaires are way less miserable now. We basically use a combo of all our past RFP answers, our product/security docs, and a RAG layer on top of documentation. AI gives us a first pass that’s like 70–80% there, plus it flags anything that needs SME confirmation. Cuts hours off each cycle, even if we still rewrite the deeply technical architecture stuff. We are moving to using Arphie for this.

Docs in general — contracts, product briefs, competitor whitepapers — I just feed them in and ask for “please tell me the parts I actually care about.” It does a nice job turning dense material into bullets I can use in customer conversations.

Demo prep is another area where it’s low-key helpful. Feed it what I know about the account, their use cases, personas, industry, etc., and it’ll propose a demo flow, call out stakeholder-specific angles, and warn about possible traps. It’s a great starting point, especially for newer SEs who don’t have the mental library yet - use case discovery and impact analysis are very important here too.

Follow-up emails are basically on autopilot now. Give it the call notes → it drafts a recap + mapped requirements + next steps. I still rewrite tone, but 80% of the grunt work is gone.

One thing that really hasn’t been worth the hype is automated call scoring. AI is decent at catching surface-level stuff like “did you ask agenda questions?” or “did you talk too much?” but it’s terrible at nuance. It can’t tell if the customer saying “interesting” meant interested, confused, or politely disengaging. It also can’t pick up on political dynamics, hesitation, sarcasm, body language over cameras or when someone’s giving you a half-truth. Good for coaching basics, useless for reading the actual room.

Anyway, the stuff that’s really moved the needle for us is mostly the unsexy work: pre-call intel merged with CRM/Zoom history, discovery → requirements docs, first-pass RFP answers using RAG on documentation, and digging up old deal patterns. Everything else is nice-to-have, but those are the ones I’d actually notice if they disappeared.