Liza Adams

Do you connect multiple Custom GPTs in one ChatGPT conversation? Answer in the poll below.

If you picked anything other than “Yes, regularly” – this will change how you work with AI.

When you “@mention” different GPTs in the same conversation, they build on each other’s work instead of starting fresh each time. It’s similar to how we tag people on LinkedIn.

Your research GPT gathers competitive intel → @Pitch Deck GPT turns insights into compelling slides → @Press Release GPT drafts the announcement → @CEO Digital twin GPT reviews it in the CEO’s voice and style.

One conversation, full team of experts, zero re-briefing.

It’s simple yet so powerful. Probably one of the most underrated and underused features of ChatGPT despite being available for over a year and a half!

Why has it flown under the radar? You need multiple Custom GPTs to make chaining valuable, and most people haven’t built them.

Most teams lose context in handoffs between AI teammates. Some teams are chaining them together.

Teams using this approach are reimagining how work flows when expertise can move freely across boundaries instead of getting stuck in department silos.

Find out how to build your first chain, see a chain in action, and understand why this creates competitive advantage in my upcoming newsletter.

Subscribe to the newsletter (link in comments) to get the full breakdown.

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I built an AI to decode my own kids’ language.

Last week in CMO Coffee Talk we shared productivity hacks. People talked about cooking tips, AI tools, all kinds of stuff. Loved it!

My contributed hack: Teen Slang Slayer GPT

My kids speak English. I think it’s English. But when they say “NGL that’s mid” and ask for the “tea” I’m lost.

So I built a GPT to translate teen speak for me. Here’s what it does:

• ➡︎ Tells me “mid” means average (not middle school)

• ➡︎ Explains that “tea” is gossip, not the drink

• ➡︎ Helps me know “FR” means “for real”

• ➡︎ I thought “TBH” meant “to be hired” for way too long 🤦‍♀️

• ➡︎ Flags when slang might mean something serious

Best part is that it also tells me how to respond without being cringe. Apparently when moms say “that’s fire” it’s not cool. Who knew? 😂

Turns out asking “what does that mean?” doesn’t make me uncool. I was already uncool. Now I’m just uncool and know what they’re saying.

If you have teens or can’t understand your kids either, see the link to the Teen Slang Slayer GPT in the comments. Enjoy!

Teen Slang Slayer – https://chatgpt.com/g/g-687a6c8b19c88191a371ae0d544c91bb-teen-slang-slayer

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Published on 2025-07-18 13:09

Yesterday I posted how AI judges companies by how they treat employees. With layoffs making the job market increasingly tough, does AI also evaluate how companies treat candidates?

Try this prompt: “I’m considering applying for a [role] at [company]. What’s their hiring process like and how do they treat candidates? Are there any red flags?” Test it for your company, too.

Below is an example of what I got when I asked about a major company’s hiring process.

AI pulled from 20+ sources to build a hiring reputation profile. No marketing team controlled this narrative.

Your hiring process IS your brand experience. Every ghosted candidate, every unpaid “project” disguised as an interview, every fake job posting creates digital breadcrumbs. AI finds them.

Think about it from a GTM perspective. When AI tells a prospect your company has “disorganized processes” and “poor communication,” what does that signal about how you treat customers?

That mistreated candidate could be your next buyer. That person who spent hours on free work might be at a company evaluating your solution. AI is connecting these dots for them.

Your employer brand and customer brand aren’t separate. Every hiring touchpoint shapes market perception.

Marketing teams obsess over customer journey mapping. But most don’t realize the candidate experience directly impacts brand perception. AI is making this blind spot visible to everyone.

You can’t build trust in the market while breaking it in hiring.

Remember that this was just casual AI chat. Imagine what deep research AI tools could dig up.

We’re in the messy middle with AI with layoffs, job uncertainty, companies claiming to be “AI-first.” But what does AI-first really mean when AI is watching how you treat people?

Share if others should know. See link to yesterday’s post in the comments.

Newsletter on “When AI Judges Your Brand Before Humans Do”