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Last week, I had the opportunity to hear Ty Abernathy share the story of building and ultimately selling Grayscale, his HR recruiting technology startup.

Grayscale’s journey had the usual startup ups and downs, including starting in one market and finding a better opportunity over time. But one aspect stood out because it’s something you rarely hear about in successful startups.

Grayscale figured out how to make channel sales work.

Why Channel Sales Are So Difficult

For most startups, selling through channel partners is incredibly difficult and often ends in failure.

The fundamental challenge is misaligned incentives and priorities. As entrepreneurs, our product is our number one priority. But larger companies have their own products, initiatives, and sales targets. Their account executives are typically compensated for selling in-house products, leaving little incentive to promote a startup’s offering.

Channel sales work best when reps earn meaningful commissions, the product is relatively easy to sell, and there’s enough money to justify the effort. Unfortunately, these factors rarely align.

That’s why I generally believe most early-stage startups are better off selling directly to customers. But Grayscale found a way to make channel sales a major growth driver.

Treat Channel Partner AEs Like Your Own Sales Team

Too often, entrepreneurs focus on the channel manager or senior executive responsible for a partnership rather than the people actually selling.

Grayscale took a different approach. They mapped individual account executives at their partners, learned their territories and accounts, and built relationships as if those AEs were part of Grayscale’s own sales team.

Rather than treating a channel partner as a single relationship, Grayscale treated its entire sales organization as an extension of its own.

Map the Partner’s Customers Against Your Ideal Customer Profile

Grayscale developed specific expertise in high-volume recruiting using text messaging, particularly in industries like warehousing.

Rather than waiting for referrals, Grayscale used publicly available information to map the customers of its applicant tracking system (ATS) partners against its ideal customer profile.

They then identified the account executive or customer success manager responsible for each promising account and concentrated sales support and relationship-building efforts on the best opportunities.

This was far more deliberate than signing a partnership agreement and hoping referrals would follow.

Go Deep While Developing the Next Channel

Grayscale continually worked to generate more business from existing channel partners by deepening relationships, identifying additional customers, and helping sales reps succeed.

At the same time, they monitored the evolving ATS market and built relationships with potential future partners.

They were constantly maximizing existing distribution relationships while preparing for the next channel opportunity.

The Risk of Building on Someone Else’s Platform

Grayscale’s customers already had an ATS, and Grayscale’s technology integrated into that system rather than operating independently.

This made ATS providers natural distribution partners, but also potential competitors. Those same partners could eventually build similar functionality or acquire a competitor.

Over time, that’s exactly what began happening.

Fortunately, Grayscale had built enough scale, industry expertise, and market presence to become an attractive acquisition target, ultimately leading to a successful exit to an established HR software and payroll provider.

The Bigger Takeaway

Channel sales are appealing because they offer access to established customer bases and sales organizations without building a large direct sales team.

But most entrepreneurs underestimate how difficult it is to make someone else’s salespeople prioritize their product.

Grayscale’s success wasn’t simply finding good channel partners. It was building an operating strategy around making those partners productive.

I still believe most early-stage startups are better served by selling directly to customers. But Grayscale demonstrated that channel sales can work exceptionally well with the right strategy and disciplined execution.

It’s a great case study in turning one of the more difficult startup distribution strategies into a competitive advantage.

Recently, I read the news that Patrick Stewart had passed away. Mr. Stewart was famous for a variety of roles, most especially his portrayal of Captain Jean-Luc Picard in Star Trek: The Next Generation.

Reading about him reminded me of one of the most interesting startup talks I attended ~15 years ago. Scott Voigt, now the founder and CEO of FullStory, was then running marketing at an email marketing company called Silverpop, and I had the opportunity to attend their user conference. Scott gave an incredible presentation about stories versus analytics and shared an anecdote about the importance of the Vulcan mind meld among teams.

In the original Star Trek series, Spock, played by Leonard Nimoy, was famous for performing the Vulcan mind meld. The mind meld is a telepathic technique where a Vulcan places their fingers on another person’s face, allowing the two to share thoughts, memories, and emotions. Instead of communicating through words, they can directly experience each other’s perspectives and develop a deeper understanding of one another.

Ever since then, when talking about startups and founders, I’ve referred to the Vulcan mind meld as the aspirational goal for the founding team.

The Vulcan mind meld happens organically much of the time just by having the founders sit next to each other in the same physical place. Every idea, every topic, every to-do list item, every initiative, every roadmap discussion, every customer call, and every piece of investor feedback gets sliced and diced and analyzed by the founders in the early days. There’s both an eagerness to know what’s going on and a desire to align and understand each other’s position.

Over time, as the startup grows, this becomes much harder. Departments emerge, founders develop their own areas of expertise, and more time is spent with other people in the organization, customers, vendors, and investors. As a result, the original Vulcan mind meld, which is so important to the early foundation of the startup, weakens over time.

The two best antidotes I’ve seen, and they’re not restricted to founders but are applicable to any executive team, are the daily stand-up and the monthly strategy dinner.

The daily stand-up has been popular for years. The idea is to get together once a day and answer three simple questions:

1. What did you accomplish yesterday?
2. What are you going to do today?
3. Are there any roadblocks?

Every day, day after day, answering these three questions as a team acts as a simple conduit for the basics of the Vulcan mind meld. Of course, it requires a lot more conversation and depth to truly sync on a daily basis, and that’s often not possible as the company scales.

That’s where the monthly strategy dinner comes in. The idea is that once a month, say the first Wednesday of every month, the founders or executive team get a private dining room at a restaurant or gather at somebody’s house and spend the next three to four hours debating the most important topics. A true deep dive into whatever needs to be discussed, especially topics that are strategic and longer-term in nature.

The day-to-day workday works great for the more tactical items and the fires that have to be put out immediately. But carving out time for the truly strategic but not urgent discussions is one of the best ways to continue the Vulcan mind meld around what we’re doing, where we’re going, and why we’re doing it.

Thanks to Patrick Stewart for bringing Captain Picard to life and helping make the Star Trek universe so memorable, and to Leonard Nimoy for bringing Spock and the Vulcan mind meld to life.

Entrepreneurs would do well to spend time and energy staying in sync with their co-founders and building programs and recurring activities to maintain that alignment as the business scales.

Recently, I was talking with a friend, and the topic of metrics came up. He shared an experience from one of his previous startups. The company was doing great, growing fast, and tracking a number of key metrics. However, they had this nagging issue where customers kept complaining, but the company would point to the metrics and say, “Look, we’re doing great. We’re hitting all of our metrics.”

After having this circular conversation repeatedly, where customers were clearly voicing concerns but all the metrics were green, they decided to make a change. If the anecdotes from customers don’t match the results from the metrics, the metrics need to be changed.

This seems obvious, but it’s easy for companies to build up systems, processes, and reports over time and get into a good groove. Of course, that doesn’t guarantee the metrics being tracked and the reports being generated match the actual customer experience.

The next time an entrepreneur is reviewing their metrics, it’s wise to look at not only the objective numbers but also the subjective feedback from customers. Entrepreneurs would do well to remember that if the metrics don’t capture the customer anecdotes, it’s time to change the metrics to make sure they do.

Last week I attended Venture Atlanta and had the chance to spend time with several entrepreneurs. A conversation in particular really stood out to me, and it was around the ideal customer profile (ICP).

One of the entrepreneurs I sat down with was from out of town, and she shared how her business had gone through some ups and downs over the years. In hindsight, the startup had tried to be too many things to too many customers. A new customer would sign up in a particular industry, and then they would start building programs and campaigns to go after more customers in that industry. Rinse and repeat.

After several years, they had quite a few customers, but churn was high and growth was challenging. Then, last year, they inventoried their customers across the different markets and decided to exclusively zero in on one particular ideal customer profile.

Now, a year later, growth has accelerated within that ICP. Customers outside of the ICP have churned dramatically, and overall, the business is in a much better place, growing nicely with high renewal rates and strong net dollar retention.

Only this conversation wasn’t unique to her.

Last year, I was talking to a different entrepreneur who shared that while they had grown fast, it was clear that one direction with a certain set of features was the future of the business. He was struggling with how to address the existing customers who no longer fit that direction.

After much back and forth and many conversations, he decided that the future of the business had to be with a subset of his existing customers. They weren’t going to achieve their potential by trying to serve multiple markets.

He too made the hard call to zero in on a much more specific ideal customer profile and recognize that existing customers outside of it were more likely to churn.

And that’s exactly what happened. The customers who were no longer a fit left, while the customers who were a good fit loved the product even more. Growth accelerated within that much more focused ideal customer profile.

As entrepreneurs, we’re eager to build and sell to anyone who’s interested. The old adage still rings true that more startups die from indigestion than starvation. Entrepreneurs are generally optimistic and eager to please customers, which helps them be successful but also leads them to try to do too much.

Entrepreneurs would do well to sharpen their ideal customer profile and stay laser focused on the long-term mission while constantly asking the question: Does this potential new customer help us achieve our goals?

With the arrival of persistent AI bots, I’ve enjoyed seeing the different ways people use these machines. One of my favorite use cases is never-ending research projects, where bots regularly go out, find information, summarize it, and present it on a recurring basis.

One research project I have running with my Grok Bot focuses on startup communities across the United States. Every Sunday night at 8 p.m., it takes the 100 largest metro areas in the country and researches their different startup organizations and communities, like Atlanta Tech Village in Atlanta or the Center for Entrepreneurial Development in Raleigh-Durham.

For each organization, it looks for news, press releases, announcements, programs, initiatives, annual reports, and other relevant information from the past week. Then it summarizes everything it finds, packages it into a single Markdown file, and emails it to me.

With a simple prompt and a bot running in the cloud, I now get to see what’s happening across the major startup communities in the United States, all packaged up and presented to me on a silver platter every Sunday night. It’s truly incredible.

I use this information to study what other communities are doing and contemplate whether we should be doing something similar in our own startup community. The big idea is that there are constant experiments happening all over the country, and by learning from other communities, we can find new ways to strengthen our own.

In addition to studying startup communities, I have a separate Grok Bot focused on downtowns across the United States. It’s very much the same idea. Take the 100 largest cities in the country, identify the downtown nonprofits and business organizations responsible for promoting their districts, running clean and safe programs, and supporting economic development, and then research what they’re doing.

The bot gathers recent press releases, news articles, announcements, and initiatives. When a new annual report comes out, it reads the entire report and summarizes the most interesting findings. Everything gets compiled into a Sunday night email with links back to the primary sources.

Again, downtown organizations across the country are constantly experimenting with programs and looking for ways to improve their communities. I want to learn from those experiments, identify the best ideas, and bring them back to our own local downtown.

Of course, this approach isn’t limited to startup communities or downtowns. You can use it for anything: your work, hobbies, passions, community involvement, or nonprofits you’re involved with.

I believe the ability to experiment with new ideas and then spread the best ones across organizations, industries, and communities has increased dramatically. As more people use bots in this manner, we’ll see great ideas spread faster and their corresponding positive impacts felt sooner.

Everyone should have one or more research bots running, constantly finding and synthesizing ideas from around the country and bringing the best ones back to them. The opportunities to learn from others have never been greater, and now the work of finding those ideas can happen automatically.

Last week I was talking to an entrepreneur who shared that, prior to AI software development tools getting so good, his team followed the standard two-week product sprint.

Every two weeks, they would sit down, map out the features, bug fixes, and roadmap priorities, and then the team would go off and do the work. They would write code, write tests, run everything through their internal processes, and then come back two weeks later to review what went well, what didn’t, where the different initiatives stood, and what should happen in the next sprint.

This type of two-week sprint is pretty common in the software development world.

Only now, with the advent of amazing tools like OpenAI’s Codex, SpaceX’s Cursor, and Anthropic’s Claude Code, the productivity of software developers has jumped dramatically. So much code is being written, so many tests are being created, so many features are being enhanced, and so many bugs are being solved that the head of product now does a daily stand-up with the head of engineering and the engineering managers every single workday.

Before, software engineers had to map things out, work through the code changes, write code, edit code, and test everything themselves. Now, much of that work is actually being done by AI. The software engineers are coaching the AI, providing feedback on what it writes, thinking through its recommendations on architectural changes, reviewing the code it produces, and orchestrating the different agents doing the work.

Of course, AI can write code much faster than a human. Software engineering is becoming much more about orchestrating agents than writing syntax in a particular language.

As AI coding continues to increase the pace of development, the biggest issue becomes curating what should actually be done.

When there are big initiatives underway, this is less of an issue. But when tweaking features and polishing different modules, it becomes easy to run fast and build things that might not be needed, don’t fit the overall vision, or are simply built because they are easy to build.

That makes staying close to the customer even more important. Teams need to understand the customer’s needs, how customers work today, and how they want to work in the future.

With two-week sprints, there was more time to gather feedback directly from customers, through customer advisory panels, customer success calls, or other channels. Now, if the product is changing on a daily basis, the customer feedback loop and the company’s opinionated vision of the future both have to evolve as well.

Ultimately, this all bodes well for startups delivering better products and customers getting more of what they need faster.

Entrepreneurs would do well to consider shrinking the cycle time of their sprints from two weeks to one workday, or some similarly short interval. But at the same time, they should dramatically increase the frequency and scalability of customer feedback so the team continues working on the most important things instead of adding more functionality simply because it is easy to do so.

We’re in a new age of software development. The startups that adapt best will balance dramatically faster innovation with equally fast customer feedback.

Last week, I had the opportunity to speak with the YPO Next Generation (YNG) Atlanta chapter about startups and entrepreneurship. YNG is a Young Presidents’ Organization program for members’ children between the ages of 18 and 30. Like the broader YPO community, the group regularly comes together through programs, retreats, and small-group forums to learn, share, and grow.

My talk focused on three themes.

The first was the unpredictability of life’s journey. I shared stories about startups I’ve been involved with and how often we began with one idea, worked hard at it, and then discovered a better direction. Almost every successful company I’ve helped build started by doing something other than what ultimately made it successful.

Pardot, for example, began by generating leads on behalf of B2B technology companies. We later pivoted to marketing automation, supplying those companies with the tools to manage their own lead generation and nurturing. We started in a promising area, but our first product wasn’t the one that worked.

The second theme was the human side of entrepreneurship. The familiar adage still holds: If you want to go fast, go alone; if you want to go far, go together.

In the startup world, as in nearly everything else, success comes down to people and teams. I shared stories about our focus on building a culture of positive, self-starting, and supportive people, as well as the two overarching mantras that guided us: Be the best place to work and the best place to be a customer.

This human-centered approach influences everything. When you talk with someone at a startup, or any company, you quickly get a sense of how they operate. Are they easygoing or cutthroat? Are they interested in a transactional relationship, or do they want to build trust for the long term? When something goes wrong, as it inevitably will, do they acknowledge it? How do they make it right?

The people side of business is, and always will be, one of the most important.

The third theme was market timing and the importance of following emerging trends. When something is white-hot and everyone is talking about it, it’s often too late. Ideally, you want to be three to five years early, early enough to build a working product, assemble a strong team, and establish a solid foundation.

Being a little early, but not too early, puts you in a powerful position. When the market arrives, you have the opportunity to grow even faster than the rapidly expanding market around you.

I enjoyed sharing these stories with the YNG group. If I had to distill the talk into three lessons, they would be these: Your original idea will often be wrong, people are at the center of everything, and in the startup world, it pays to be a little early when the next big trend arrives.

One of the things I enjoy doing is researching and coming up with new startup ideas. It’s fun to brainstorm and imagine what could be. Of course, there’s a big gap between ideation, execution, and ultimately building a successful company.

For many people who want to be entrepreneurs, there’s a natural feeling that the idea needs to be perfect. The reality is, it’s hard enough to find a great idea, let alone a perfect one.

A great starting point is simply talking to people. Reach out to friends, mentors, and colleagues and ask them what they would like to see exist in the world, in their home, or in their business. What frustrates them? What takes too much time? What do they wish worked better?

One of the best ways I’ve found to discover new ideas is to start doing something new yourself. Pick up a new hobby. Start a new side hustle. Make a new investment. Get involved with a nonprofit. Ideas become much easier to find when you put yourself in new situations.

Research fast-growing trends. Study lists like the Inc. 5000. Look at the companies on those lists and analyze their industries. Are they still early and growing quickly, which usually means there’s plenty of opportunity? Or are they growing quickly in an industry that has already matured, meaning there’s likely more competition and less white space?

My new favorite piece of advice for ideation is to combine AI with scheduled tasks.

Fire up ChatGPT, Claude, Grok, Gemini, or one of the newer automated AI agent products like Grok Bot, Meta Muse, or Instinct. Better yet, use several of them.

Then have the AI generate a new startup idea for you every hour, every day, or every week and notify you when the idea is ready for review.

Each time it sends you an idea, provide feedback. Do you like the category? Do you like the industry? Do you like certain characteristics of the business? What don’t you like? Over time, that feedback helps steer the next ideas in directions that are more interesting to you.

For me, I’ve turned this into a simple daily routine. Every night, ChatGPT is scheduled to generate a new startup idea and send it to me. Then every morning at 8 a.m., Grok Bot generates a second startup idea. That means I start each day with two fresh startup ideas to review.

As I go through them, I give feedback on what I like and don’t like: the market, the customer, the business model, the level of complexity, the size of the opportunity, and anything else that stands out. The goal is for that feedback to continuously improve and refine the types of ideas being generated.

Most of the ideas won’t be great. That’s the point. Instead of sitting down occasionally and trying to force myself to come up with a great startup idea, I have two AI systems continuously feeding me new possibilities every single day, seven days a week.

For entrepreneurs looking for new ideas and inspiration, talking to people about their problems and using AI on a scheduled basis to continuously generate ideas creates a tremendous number of possibilities to contemplate, combine, refine, or turn into the next big startup.

Every year, I look forward to reading the latest Inc. Magazine Inc. 5000 list of the fastest-growing private companies in the United States.

When I was a kid, I would grab Inc. magazine off the shelf at the local Publix and scour the list, studying the company names, stories, trends, ideas, and entrepreneurs behind some of the fastest-growing private companies in America.

Over the years, I’ve had the opportunity to create a few companies from scratch, as well as co-found a few more. Even after all these years, it’s still a thrill to build a fast-growing company and see it rank among private companies from across the country.

Here’s a list of the 2026 Inc. 5000 companies in Atlanta.

Inc. Rank	Company	3-Yr Growth	Industry	Leadership
14	Impiricus	11,691%	Artificial Intelligence & Data	Sandy Donaldson, Osama Hashmi
35	The Salon Suite Model	7,210%	Education	Patrice McKinney
127	Saleo	2,361%	Software	Justin McDonald, Daniel Hellerman
142	Carpool Logistics	2,201%	Logistics & Transportation	Michael Malakhov
149	Freestyle Snacking	2,103%	Food & Beverage	Nikki Seaman
171	Thrivemodal	1,928%	Human Resources	Oliver Ong
182	Document Crunch	1,888%	Construction / Software	Josh Levy
225	ZonPrep	1,521%	Logistics & Transportation	Kayvon Nazarian
234	My CPA Coach	1,459%	Financial Services	Krystal Standberry, Sherman Standberry
237	SCW.AI	1,432%	Software	Evren Ozkaya
269	Tractian	1,251%	AI & Data	Igor Marinelli
504	Trilogy Investment Company	684%	Real Estate	Jason Joseph
531	Heathos	655%	Insurance	Todd Baxter
537	Empify	647%	Financial Services	Ashley Fox
565	Anaptyss	617%	IT Services	Anuj Khurana
576	Cyble	609%	AI & Data	Beenu Arora, Manish Chachada
581	Art of Drawers	606%	Consumer Services	Allan Young
601	Financial Cents	578%	Software	Shahram Zarshenas
630	Granum	570%	Software	Mark Sedgley
640	Flock Safety	537%	Security	Garrett Langley
929	ketteQ	371%	Business Products	Mike Landry
953	We Mail America	363%	Advertising, Marketing & PR	Gary Pizzati
1,012	Cognosos	346%	Logistics & Transportation	Heath Thompson
1,035	Intown Golf Club	335%	Hospitality	Michael Williamson
1,238	ValidiFI	282%	Financial Services	John Gordon
1,308	AdvizorPro	269%	IT Services	Michael Magnan
1,351	Ruby-Collins	261%	Construction	Scott Cline
1,416	Advanced Tech Placement	250%	IT Services	Maggie Bray, Grace Denyer
1,478	RS Group	238%	Logistics & Transportation	Brent Staton
1,527	Manay CPA	229%	Financial Services	Burcu Bree Manay
1,558	Bellwood	225%	IT Services	Rob Kischuk
1,624	Docufree	214%	Software	Brad Jenkins
1,646	Vintage Modern	212%	Automotive	Chau Nguyen
1,671	Codoxo	207%	Healthcare & Medical	Musheer Ahmed
1,714	ChronicCareIQ	203%	Healthcare & Medical	Matt Ethington
1,777	Southworth PC	196%	Legal	Shaun Southworth
1,863	Southern Reins Logistics	186%	Logistics & Transportation	Jake Mathis
1,911	Cogitate	180%	Software	Arvind Kaushal
1,994	GOCare	172%	Software	Mike Roddy
2,056	Merit Financial Advisors	166%	Financial Services	Rick Kent, Kay Lynn Mayhue
2,181	Pye-Barker Fire & Safety	155%	Business & Corporate Services	Bart Proctor
2,279	LoadUp	148%	Environmental Services	Greg Workmon
2,359	Kahua	142%	Software	Scott Unger
2,386	Alloy	140%	Advertising, Marketing & PR	Raj Choudhury
2,420	Vantage Point Consulting	137%	IT Services	Krish Subbiah
2,447	20North Marketing	135%	Advertising, Marketing & PR	Connor Dunaway
2,590	Groth, Makarenko, Kaiser & Eidex	125%	Legal	Joseph Kaiser
2,626	Giant Sports Cards	123%	Consumer Services	Jon Butts
2,738	Canopy	116%	Software	Suzanne Lane, Steve Latham
2,864	Groundfloor	109%	Financial Services	Brian Dally
3,159	ImagineX	95%	IT Services	Shaun Bank
3,165	Protomiq	95%	Automotive	Jorge de Castro
3,287	TriData	90%	Financial Services	Christian Ranke
3,321	Tier4 Group	88%	Human Resources	Betsy Robinson
3,465	Dunamis Woman Enterprise	82%	Consumer / Education	Davetta Collins
3,515	PEPL	80%	Human Resources	Jennifer Vilines
3,785	TaxConnex	69%	Financial Services	Robert Dumas
3,793	Vayman & Teitelbaum	69%	Legal	Esther Vayman, Greg Teitelbaum
3,891	BeyondTrust Corporation	64%	Security	Janine Seebeck
3,913	Atlanta Divorce Law Group	64%	Legal	Sara Khaki, Shawna Woods
3,918	Procure Analytics	63%	Business & Corporate Services	Suja Katarya
3,983	Inteleca	61%	Computers & Technology	Paul Hogg
4,110	Innovien Solutions	56%	IT Services	Camryn Mastel
4,224	The Shelf	52%	Advertising, Marketing & PR	Lauren Jung, Atul Singh
4,265	Aggregate Singularity	50%	Software	Christy Williams
4,318	Community Construction Group	48%	Construction	Ross W. Haynes
4,363	Flex HR	47%	Human Resources	Jenny Morehead
4,486	YouDecide	41%	Insurance	Peter Marcia
4,687	WRK Marketing	31%	Advertising, Marketing & PR	Sesealy Owens
4,991	OTR Solutions	12%	Financial Services	Fritz Owens

Congratulations to all the entrepreneurs who made the list and are building dynamic, fast-growing businesses.

With all the talk of AI agents and vibe coding new software, one issue that keeps coming up is the system of record.

Historically, the system of record was the main software-as-a-service application a company used. Think Salesforce.com or HubSpot in CRM, Workday and Rippling in HR, and Pardot and Marketo in marketing automation.

As part of the SaaSpocalypse beatdown, followed by the slight improvement, one of the big ideas was that companies charging based on users or seats would come under pressure. If an AI agent is one seat but can do the work of 10 or 50 humans, the number of seats a company needs could go down dramatically over time.

Combine that with much better tools for building one-off applications and moving data from system A to system B, and there may also be less lock-in from legacy systems of record.

All of that might be true.

But there’s another idea that hasn’t been discussed enough: the potential for an entirely new system of record to emerge.

Imagine a startup that provides the backend, database, data lake, and underlying infrastructure, but also includes roles, groups, responsibilities, governance rules, workflows, required approvals, and clear designation of who owns each piece of data, who can change it, and who can’t.

Right now, when you vibe code a new CRM, go-to-market tool, HR application, or almost any other piece of software, the AI typically creates a new database with relatively limited rules around it. That becomes more complicated once multiple products and systems are reading from and writing to the same data. There are second- and third-order effects around permissions, ownership, governance, consistency, and control.

This creates an opportunity for a new startup.

It wouldn’t be an incumbent with existing pricing power and an innovator’s dilemma problem. Instead, it could provide a data store with a governance engine on top at a much lower cost than interfacing with a headless Salesforce.com or another legacy application.

Then, through open source libraries, great APIs, and excellent engineering, it could position itself so that the agents deciding which products and modules to use naturally select it as the system of record.

The goal would be to create a new industry-standard system of record that is AI-agent native, easy to drop into existing systems, compatible with applications that previously wrote to legacy systems, and available through a self-service freemium model without an expensive go-to-market motion.

For enterprise-focused entrepreneurs looking for a potential business idea, being the system of record has historically been incredibly valuable. It’s also clear that many legacy incumbents face the traditional innovator’s dilemma.

That creates an opportunity to build the next-generation system of record: AI-agent native, optimized for vibe coding, neutral across applications, easy for developers and agents to adopt, and priced like modern infrastructure instead of legacy enterprise software.