An Interview With Chad Silverstein
The best place to start is internally, with the people doing the work. They’re usually the ones who know where the bottlenecks are and where AI can have the biggest impact.
In the ever-evolving and never-ending landscape of business, staying ahead of the curve is a prerequisite for success. Artificial Intelligence (AI) has gone from being a futuristic concept to a daily business tool that executives can’t ignore. In this interview series, we would like to talk with business leaders who’ve successfully integrated A.I. into their operations, transforming their companies in the process. I had the pleasure of interviewing Raja Walia.
Raja Walia is the founder and CEO of GNW Consulting, a MarTech-driven strategic operations agency that guides companies through the ever-changing landscape of marketing technology. Raja has been leading teams and spearheading marketing strategies across hundreds of organizations for more than 20 years. He is recognized as a focus-driven leader who consistently delivers the perfect balance of strategy and execution for marketing operations professionals ranging from small to Fortune 500 businesses.
Thank you so much for joining us in this interview series! To set the stage, tell us briefly about your childhood and background.
My family and I moved from Punjab, India, to the States in 1990. I really didn’t get acclimated until the late ’90s. I honestly didn’t even know what pizza was until I watched the Teenage Mutant Ninja Turtles and wondered, “What is that they’re eating, and why does it look so good?”
I started in consulting in 2011, specifically in MarTech, during the MarTech boom. There were only about 900 Software-as-a-Service (SaaS) products at the time. I’ve been consulting my entire professional career and have worked at various sized consulting firms. I had the opportunity to work with clients like American Express, McKesson, and Nasdaq. I’ve always been a fan of technology, so in my early career, I took the time to learn as many platforms as I could, from Adobe to Oracle (Eloqua), Salesforce, and whatever else I could find. I wanted to be certified in all of them, and eventually I held certifications in every platform I consulted on.
What were the early challenges you faced in your career, and how did they shape your approach to leadership?
Learning by doing and failing. There were no best practices and no playbook. A lot of it was figuring out how to do just about everything on the fly.
That experience still shapes how I hire and train consultants today because I remember what it felt like. The pressure of learning something new while also being expected to perform and get things done was intense. When I say I’m a leader who builds, what I mean is that I haven’t forgotten what it’s like to be in that position. I have a lot of patience for employees because I know how difficult consulting can be.
Finding solutions isn’t easy when you’re expected to be the outside expert. As consultants, we’re often brought in as the third-party experts who are either viewed as heroes when things go well or blamed when things don’t.
Throughout my career, I’ve worked for all kinds of leaders. I’ve reported to people whose approach was, “shut up and do it,” “figure it out,” or “that’s why you have a salary.” I’ve also worked for leaders who never held regular one-on-ones and were completely hands-off as long as the work got done.
Both approaches sit at opposite ends of the spectrum. On one side, it’s difficult to grow if you’re not challenged to improve and develop resilience. On the other, it’s hard to stay motivated when someone is constantly looking over your shoulder. The best leadership exists somewhere in the middle.
Leaders need enough experience and expertise to properly guide their teams while also creating an environment where people can learn, grow, and thrive. That’s something I think about when hiring leaders as well. There are specific qualities I look for because I’ve experienced firsthand the types of leadership that bring out the best in people and the types that don’t.
We often learn the most from our mistakes. Can you share one mistake that turned out to be one of the most valuable lessons you’ve learned?
I’m going to answer this in two ways: professionally and personally.
Professionally, I once deleted an entire Google Analytics instance for a very, very large enterprise company at 2 a.m. I had been working for more than nine hours trying to solve a problem that I just couldn’t figure out. It bothered me so much that even when I tried to step away, I couldn’t stop thinking about it.
By that point, I was exhausted. I was so tired that I didn’t even notice the warnings before deleting the entire instance. Then I had to work with Google to restore it, which took another four hours.
The lesson came the next day. After getting some rest and coming back with a fresh perspective, I found the solution in probably five minutes. Sometimes we spend so much time trying to force an answer that we make things worse. Stepping away isn’t avoiding the problem. Sometimes it’s the fastest way to solve it. Your brain needs time to disconnect.
On the personal front, my biggest lesson has been about being intentional with my communication.
I’ve always been a hands-on, heads-down person. I can put on music, focus on the work, and stay in my own world for hours. Early in my career, a lot of information stayed in my head. I knew what I was doing, but I wasn’t always good at translating that knowledge to other people.
Over time, I learned that communication is just as important as execution. Not everyone processes information the same way, and not everyone speaks the language of technology. If you want to lead, you have to be able to explain complex ideas in a way that other people can understand and act on.
Technical skills matter, but there are plenty of situations where strong communication skills matter even more.
A.I. is a big leap for many businesses. When and what first sparked your interest in incorporating it into your operations?
When AI first became available, I jumped in immediately. I’ve never been the type of person who waits for a final product before testing it. I’ve always been the opposite. Sign me up for the beta, the pre-beta, the beta beta. I want to learn as something is growing, not after it’s already established and everyone is using it. That’s always been my personality.
Some people learn by reading tutorials, watching YouTube videos, or waiting for a best-practices guide. I’m the person on a plane, in the air, reading how to fly the plane and not crash. I learn by doing.
When you’re that early to something new, the possibilities feel endless. You can probably think of 100 ways to incorporate a new technology into a business. By the end of the day, you’ve narrowed it down to 10, and then you’ve thought of 100 more.
That’s what initially attracted me to AI. The technology itself was interesting, but what really captured my attention was the number of ways it could change how businesses operate. Every conversation led to another idea. Every use case uncovered three more. It created an opportunity to rethink processes, workflows, and operations across the business.
I wanted to learn alongside the technology as it evolved because that’s where some of the biggest opportunities usually emerge.
AI can be a game-changer for individuals and their responsibilities. Can you share how you personally use AI and what are your go-to resources or tools?
Once again, let me answer this in two ways: personally and professionally.
In my personal life, I coach my kids’ little league teams, from soccer and baseball to football. I use LLMs to create plays and visual materials that are fun for kids between the ages of five and seven. I don’t want to give them diagrams with just Xs and Os. I want things that are more creative and easier for them to understand.
I even use AI to help translate adult concepts into kid concepts. A lot of coaches tell kids to run routes, run a flat, run a dig, cross over, and so on. Kids don’t think that way. Everything has to be more fun, and even the diagrams have to translate to them.
Professionally, I use AI for everything from calendar organization and note-taking to meeting optimization. I also use LLMs as a spot check for ideas and thinking. You have to be careful, though, because they tend to agree with you. You have to push back and make sure they’re configured to challenge you instead of just reinforcing what you already think.
Beyond that, I spend a lot of time experimenting with no-code and prompt-based platforms like Lovable. I recently built a user-facing platform to help our customers with GEO citations.
On the flip side, what challenges or setbacks have you encountered while implementing A.I. into your company?
Where to actually implement AI is probably the number one thing most companies struggle with. There’s a lot of jargon out there and a lot of YouTube videos telling people they can automate anything. The reality is that there are areas where AI enhances what people do, and there are areas where people still need to be part of the process.
One of the biggest challenges is constantly fighting the urge to say, “Let’s replace this entire process with an agent or AI.” That’s usually where things get complicated. It’s like peeling the layers of an onion. You think something will work, but once you start digging into it, the rabbit hole goes very deep, very quickly.
Let’s dig into this further. Can you share the top 5 A.I. tools or different ways you’re integrating AI into your business? What specific functions do they serve and what kind of result have you seen so far? If you can, please share a story or example for each.
1. Claude — I use Claude for multiple things, but each chat has a very specific purpose. Some are dedicated to code work, some to technical templates, some to creativity, and some to strategy. I even have chats dedicated to market research, competitor analysis, and product research. I’ve set up alerts and notifications that pull information from the market and give me the highlights. It’s basically my own curated newsletter of information. We also use Claude with the Read.ai MCP server for note-taking, meeting transcripts, and documentation.
2. Lovable — We’ve built a few things in Lovable, and I’ve personally built two. One is an AI Optimization Index that dynamically pulls information and adjusts the assessment based on how someone answers. It gives businesses an idea of what’s needed across five different levers of AI adoption and provides a 30-, 60-, and 90-day plan.
The cool part is that if you take the assessment today and come back 30 days later and answer honestly, the plan changes because the index evolves every time someone takes it. We’ve also built custom reporting and analytics applications for clients to solve reporting challenges that would normally require a BI tool and a developer coordinating together. We’ve been able to do that in a fraction of the time.
3. Leo, Your GEO Buddy — I’m biased on this one because it’s my favorite and I helped create it. Our CSO had a vision for making content more likely to be cited by LLMs from a GEO perspective. One of the biggest challenges was consistency. If you take a piece of content and ask an LLM to “make this GEO-ready,” you’re going to get different results every time.
We took everything we knew, combined it with the research our CSO had done, and turned it into a repeatable playbook. The playbook creates a consistent process that helps improve the likelihood of citation. It also makes it easy for someone to update content directly in a CMS without involving a webmaster. The key is consistency. That’s what makes it work.
4. n8n — You can’t be a developer and not know about n8n. The ability to build workflow automation without writing code the way we used to is amazing. Whether it’s moving data between systems, creating complex workflows, or automating repetitive processes, the visual editor makes it incredibly powerful. This is one of those tools that’s kind of an “if you know, you know” platform.
5. Veo 3 — This one is more personal. I’ve been using Veo 3 to learn video editing. I created a horrible, but funny, Leo announcement for LinkedIn despite having absolutely no video editing experience. I used Claude to generate a script, took it into Veo, and started experimenting with ideas. Being able to take something silly that my kids created and turn it into an animated video has been a lot of fun.
There’s concern about A.I. taking over jobs. How do you balance A.I. tools with your human workforce and have you already replaced any positions using technology?
I can’t predict the future, but at the current stage of AI, it’s very hard for AI to replace humans completely.
You still need people in place to validate and confirm that what an agent is doing is actually correct. Without a database or some form of memory, an agent performs a task and then immediately forgets it. When something is executed through an n8n workflow or an agent, the human is still responsible for making sure the outcome is right.
I do think AI will replace some of the more tedious work. Things like checking spreadsheets, consolidating data, or managing parts of paid advertising that previously required a lot of manual updates can already be automated to a certain extent.
What happens down the road is anyone’s guess. AI will probably continue to improve and get better at making recommendations and supporting decisions.
Right now, though, the key thing the human workforce still holds is decision-making. An agent can execute tasks. It cannot make business decisions. That’s still where people provide the most value.
Looking ahead, what’s on the horizon in the world of AI that people should know about? What do you see happening in the next 3–5 years? I would love to hear your best prediction.
My best prediction is that we’re going to see new jobs emerge where people oversee what agents and AI systems are doing.
I think tactical jobs are going to be impacted the most. I’ve talked about this before, but I believe every employee will eventually have a digital teammate that they chat with, communicate with, and work alongside throughout the day.
That digital teammate, AI assistant, or whatever it ends up being called will become your “doing arm.” It will handle certain tasks while you focus on others.
The companies that learn how to manage both humans and AI are going to be the most successful. Think of it as a new interface for work. You log into your workstation and your digital teammate is already there. It highlights what needs attention, surfaces priorities, and helps organize your day. You assign it the tasks it can handle, while you focus on higher-level work, decision-making, and validating outcomes.
Today, we navigate software through menus, dashboards, reports, and applications. I think that changes over the next three to five years. Our interactions will increasingly start with a digital helper, teammate, or AI agent.
Instead of going into software and figuring out how to build something ourselves, we’ll simply ask for it.
If you had to pick just one AI tool that you feel is essential, one that you haven’t mentioned yet, which would it be and why?
That’s a hard question to answer because everything is changing so fast.
I could tell you my favorite AI tool is X today, and by the time this gets published there will probably be 40 more tools on the market competing for that spot.
Right now, I’d say Claude is still my favorite, with Lovable right behind it. Claude gives me the flexibility to think through ideas, research, strategy, and problem-solving. Lovable gives me the ability to be creative and build things quickly.
What I like most is the speed. I can build something, test it, and see if it works. If it doesn’t, I delete the project and move on. The cost of experimentation is so much lower than it used to be, which makes it easier to try new ideas and learn from them.
For the uninitiated, what advice would you give someone looking to integrate AI into your business and doesn’t know where to start?
This is just my advice, but you can’t know how to integrate AI without first understanding what the tool does and what job or process you’re trying to use it for.
I know that’s not realistic for every owner or CEO, but simply saying, “Let’s get more AI in here,” isn’t the right approach.
You have to pick a starting point. In larger organizations, that usually means talking to the people doing the work every day. The people who have ever said, “Man, I wish this was faster,” or “If someone could take this off my plate, I could focus on something more important.” Those are the people who will help you identify where AI actually fits and where it can make the organization more efficient.
Don’t follow the hype. You’ll hear a lot of stories about autonomous companies, replacing entire departments, and running businesses with almost no people. There’s a lot of clickbait and fluff out there, so don’t fall into that trap.
The best place to start is internally, with the people doing the work. They’re usually the ones who know where the bottlenecks are and where AI can have the biggest impact.
Where can our readers follow you to learn more about leveraging A.I. in the business world?
GNW Consulting Website for AI updates and information
My LinkedIn to follow me and connect
This was great. Thanks for taking time for us to learn more about you and your business. We wish you continued success!
About The Interviewer: Chad Silverstein is a seasoned entrepreneur with 25+ years of experience as a Founder and CEO. While attending Ohio State University, he launched his first company, Choice Recovery, Inc., a nationally recognized healthcare collection agency — twice ranked the #1 workplace in Ohio. In 2013, he founded [re]start, helping thousands of people find meaningful career opportunities. After selling both companies, Chad shifted his focus to his true passion — leadership. Today, he coaches founders and CEOs at Built to Lead, advises Authority Magazine’s Thought Leader Incubator. Learn more at www.chadsilverstein.com
Raja Walia of GNW Consulting: How We Leveraged AI To Take Our Company To The Next Level was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.