> ## Content Index > Fetch the complete content index at: https://intelligence.artificialrealitymedia.com/llms.txt > Use this file to discover other available public pages before exploring further. # Why the operators furthest ahead ask for nothing - URL: https://intelligence.artificialrealitymedia.com/ma-broker-product-requests-sideways/ - Published: 2026-09-02T12:05:00.000Z - Updated: 2026-09-02T12:05:00.000Z - Description: Asked what AI companies should build, an M&A broker running her firm on AI said she could not think of anything. Three requests came out sideways. - Author: Galina Fendikevich - Tags: M&A advisory, #For AI Companies, #Product requests, #Import 2026-09-03 13:12 Ask Christine McDannell what AI companies should build and she says she cannot think of anything. She runs The Magnolia Firm, a sell-side M&A brokerage in Austin, has cut payroll by 83%, and has automated more of her own job than almost any operator in this research. Three specific product requests still came out of the conversation. None of them arrived as an answer to that question. > "I cannot think of anything right now ... which is a good place to be. Tech is so exciting. And again, I'm in it all day, every day, to see the improvement so fast." The requests surfaced sideways, while she was describing work she had already done. ## What did she actually ask for? Three things: a social media agent that runs end to end, an M&A infrastructure platform so boutique firms stop rebuilding the same workflow, and a relationship system that can read her real network and tell her who to talk to. The first is the one she addresses to builders directly. > "I want it to go like from A to Z. I want it to actually — it knows my industry. So it does the content, it writes the prompts, it writes the keywords ... And then can it post it?" What she has instead is a chain of separate requests: > "I have to prompt every time. Okay, can you make sure you research the proper keywords for M&A industry? The ones that are performing best, can you put that? And then separately: okay, can you write a caption? So it's like piecemeal together." Her diagnosis of the cost is the line worth pinning above a roadmap: "Which is not fun, because I'm the human in the loop — but I'm too much in the loop on the social media stuff." ## Why does the social agent not exist yet? Because the steps do not chain. Galina Fendikevich, who hosts Artificial Reality, the AI buyer-evidence podcast, confirmed the same gap from extensive testing: separate products for keyword research, branding, carousels, copy, video clipping, captions and posting, with nothing covering the sequence. McDannell's own summary was direct: "So yeah, I think that the M&A industry, if it could have this marketing — so yes, Silicon Valley, please build this ... It's just this A to Z, because I don't see it out there." The buyer profile matters here. She says she is not on social media and does not enjoy producing content — "I hate doing content" — which is precisely who an end-to-end agent is for. She already has agents pinging her on Slack, Telegram and iMessage, so a notify-before-publishing step is familiar rather than novel. Posting is the last mile she names. ## What does a workaround look like when nobody calls it a request? Like a weekend of manual exports. Asked about relationship tracking, McDannell described building the missing product by hand: > "I exported my WhatsApp chats. I exported [LinkedIn](https://www.linkedin.com/?ref=intelligence.artificialrealitymedia.com) so I could go back January 1st ... and I did a report of everybody I've met in Austin. Anybody that lives in Austin I've met on January 1st or beyond. And then iMessage, it can actually export also. So I had to manually do these, export all these and then throw them in. And then it did create the spreadsheet." The purpose is not a sales pipeline. It is deliberate friendship maintenance: "I want to put everybody on a spreadsheet and track them, because I want to put a lot of effort into keeping those friendships — going through that list and being like, I should invite them to brunch or these events." Her reaction when the idea was described back to her as a product: "Oh my gosh, you should develop this. You have the best ideas. That would be rad. That would be super rad." On the existing category she is milder than her host. McDannell finds Salesforce "too robust" and HubSpot expensive, uses [Zoho](https://zoho.com/?ref=intelligence.artificialrealitymedia.com), spent significant time and money customizing it through an agency, and says it works well — while agreeing the setup burden is the category's problem. Fendikevich's assessment of HubSpot and Salesforce was considerably harsher: among the worst technology products on the market, requiring teams to maintain, unable to simply read an inbox and build profiles from it. ## What this changes about product discovery The most capable users make the worst survey respondents. McDannell has already routed around every gap she has, so nothing registers as missing. The need is visible only in the workaround, and the workaround looks like competence rather than complaint. So stop asking operators what they wish existed. That question returns "nothing" from exactly the people furthest ahead, and it returns speculation from everyone else. Ask instead: **show me what you did last week.** Then look for the steps done by hand between two tools. A manual WhatsApp export is a product specification. She does not experience it as one, which is why you will never get it from a survey. ## Where this comes from S1E5: How she cut her payroll by 83% using one AI agent — the full interview with Christine McDannell. Listen or watch: [YouTube](https://www.youtube.com/watch?v=1VO7nWtzNEU&ref=intelligence.artificialrealitymedia.com), [Spotify](https://open.spotify.com/episode/6E4sAUyfk4X5gUqEtzhL8o?ref=intelligence.artificialrealitymedia.com) or [Apple Podcasts](https://podcasts.apple.com/us/podcast/how-she-cut-her-payroll-by-83-using-this-one-ai-agent/id6780699025?i=1000776953676&ref=intelligence.artificialrealitymedia.com).