Earley AI Podcast - Episode 88: Digital Twins, Agentic AI, and the Future of Work with David Shim

In this episode, Seth Earley speaks with David Shim, Co-Founder and CEO of Read AI, the fastest-growing meeting intelligence platform globally with over 5 million monthly active users. They explore how AI is moving beyond summarization toward recommendation and autonomous action, what it really means to build a digital twin grounded in your actual work history, and why the organizations getting the most from AI are the ones that treat it like a trainable intern rather than an out-of-the-box solution. David shares candid insights on agentic guardrails, data privacy, workforce transformation, and why access to personal AI may one day be considered a basic human right.

Key Takeaways:

• AI is moving from task execution to recommendation - the next frontier is AI that proactively surfaces what you should do next.
• A digital twin is only as good as its context; weighting recent activity more heavily produces responses that actually reflect how you think and work today.
• Treating AI like a trainable intern - feeding it your emails, files, meetings, and tools - is what separates high-value users from disappointed ones.
• Native permissions are the cleanest foundation for digital twin privacy; building new rules for every edge case creates the vulnerabilities you are trying to avoid.
• Agentic guardrails should be built in from the start, not bolted on - autonomy without oversight erodes trust and adoption faster than it builds them.
• The tension between organizational IP and individual work style is real; your tone, voice, and preferences belong to you, even when the content belongs to the company.
• AI is a great leveler - emerging markets and individuals with access to these tools are already competing on equal footing with developed market counterparts.

Insightful Quotes:

"It's not plug and play today. You have to give it more context - your emails, your files, your CRM, your meetings. When you have all that data, now your intern is learning as you go, and it's pulling from your experience as the mentor." - David Shim

"Your digital twin knows I hate meetings after three hours straight. After three hours, my engagement goes down, my sentiment goes down - so it puts in a buffer. That's the first part. Then it starts asking: what happens when people ask you a question?" - David Shim

"You can't take the AI's version of the world as a representation of your version of the world. What's more valuable is your secret sauce, your knowledge, your expertise - you have to give it examples of your work, give it your perspective, not just take the LLM's." - Seth Earley

Tune in to discover how digital twins and agentic AI are transforming the way individuals and organizations work - and what it takes to get real value from the technology before it gets ahead of you.

Links

LinkedIn: https://www.linkedin.com/in/davidshim/

Website: https://read.ai

Ways to Tune In:

Earley AI Podcast: https://www.earley.com/earley-ai-podcast-home Apple Podcast: https://podcasts.apple.com/podcast/id1586654770 Spotify: https://open.spotify.com/show/5nkcZvVYjHHj6wtBABqLbEiHeart Radio: https://www.iheart.com/podcast/269-earley-ai-podcast-87108370/ Stitcher: https://www.stitcher.com/show/earley-ai-podcast Amazon Music: https://music.amazon.com/podcasts/18524b67-09cf-433f-82db-07b6213ad3ba/earley-ai-podcast Buzzsprout: https://earleyai.buzzsprout.com/

Podcast Transcript: Digital Twins, Agentic AI, and the Future of Work

Transcript introduction

This transcript captures a conversation between Seth Earley and David Shim about how AI is evolving from passive note-taker to proactive digital twin - an AI that knows your preferences, manages your schedule, answers on your behalf, and acts in your name while you sleep. They explore the technical and organizational conditions required to make that work safely, how organizations can drive bottom-up AI adoption without waiting for IT, and why the long-term workforce implications of these tools may be more equalizing than most people expect.

Transcript

Seth Earley: Well, welcome to today's Earley AI Podcast. I'm your host, Seth Earley, and in each episode, we explore how artificial intelligence and data are shaping the business strategy and operations of enterprises today. Today, we're looking at how AI is transforming the way we work - from meeting intelligence and productivity to digital twins and agentic technologies that act on our behalf.

Joining me is David Shim, who is CEO of Read AI, the fastest-growing meeting intelligence platform globally, with over 5 million monthly active users and 40,000 users signing up every single day. David founded a location analytics company in 2011, which Snapchat acquired in 2017. The business was subsequently spun out to Foursquare, where David served in a senior leadership role before leaving in 2020 to found Read AI. He brings a deep background in machine learning, product-led growth, and building AI-powered tools that people actually use. Welcome to the show, David.

David Shim: Thanks for having me, Seth. Excited to be here.

Seth Earley: So, let's start with misconceptions. What are the biggest things people are not understanding about AI today, especially when it comes to how individuals and organizations think about what it can do for them?

David Shim: I think they're missing out on the recommendation side of things. Right now, AI is doing very specific tasks. You bring an agent into a meeting, it takes the notes, you get the notes, you decide what to do with them. Where things are going is those agents saying, hey, based on what you've done in the past, let me recommend that you probably want to follow up with the PDF of the deck, or you want to schedule a follow-up call, or bring in one of your associates to talk about the methodology. That recommendation stage is where it starts to look more like Match.com or Tinder - we're going to figure out what sticks, but the recommendation piece is going to be huge. And I think people are kind of ignoring the fact that AI is going to help you get there faster - and then the question is, what are you going to do with your time?

Seth Earley: And what about people who jump in and are disappointed? Because we're seeing a lot of misuse too - consultants producing 50-page AI documents with no synthesis, no analysis, no creative thought. What are your thoughts on how people are using or misusing the technology?

David Shim: Anyone who jumps in and assumes that logging into ChatGPT or Claude means everything is just going to work is in for a bad experience. Where you get a great experience is when you understand it is like an intern. When an intern comes in, they might even have an MBA and be ready to dive in, but you still have to train them, you still have to get them up to speed. With Read AI, it is not just meetings - you have to give it access to your emails, your files, your Jira, your Confluence, your CRM. When you have all that data, now your intern is learning as you go, pulling from your experience as the mentor. When you apply that AI, it has more context. But it is not plug and play today. You need that mentality of, I am training this model to do work for me, not that it will do it out of the box.

Seth Earley: Let's talk about digital twins. Where do you stand on that concept, and what does it actually mean in practice?

David Shim: A digital twin, in its most basic form, knows everything that you know in the digital environment. It has your emails, your meetings, your messages, all the files and content you have created, the IP you have generated. It cannot go into your head, but your digital footprint is the basis to train it. And once trained, it knows as much as you do - and honestly, it has better recall. It can connect dots across meanings that you cannot.

The challenge is context weighting. If you give everything the same weight, it might pull something from four years ago that you cared about deeply and say, this is really important today - and you would say, no, it is not. When we built our digital twin, we tested the full context window against weighting the most recent activity more heavily. The world has changed in the last two years when it comes to AI. You want the more context-relevant, recent material. Once you do that, the digital twin starts responding more like you would. It starts thinking like you would.

We started with something basic: scheduling. When you think about scheduling, you spend a couple of hours a week coordinating meetings across multiple people. The digital twin connects your calendar, understands your meeting patterns, knows when you have good and bad meetings, and asynchronously coordinates with multiple people to find the right time. You do not even know it is doing that in the background. The meeting just appears on your calendar.

Seth Earley: And it goes beyond scheduling?

David Shim: My digital twin knows I hate meetings after three hours straight. After three hours, my engagement goes down, my sentiment goes down, and it is not a good experience for me or the other participant. So the digital twin has recognized that and puts in a 30-minute buffer before scheduling the next one.

Then it asks what happens when people ask you a question. If you CC Ada - that is our digital twin at Read AI - Ada will respond to questions that come in. If it is a basic question, like can you confirm that meeting time, it answers in your tone of voice. If it is more complicated, like what is your net price on this product, the digital twin says Seth normally does not give that out, so let me check in with him first. It will draft the response and flag it for your approval. If you say no, it pulls back.

We have clients in Asia and Europe. The digital twin is continuing conversations and getting work done while I am asleep. It is not just a tagline - it is following up, answering open questions, and the productivity impact is significant. We are only in the first inning.

Seth Earley: You have talked about AI access becoming a basic human right, similar to how we now think about internet access. Where do you stand on that?

David Shim: If you think about internet access 20 years ago - Prodigy, CompuServe, dial-up - if you had said that was going to become a human right, everyone would have laughed at you. We had mail, we had newspapers. Now people argue internet is a human right and everyone should have it. I think that level of productivity - getting your time back, getting the efficiency advantage - starts to cross that same threshold. And the best part is that it is going to be a great leveler. People who have access to AI are going to be just as competitive in whatever market they are in. If you have a computer or a phone with access to AI, you have a shot to be just as strong, just as educated, as anybody in developed markets.

Seth Earley: Let's talk about the tension between organizational IP and personal identity. The organization owns the content, but it does not own your tone, your voice, your working style. How do you think about that distinction?

David Shim: When it comes to raw content, the enterprise owns that. Emails, files, proposals created during work hours - that is work product. From that, you could build a digital twin that is highly valuable for the organization. What it does for the next person coming in is it eliminates the three-to-six month ramp-up time. Instead of that new person hunting for files and figuring out who to talk to, you let their agent talk with the digital twin that was built on the role, and it can just answer the questions, find the contracts, surface the context.

But now, Seth, imagine you go to a different organization. Your digital twin knows your voice. It knows you do not respond to emails after six PM. It knows that at eight AM you want to send a response right away because you want them to know you are on it. Those are preferences that belong to you. When your digital twin and the new organization's systems start talking, that process gets built out from the combination - and you are not starting from scratch at every new job.

Seth Earley: How do you handle privacy and permissions in a way that scales?

David Shim: The cleanest approach is to use native permissions. When you log into HubSpot, you have permissions that say you have access to this level of data. Your digital twin ultimately has the same level of access - it does not get more. In many cases it gets less.

The alternative is building rules for every case, building prompts for every case. What you run into is exactly what happened with early ChatGPT - people trying to probe it, find cracks in the system, extract personal information. You do not want that. Use what is native rather than trying to build the ultimate custom setup.

We launched with email because email is the clearest workflow. If I email someone, I expect a response from that person, not from fifty others. If the digital twin CCs a manager, that is fine - they are in the loop. And that transparency stops people from asking nefarious questions, because they know it is going back to the original person.

Seth Earley: Let's talk about agentic guardrails. You built those in from the start at Read AI. What does that look like, and why does it matter?

David Shim: The key principle is that the agent should always keep the original person visible. When a digital twin responds to an email about sensitive content, the original person still gets the actual content. They can go in and say, that was wrong, that was not something I wanted to share. You have that override.

What we found with Ada is that 25 percent of people still say thank you every time it completes a task - even knowing it is an AI agent. That tells you something about the value people are finding in it. But that trust only holds if the guardrails are real. Autonomy without oversight erodes adoption faster than it builds it.

Seth Earley: How are you seeing organizations adopt AI in a way that actually works, versus top-down mandates that stall?

David Shim: One of our clients is a multinational company with product managers in Tokyo, Paris, and LA. They all speak different languages. All the content they generate was not accessible across those teams. They started using our product individually in different markets, and usage spread organically. The company came in and said, we trust our employees to pick what makes sense for them. We did a review, leaned in hard, and now they are getting insights from Tokyo in LA that they never would have seen before. AI does not care that your meeting was in Japanese or French. It surfaces the top five global problems and says, here is what you should work on, here is feedback from clients in those markets.

That would never have happened with a top-down approach or by waiting for IT to decide what would go in. Bottoms up, then check with IT, then get it done. That is the pattern that works.

Seth Earley: Looking ahead, where do you see Read AI going, and what should business leaders be paying attention to as agents become more capable?

David Shim: Today, Read AI is the system of record for meetings for over five million people. People trust us for their notes, they are building on top of our systems to push into HubSpot, Salesforce, Jira, Confluence. Three or four years ago, meetings were like Snapchat messages - ephemeral, whatever you remembered, and then gone. Where we are going is a system of action. How does AI take actions for you, or how does it recommend specific actions?

Ada is already doing scheduling, it is already handling routine email responses. The next step is after a meeting, do you want me to schedule a follow-up? Do you want me to research this open question and ask four people in the org what the current status is? Even before that, can I move deals in HubSpot forward? Imagine you never have to update HubSpot again because it moves from 25 percent to 50 percent to 75 percent automatically based on the signals it is seeing across emails, messages, and meetings from everyone on the team. And then it says, Seth, if you make this call right now, there is a 95 percent chance you close this deal next week. That is where Read AI is headed.

Seth Earley: David, thank you so much for joining us and sharing your perspective on digital twins, agentic AI, and what it really takes for organizations to get value from these technologies.

David Shim: This has been a great conversation. Thanks, Seth. Appreciate it.

Seth Earley: And to our listeners, thank you for tuning in to the Earley AI Podcast. Be sure to subscribe for more conversations on how AI is shaping the future of business.