As I get older, I’m starting to forget everything. Tell me I have a meeting next week? It better be on my calendar. Need me to pick up pickles? Put it in a text. Time to go to the doctor? They better make house calls.

That’s why I’ve been thinking a lot about productivity devices that can record my day and then hand me a punch list, a summary, and a little help figuring out what I’m supposed to do next. That is what the Memoket Gem is trying to be.

The Gem is a futuristic little electronic lozenge, essentially a wearable recorder tied to an AI assistant. You press a button when you want to start recording, and it keeps going until the conversation ends. The company says it can record for up to 20 hours, which means you could feasibly charge it once a week depending on how much you use it.

When you open the app, your conversations are downloaded and analyzed for content and context. The device itself is small and fairly innocuous, which matters. Nobody wants to be the person who pulls out a giant recorder in the middle of a meeting. A wearable like this feels less intrusive, though, obviously, you should still be clear with people when you are recording them.

The hardware, however, is not really the point. Memoket’s main pitch is that it does more than summarize one meeting at a time. It tries to connect conversations across days, weeks, and projects, giving users a longer-term memory layer built from scattered client calls, meetings, voice notes, and random ideas that would otherwise disappear.

That makes the Memoket useful for founders, salespeople, consultants, operators, and anyone who spends a lot of time talking and does not want to manually organize notes afterward. The wearable can be worn as a pendant, clipped to clothing, used on the wrist, or attached to an Apple Watch. The company also says it now has desktop apps for Mac and Windows.

The service offers 300 transcription minutes per month for free, and the paid plan expands that to 1,500 minutes for $8.33 per month. It also integrates with Slack, Notion, Claude, ChatGPT, Google Calendar, Outlook Calendar, and Reminders, which means action items can move into your existing workflow instead of sitting in yet another app you forget to open.

In plain English, Memoket is trying to be a personal memory system for work and life. It records what happened, turns it into notes, pulls out tasks, and tries to connect the dots over time. For people who live in meetings, calls, errands, and half-remembered conversations, that could be pretty useful.

I tried the device over the last few days and I think it’s one of the most interesting productivity products I’ve seen in a while. Unlike Notion or Zoom’s call recording features, the Memoket Gem works in real life, in real meetings, which means you can take it anywhere, including spots where you’re without your laptop.

As you can see, the app creates action items and lets you search conversations that you’ve had, creating a trail from idea to idea. It’s a very clever system and worth the $179 price tag if you spend a lot of time in meetings. The introductory package includes a wristband that doubles as an Apple Watch attachment, allowing you to wear the Gem on the inside of your wrist. There is a pendant and pin solution as well but I wasn’t able to test those add-ons.

Arguably these things are going to get smaller and nearly invisible, rendering even this tiny hunk of electronics obsolete fairly quickly. That said, until that day comes, a tool like the Gem will definitely change how you view meetings, transforming them from snooze fests to action-item packed conversations. Plus it can remind you to go get pickles.

*record scratch* *freeze frame* Yep, that’s me. You’re probably wondering how I got here.

Yep, that’s me circa 1989. I was as nerdy then as I am now.

The reason I wanted to share that photo is because I’ve been thinking a lot about what I want to be when I grow up, besides an accordion player, and I think it’s time to put some of my skills to use for clients. For a while, I’ve been sitting on a new agency called Onfluence. The tagline is:

You’re Brilliant. Why Are You Still Invisible Online?

The goal is to help founders, CEOs, and industry experts turn expertise into influence by creating content and thought leadership around people who are doing amazing things. I’ve been doing this work for a few founders so far, mostly as a series of loose coaching gigs. Basically, we chat once a week for about thirty minutes, and I help with your Substack, blogs, press releases, media training, SEO/GEO, social media management, media outreach, and general marketing. I am working with my friend Neeraj Bansal who is on the operations side and between the two of us we have over 60 years experience in startups and entrepreneurship.

Thus far, I’ve helped folks build 25,000-reader newsletters, gain 500,000 Twitter followers, build a massive Discord audience, get great global press, and host dinners with journalists at major events. My goal is to be a coach, not a PR person or your full-time CMO. This introductory package is $1,000 per month, which feels like a reasonable amount in this economy. I want to help founders build, and I think this is a great way to do it.

Contact Me

I also have another offering that is a bit more complete. It includes about 22 pieces of content per month, including newsletter posts, LinkedIn posts, and TikTok, Instagram, and LinkedIn reels. For that, I’m offering an introductory rate of $1,500 per month. This is a little more in-depth, and I’d love to chat with folks who are particularly interested in this solution.

The bottom line? I want to use my skills for good and survive as a freelancer. If you’re interested in either package, email me at john@biggs.cc. I’d love to help.

I had one of my favourite conversations in a long time this week with writer and Full Bleed podcast host Arjun Basu.

We both came from the magazine world. We remember the days when magazines had millions of readers, editors could call a trend before it happened, and entire industries waited to see what would appear in next month’s issue.

Then the internet arrived.

Most people tell that story as if technology simply destroyed print. Arjun had a more interesting take.

He argues the first mistake wasn’t losing advertising. It was trying to make magazines behave like the internet.

“The internet spent all that time just being like magazines and newspapers,” he told me. “And then slowly the ad dollars started going away.”

That made me think.

Every new technology seems to convince the old one to abandon what made it valuable.

Magazines chased clicks.

Newspapers chased page views.

Television chased YouTube.

Now everyone is chasing TikTok.

Somewhere along the way we stopped asking whether we should.

One thing Arjun said really stuck with me.

“The publisher sort of forgot about the reader.”

When advertisers paid the bills, readers became a metric instead of the customer.

Today that’s changing again. The publications that are succeeding are asking readers to pay directly, which means they have to produce something worth paying for.

The audience is back in charge.

There’s another twist I didn’t expect.

Many of the people buying independent magazines today aren’t Gen X nostalgics trying to relive the 1990s.

They’re Gen Z.

Magazine shop owners are finding their stores filling up with people in their twenties who are making zines, buying beautifully printed magazines and treating them as social spaces instead of relics.

Maybe that’s because they grew up surrounded by screens.

Maybe holding something real has become the novelty.

I don’t think print will ever return to what it was.

Neither does Arjun.

“The days are over,” he said. “You are paying your penance, and I’m trying to bring it back.”

He’s probably right.

But perhaps that’s the wrong goal.

The future isn’t recreating the old magazine industry.

It’s taking what magazines were always best at, thoughtful curation, strong voices and memorable design, and building businesses around communities instead of advertising.

That’s a much harder business.

It also might be a much better one.

Cohen is the co-CEO of Made By Us Studios, a company trying to bridge Hollywood and the creator economy. On this week’s Keep Going, she made a simple point that explains why so much of the media business is changing.

“Every creator can become an influencer, but not every influencer can become a creator.”

That distinction matters.

An influencer rents attention. A creator builds intellectual property. They create stories, characters, formats and communities that people return to again and again. Instead of simply recommending products, they’re building entertainment businesses.

Some of the largest creators now attract billions of views every month. Their audiences rival traditional television networks, but without the overhead or the geographic limits. As Cohen put it, many creators have become media companies with a person at the centre instead of a corporate logo.

That shift is changing advertising as well.

For decades, brands paid millions to interrupt audiences with commercials. Today, many would rather become part of the content itself. Instead of producing a traditional advertisement, they’re giving creators the freedom to build stories that naturally include a product. When it works, viewers don’t feel like they’re being sold to. They feel like they’re watching the content they already came for.

Trust is what makes that possible.

“Trust is the only asset a creator cannot afford to lose,” Cohen said.

Creators speak directly to their audiences every day. They know what resonates because they receive immediate feedback through comments, views and engagement. That relationship is difficult for traditional media companies to replicate.

For anyone hoping to become a creator, Cohen offered surprisingly practical advice.

Don’t worry about expensive cameras or production quality. Start with authenticity. Figure out what makes your voice different and show up consistently. Today’s audiences often prefer content that feels genuine over something that looks overly polished. With AI lowering production costs even further, the biggest advantage isn’t technology. It’s originality.

One prediction stood out.

Cohen believes we’re moving back toward a model where artists own more of their work, similar to the United Artists era of Hollywood. Instead of platforms controlling everything, creators will increasingly own their intellectual property while using digital platforms as distribution channels.

Whether that prediction comes true or not, it’s clear the lines between Hollywood, YouTube, television and social media are disappearing.

The next major entertainment company may not begin with a studio lot in Los Angeles.

It may begin with someone holding an iPhone in their bedroom.

Starting and running a business can be one of the most rewarding experiences, but knowing when and how to shut it down is equally crucial. In this post, we’ll explore key insights from Dori Yona, CEO and co-founder of Simple Closure, on navigating the often daunting process of business closure. You’ll learn about the common pitfalls, best practices, and how to ensure a smoother transition during this challenging time.

This was an interesting interview and had a lot of info for folks who might be considering closing their businesses so I took some of the best practices from our conversation.

Understanding the Need for Business Closure

Every year, millions of businesses in the U.S. shut down for various reasons, from running out of cash to strategic pivots. Dori shares that many founders wait until it’s too late, leading to fines and penalties. The proactive approach involves assessing your business’s financial health and recognizing when it’s time to seek help. The earlier you start planning for closure, the better the outcome.

The Simple Closure Process

Simple Closure offers a streamlined process for shutting down a business. It starts with a quick onboarding, where you provide essential information about your company. This information is then analyzed in conjunction with public state databases to ensure no detail is overlooked. The result is a tailored shutdown plan that simplifies what is typically a complex process, reducing timelines from several months to just weeks.

Best Practices for Preparing for Shutdown

1. Don’t Go It Alone: Dori emphasizes that founders often underestimate the complexity of shutting down a business. It’s essential to seek professional help to avoid costly mistakes.

2. Budget for Closure: Many founders mistakenly believe they can simply run their business until it’s out of money and then shut down. However, shutting down incurs costs such as taxes and employee severance. Dori advises ensuring you have adequate funds available to cover these expenses.

The Importance of Knowing When to Shut Down

Recognizing the signs that it’s time to close your business can be difficult. Dori explains that some founders may resist shutting down even when financial indicators suggest it’s necessary. It’s crucial to evaluate your situation honestly and make informed decisions. This might involve using tools or resources that can help calculate the best time to close based on your business’s specific circumstances.

Conclusion: Key Takeaways for Founders

Shutting down a business is never easy, but with the right guidance, it can be a manageable process. Here are the primary takeaways:

- Be proactive and assess your business’s health regularly.

- Don’t hesitate to seek professional help.

- Ensure you have the funds necessary for a proper shutdown.

- Understand your liabilities and plan accordingly.

Frequently Asked Questions

What are the first steps to take when considering shutting down a business?

Start by assessing your financial situation and consulting with professionals who specialize in business closures to understand your options.

Are there costs associated with shutting down a business?

Yes, there are various costs, including taxes, employee severance, and potential fines, which is why it’s important to budget for the process.

How long does it typically take to shut down a business?

With Simple Closure, the process can be expedited from several months to just a few weeks, depending on the complexity of your business.

What should I do with my business’s assets when shutting down?

Services like Simple Closure can assist with monetizing your assets, ensuring that you get the most value out of your business before it closes.

Keith Wyche has had the kind of career that looks clean from the outside.

Bell. IBM. Pitney Bowes. Grocery. Walmart. Board seats. Books. Big jobs. Big teams. The sort of resume that makes people assume there was always a plan and that the climb was smooth.

It was not.

Wyche told me something on Keep Going that I think a lot of ambitious people need to hear. Early in his career, he was getting results, but he was not getting promoted. He was young, talented, and frustrated. So he gave his boss an ultimatum. Promote me in three months, or I will promote myself.

Three months later, he left.

Then someone told him the truth. He was a bull in a china shop. He got results, but he abused his people. He fought with finance. He fought with other teams. It was all about him, his team, and winning.

That stung. But it also changed him.

Wyche realized that he had been copying the leadership models he had seen before him. Hard, military-style management. Beat your chest. Push harder. Win. He was younger than many of the people he led, so he overcompensated. He thought leadership meant force.

It did not.

That was the beginning of a different kind of career. He worked with an executive coach. He looked at his blind spots. He started to understand where the behavior came from. Maybe it was imposter syndrome. Maybe it was not being heard earlier in life. Maybe it was just immaturity. Whatever the source, he had to face it.

That is the part people like to skip. They want the promotion, the title, the corner office, and the authority. They do not want the mirror.

Wyche’s new book, Uncommon Leadership: A Blueprint for Restoring Integrity, Trust, and People-Centered Leadership, comes from that same place. He said he wrote it out of disappointment with leadership today. His grandson asked him whether the failures he saw among pastors, politicians, and corporate leaders were what leadership really was. Wyche had to sit with that question.

His answer is no.

Somewhere along the way, he said, we moved away from servant leadership and toward self-serving leadership. The work became about the leader instead of the people. The quarterly return mattered more than trust. Power mattered more than integrity. Output mattered more than engagement.

But two things can be true. You can deliver results and still bring people with you. You can care about the business and care about the people doing the work. Wyche ran roughly 100 Walmart stores with 30,000 people reporting into his organization. If those people did not do their jobs, he could not do his. Leadership was not theoretical. It was operational.

That came through clearly in his Walmart story.

He joined Walmart in 2015, when Amazon was taking share and Walmart’s grocery business was under pressure. The company was built around stores, and there was real fear that e-commerce would cannibalize the core business. Wyche helped explain the change by telling the story of Sears. Sears had stores and a catalog. It had both the physical footprint and the home delivery model. Then it lost its way.

The point was not to scare people. The point was to connect them to the vision. Here is why change matters. Here is how you can help. Here is what happens if we do not move.

That is what leaders often miss. They announce the change, but they do not connect people to it. They talk about strategy, but not meaning. They talk about results, but not roles. People do not resist change only because they are stubborn. They resist change because they do not understand where they fit.

That lesson matters right now because AI is creating the same kind of fear. People worry about their jobs. They worry about their value. They worry that the thing they trained for will disappear.

Wyche does not pretend to know exactly where AI goes, but he has been through enough changes to know that humans are resilient. AI can handle administrative tasks. It can speed up work. It can process information. But it does not replace judgment, empathy, common sense, or the human touch. His line was simple. AI may know a tomato is a fruit, but common sense tells you not to put it in a fruit salad.

That is a good leadership test for the next few years. The companies that handle AI well will not just install tools. They will help people understand how to work with those tools. They will help people stay current. They will help people find new ways to add value.

Wyche’s advice to his grandson was the same advice he gives to people trying to build a career now. Be a continuous learner. Stay flexible. Do not lock yourself too tightly into one path. Look for ways to add value. Be willing to take the tough assignment nobody else wants.

He also made another point that stuck with me. Careers are no longer ladders. They are lattices. You may move up, sideways, or even slightly down to build the experience that gets you where you need to go. The old straight-line career is mostly gone. The people who keep going are the ones who keep learning.

That connects to one of Wyche’s earlier books, Good Is Not Enough. Performance matters, but it is not the whole equation. You also need exposure and perception. Are the right people aware of your work? Do they understand the value you bring? What is your brand inside the organization?

Nobody breaks through the glass ceiling alone, he said. Someone on the other side has to see you, appreciate your value, and pull you through.

That is not cynicism. It is reality. Good work matters. But good work hidden in a corner often stays there.

The lesson from Keith Wyche is not that success is about being polished, perfect, or politically smooth. It is about learning. It is about taking correction. It is about understanding that leadership is not something you perform over people. It is something you practice through people.

Early in his career, Wyche thought winning was enough.

Then he learned that how you win matters.

That is the uncommon part.

That’s the challenge Will Ruben is trying to solve with WorkClaw, a new product from Workmate Labs that turns AI agents into something closer to digital employees.

Ruben describes WorkClaw as “an AI team for your team.” Instead of asking users to learn prompt engineering or build complicated workflows, the platform lets them create AI teammates with specific jobs. A florist could train an AI to process invoices. A marketer could create a content assistant. An engineer could build a coding partner. The goal is not to replace workers, but to give every company access to the sort of specialised support that was once available only to large organisations.

The idea grew naturally out of Workmate, Ruben’s first product. Workmate focuses on scheduling, one of the most common tasks handled by executive assistants. After building an AI that could manage meetings and calendars, the company began looking at what else an AI teammate might be able to do. Recent advances in large language models made that expansion possible.

One of the most interesting parts of our discussion centred on a problem many AI founders rarely talk about. Traditional software is predictable. AI is not.

Ask a database the same question twice and you get the same answer. Ask an AI system twice and you might get two different responses. That creates challenges for companies trying to build reliable products.

Ruben compares the situation to earlier machine learning systems, including the recommendation engines that power social media platforms. The answer, he argues, is measurement, testing, and designing systems that can recover gracefully when things go wrong. If an AI makes a mistake, users need a way to correct it, and the system needs to learn from that correction.

That uncertainty also creates cost concerns. During our conversation I joked about running OpenClaw on a Raspberry Pi and accidentally generating a large OpenAI bill because a poorly configured process kept checking my email. Ruben believes those problems will become less significant as companies gain access to cheaper open source models and more efficient infrastructure. His view is that most business tasks do not require the most advanced models available today.

Perhaps the biggest challenge facing AI startups now is not technology but distribution.

Building software has become dramatically easier. Getting people to use it remains difficult.

Ruben said Workmate Labs relies on a mix of product-led growth, advertising, traditional sales, and good old-fashioned conversations with users. One tactic that has worked particularly well is identifying companies that visit the website, understanding who they are, and following up before interest disappears.

Looking ahead, Ruben says WorkClaw’s next step is reducing the friction involved in getting started. While the current product removes much of the technical complexity, users still have to decide what kind of AI teammates they want and how those teammates should behave. Future versions will offer ready-made AI roles, including executive assistants, marketers, engineers, salespeople, and operations staff, making it easier for businesses to start seeing value immediately.

The broader question is whether people want another tool or whether they want something that feels more like a co-worker.

Ruben is betting on the second option.

If he’s right, the future of software may not be a collection of apps sitting on a desktop. It may be a collection of digital colleagues working quietly in the background, each trained to do a specific job and each getting a little better over time.

That future is still taking shape. But products like WorkClaw suggest it may arrive sooner than many people expect.

Most AI tools are very good at text, code, and spreadsheets. Lium is focused on the messier stuff, the huge physical-world data sets that sit inside farms, climate labs, energy systems, logistics networks, and other operations where the answers are buried under terabytes of data.

Knutson, the CEO and co-founder, describes Lium as an “agent harness” or a cloud operating system for agents. The idea is to give language models the tools they need to work over large, complex data sets that they cannot handle well out of the box. Instead of asking a data scientist to build a pipeline every time someone has a question, Lium lets subject matter experts ask questions in natural language and then builds the tools and workflows needed to answer them.

Thill, co-founder and president, said the core user is often not a software engineer. It is the person who knows the domain, knows the data matters, and knows there are answers inside it, but cannot easily get them out. He gave the example of a farm operator working with soil reports, NOAA data, tractor data, and crop performance information. The operator may know something is off, but does not have the time or technical skill to combine all those sources into a useful answer.

That is where Lium is meant to fit. A user can describe what they want to know, and the system builds repeatable workflows around the data. Once those workflows exist, other people inside the organization can use them too. An analyst can build the tool, and a CEO can later ask a simple question that relies on the analyst’s work in the background.

That shared layer is one of the more interesting parts of the product. Knutson described work with the North Carolina Institute for Climate Studies, where scientists and researchers built tools inside Lium, then on-screen meteorologists could ask questions and get answers using the right climate data without needing to understand every data source underneath.

The company’s bet is not that AI replaces the expert. It is that AI needs the expert. Knutson said Lium is built around human-in-the-loop workflows because language models do not have enough training data to understand all the hidden patterns and details inside many physical-world data sets. The system has to know when to stop, ask the human for domain knowledge, and then turn that knowledge into a tool the system can use again.

That point matters because the obvious fear is job loss. If a person’s job is to build reports, what happens when anyone can ask Lium for the same report? Knutson and Thill argue that the expert becomes more valuable, not less, because the tool captures and scales their knowledge. Thill compared it to software engineers using AI coding tools. The tools make people more productive, and that can create demand for more work that was not worth doing before.

Lium is still early, but the founders say they are seeing strong interest. During private beta, around 50 groups worked in the platform. Now that it is public, the challenge is different. Instead of onboarding users by hand, the company has to explain the product clearly enough that people can find it, understand it, and get value without a sales call.

That is not easy, because Knutson and Thill say many potential users do not know this kind of system is possible. For Lium, the main competitor is not another startup. It is the belief that this kind of data is too hard to work with.

Fundraising followed a similar path. Knutson said early investors were skeptical because he and Thill did not have the usual Silicon Valley AI profile. They had startup experience, but not the standard AI pedigree. The company raised a smaller pre-seed round than it wanted, then came back after showing it could build things people did not think it could build. That proof changed the conversation.

The company spent roughly 18 months learning and building before going public. Knutson said this was not the kind of product where you can ship a tiny version and see what happens. If someone brings a terabyte of data, the system has to work. That meant building alongside design partners until the product was strong enough to handle real use.

Now the work is public. Lium is learning from users, tightening the funnel, and building around what people actually do with the product. The name, by the way, comes from language plus the suffix of physical elements, a nod to the company’s goal of connecting language to the physical world.

Most of us spend a lot of time thinking about what we want. A better job. More money. A nicer house. More freedom. Less stress.

Very few of us spend much time thinking about what a successful life actually looks like.

That question came up during a conversation with Perry Atwal, a lecturer at the University of British Columbia and author of the upcoming book Wisdom for Life. After teaching more than 20,000 students around the world, Atwal has spent years looking for patterns in the people who thrive and the people who struggle.

One of the most interesting things he said was that most of us are aiming too low.

He asked a simple question: when you have no reason to feel anything, where is your energy level? On a scale from one to ten, are you ready to go back to bed, or are you bouncing off the walls?

Most people, he said, live around a five or six.

His argument is that we should be trying to live closer to a nine or ten.

That idea stuck with me.

A lot of us assume that energy comes from success. Atwal sees it the other way around. Energy creates success. The people who excel are often the people who bring more than what is asked of them. If an assignment calls for three things, they deliver five. They are curious. They stay engaged. They keep moving.

His prescription is surprisingly simple.

Take care of your health. Walk more. Spend time outside. Do work you genuinely enjoy.

“I walk for two or three hours every day,” he told me. “Virtually every great thought I’ve had in the last twenty years has been on that walk.”

That sounds almost too simple in a world obsessed with optimisation, AI, and productivity hacks. But perhaps that is the point.

The most powerful part of our conversation came when we started talking about work and purpose.

Many people feel trapped. They sit in offices wondering whether this is all there is. They worry they picked the wrong career. They worry they missed their chance.

Atwal argues that the pressure to find the perfect path is largely self-imposed.

Previous generations might have held two or three jobs during a lifetime. Today’s workers may have ten or twelve jobs and move across multiple industries. The first job does not have to be the perfect job. It only has to be the next step.

He also believes we underestimate the power of perspective.

One example from the interview has stayed with me.

He talked about cleaners.

Some people might look at a cleaning job and see failure. The happiest cleaners he knows see something completely different.

They see buildings that people want to enter because of the work they do. They see value created. They see contribution.

The job is the same. The story they tell themselves is different.

That idea feels especially important right now.

We live in a moment where every headline seems designed to convince us that the future is bleak. Economic uncertainty. Political conflict. AI replacing jobs. Constant disruption.

Atwal’s response is not to ignore reality. It is to choose where to focus your attention.

“The only constant really is change,” he said.

That may be the closest thing to a universal truth.

The people who flourish are rarely the people who predict the future correctly. They are the people who adapt. They keep learning. They develop skills that transfer from one job to another. They stay curious.

They also let go.

Let go of old habits. Let go of old assumptions. Let go of the idea that your life must follow a script.

Atwal even applies that philosophy to his closet. If he hasn’t worn something in two years, it’s gone.

The same rule probably applies to a lot more than clothes.

If there was one lesson I took from our conversation, it was this:

Success is not a destination. It is a way of moving through the world.

Take care of your health. Do work that matters to you. Surround yourself with positive people. Focus on your strengths. Help others when you can.

The details of your career will change.

The technology will change.

The world will change.

The question is whether you will keep going.

Hi,

A quick reminder to the Keep Going community.

I’m trying to return to journalism full time, both here and at Resilience. That means I need paying readers. I have a family to support and a small dog named Nina who eats more than you’d think.

Here is the reality:

Startup journalism is collapsing. Reporters are leaving the field. Most coverage has turned into lightly edited press releases written to please investors and founders. The hard questions rarely get asked.

I’m trying to do the opposite.

At Keep Going I want to publish original reporting, real founder interviews, sober analysis, and clear takeaways you can actually use. No pay-to-play. No sponsored nonsense. Just reporting.

But that only works if readers pay for it.

So here is the ask.

Subscribe now and I’ll give you 20% off for life. That’s $40 a year to help support real entrepreneurial conversations with real CEOs and researchers.

Get 20% RIGHT NOW

If you read Keep Going and it helps you think about startups, technology, or the future of this industry, please support the work. Paid subscriptions let me stay independent, cover difficult stories, and keep writing without answering to advertisers or investors.

This is a one-man newsroom. I’m doing everything I can to make it worth your time. I’m interviewing fascinating people like Patricia Martin (whose insights made me cry), Kevin Gaskell who turned around Porsche, and thinkers like Dr. Rod Berger.

But independent journalism only survives if readers decide it should.

I love startups and I love honest conversations. I think you do, too. I will share this reminder about once a month. If Keep Going has helped you think, build, or avoid a mistake, please help me keep it going. Thank you.

That’s the challenge Will Ruben is trying to solve with WorkClaw, a new product from Workmate Labs that turns AI agents into something closer to digital employees.

Ruben describes WorkClaw as “an AI team for your team.” Instead of asking users to learn prompt engineering or build complicated workflows, the platform lets them create AI teammates with specific jobs. A florist could train an AI to process invoices. A marketer could create a content assistant. An engineer could build a coding partner. The goal is not to replace workers, but to give every company access to the sort of specialised support that was once available only to large organisations.

The idea grew naturally out of Workmate, Ruben’s first product. Workmate focuses on scheduling, one of the most common tasks handled by executive assistants. After building an AI that could manage meetings and calendars, the company began looking at what else an AI teammate might be able to do. Recent advances in large language models made that expansion possible.

One of the most interesting parts of our discussion centred on a problem many AI founders rarely talk about. Traditional software is predictable. AI is not.

Ask a database the same question twice and you get the same answer. Ask an AI system twice and you might get two different responses. That creates challenges for companies trying to build reliable products.

Ruben compares the situation to earlier machine learning systems, including the recommendation engines that power social media platforms. The answer, he argues, is measurement, testing, and designing systems that can recover gracefully when things go wrong. If an AI makes a mistake, users need a way to correct it, and the system needs to learn from that correction.

That uncertainty also creates cost concerns. During our conversation I joked about running OpenClaw on a Raspberry Pi and accidentally generating a large OpenAI bill because a poorly configured process kept checking my email. Ruben believes those problems will become less significant as companies gain access to cheaper open source models and more efficient infrastructure. His view is that most business tasks do not require the most advanced models available today.

Perhaps the biggest challenge facing AI startups now is not technology but distribution.

Building software has become dramatically easier. Getting people to use it remains difficult.

Ruben said Workmate Labs relies on a mix of product-led growth, advertising, traditional sales, and good old-fashioned conversations with users. One tactic that has worked particularly well is identifying companies that visit the website, understanding who they are, and following up before interest disappears.

Looking ahead, Ruben says WorkClaw’s next step is reducing the friction involved in getting started. While the current product removes much of the technical complexity, users still have to decide what kind of AI teammates they want and how those teammates should behave. Future versions will offer ready-made AI roles, including executive assistants, marketers, engineers, salespeople, and operations staff, making it easier for businesses to start seeing value immediately.

The broader question is whether people want another tool or whether they want something that feels more like a co-worker.

Ruben is betting on the second option.

If he’s right, the future of software may not be a collection of apps sitting on a desktop. It may be a collection of digital colleagues working quietly in the background, each trained to do a specific job and each getting a little better over time.

That future is still taking shape. But products like WorkClaw suggest it may arrive sooner than many people expect.

Reid is the CEO of Claer AI. The product is an AI-driven supplement regimen builder that asks for your health profile, matches it against a large library of peer-reviewed studies, then turns the recommendations into a practical plan, starting with sachets you can mix, and aiming later at a single personalised powder. He describes it as using AI like a nutritionist, then following that logic through a supply chain he already knows well.

His origin story is straightforward. Reid says he built and sold a social media analytics company to Comscore, then later ended up running one of the world’s largest supplement companies as part of a small executive team. That role changed his view of supplements, not as gym culture products, but as widely applicable compounds with strong safety profiles and real evidence behind them. He uses his own experience as the hook, after adding basic products like protein and creatine, he says he saw a clear change in strength and mobility as he aged.

The gap he wants to fix is trust and confusion. Reid calls the industry large but fragmented, and he points to consumer confusion as a driver. His claim is that people do not stick with one brand because the space feels like a Wild West, and they worry about doing something wrong or wasting money. Claer’s AI is meant to create a long-term relationship that adapts over time, including using biometrics from wearables and adjusting the regimen so users do not have to think about it constantly.

The most concrete feature he described is interaction checking. A common fear is that a supplement will clash with a medication or another intervention. Reid says Claer uses a “currently updated” evidence base to flag these issues, and he thinks that capability has applications beyond supplements, especially anywhere medication regimens shift often.

On funding, Reid says the company started self-funded, went through the ERA accelerator in New York, and that the health tech environment is active enough that fundraising is not the core problem. He frames the business model as bundles with solid margins and higher cart values, plus better retention because of the personalised front end. He also splits the company into two stages, first prove the commerce and retention dynamics, then raise larger funding later to personalise the manufacturing itself and deliver the single powder vision.

Reid also made a broader point that fits the Innovators beat. He argues that AI lowers the cost of running an “antiquated” industry by replacing a stack of specialised SaaS tools across the whole value chain. He says that in his prior role he spent millions per year on specialised software, and he expects a large share of those tools to become unnecessary as teams build from basic AI primitives and open source components.

He described the early internet as directed. People knew what was missing. They wanted communities, comments, and places to post work, and they built them from scratch because the infrastructure did not exist yet. Now, he says, you can recreate 95 percent of those platforms in a weekend. The hard part is not building the tool, it is making it matter.

That is where his argument gets uncomfortable. Virality used to ride on something raw and human, and he thinks AI breaks the default assumption that what you are seeing is real. His view is that we are moving into a world where you should assume media is inauthentic until it is proven otherwise. That shift changes what spreads, what people trust, and how creators feel about putting work into the world.

Layer is his response. It is a hardware company, a digital art display built to treat generative and kinetic art like fine art, not like a TV on a wall. He told me the idea grew out of an identity crash after leaving DeviantArt, and a simple desire, he wanted the best digital art on his own wall, presented correctly. He went looking for a product that did it, and he says he could not find one, so he built it.

He also does not sugarcoat how hard hardware is. He told me getting a manufacturing partner is harder than raising venture capital, because the manufacturers that can actually deliver are not built for startups, and you have to earn your way into their calendar. That challenge is part of what pulled him back into building in the first place. He missed meeting people, the artists, the founders, the operators in labs, the whole human mess that comes with making something real.

The Keep Going part of this episode is not “follow your passion.” It is more specific. Angelo is making a bet that digital art is going mainstream, and that the people who will survive this AI wave are the ones who adapt their craft to what the medium is good at. He said still images should often be printed, because printing is already excellent. Displays should be used for work that moves, especially generative work that does not loop in a way your brain gets tired of. He thinks that kind of work will define the century.

He is not naïve about the cost. He said illustrators are suffering and that many jobs are gone, and he widened it to the broader creative class, designers and builders getting hit by tools that shrink teams overnight. Still, he ended with the only kind of optimism that counts, the practical kind. Creative people adapt. They always have.

On this episode of Innovators, I spoke with the SingFit co-founder and CEO about how her company is using therapeutic music to help people with dementia, traumatic brain injuries, and speech loss. The idea sounds almost deceptively simple. People who lose the ability to speak can often still sing. Music activates multiple regions of the brain at the same time, creating pathways that normal speech sometimes cannot access.

SingFit turns that principle into software.

The platform recreates part of what music therapists do in clinical settings. Songs include lyric prompts, guided vocal tracks, and structured timing designed to encourage participation and cognitive engagement. The result is something that can be used not just by trained therapists, but by caregivers, nursing assistants, and families at home.

Francine said the company now operates in more than 10,000 skilled nursing and senior living centers across the United States. The company recently launched a caregiver-focused version with AARP aimed at helping families support loved ones at home.

One of the more interesting parts of the conversation was how deeply personal the company’s origin story is. The original idea came from Francine’s father, an inventor and former opera student who was fascinated by the role of lyric prompters in live performance. He imagined a system that could feed people lyrics in real time long before the technology existed to build it.

Years later, Francine’s brother became a music therapist after seeing a friend recover from a traumatic brain injury and emerge from a coma mouthing the words to “Wish You Were Here.”

That combination of therapy, family history, and technology became the foundation for SingFit.

Francine also made an important point about startups in healthcare and assistive technology. Too many founders start with technology instead of problems. Her advice was direct. Find a real problem first, then build the system around solving it.

In SingFit’s case, the company focused on one issue inside dementia care: social isolation. Patients often begin withdrawing socially as their condition progresses, which can accelerate decline and increase care costs. The platform was designed to create engagement, connection, and routine through music.

The broader issue she kept returning to was aging. Dementia care, caregiver support, and cognitive decline remain massively underserved compared to other parts of healthcare. Francine pointed out that only a handful of dementia drugs have been approved over the past century while cancer treatments continue advancing rapidly.

Music may not solve dementia. But the company is betting that engagement, memory, rhythm, and emotional connection can improve quality of life in ways that medicine alone often cannot.

And honestly, there is something refreshing about hearing a founder talk about care instead of scale for once.

Success is rarely a clean break. It is usually a slow crawl out of fear.

On this week’s episode of Keep Going, Melissa talks about leaving abuse, learning how to speak up again, and building an event planning business after losing everything.

“I believed that I was nothing,” she said. “I believed that someone else had to control my mind because that was what I was told for over 17 years.”

That damage does not disappear overnight. Melissa described the strange process of learning how to trust herself again. First she decorated rooms for family and friends. Then she started charging for it. Then she had to learn something even harder, valuing her own work.

“Doing it for free was the easy part,” she said. “When you was trying to charge for it, it became a bit of a challenge.”

What stood out in the conversation was how practical her advice became. There was no fantasy about instant success. She talked about systems. Contracts. Pricing. Schedules. Learning skills properly instead of pretending you already know everything.

When she started her decorating company, she signed up for classes because she wanted to understand the work deeply. “Don’t just wing it,” she said. “Learn the industry.”

Then the pandemic arrived and destroyed the in-person event business almost overnight. Instead of treating it as the end, she pivoted into virtual events, books, speaking, and media work. That shift became another lesson. The thing that feels like collapse is sometimes just a forced change in direction.

One of the strongest parts of the interview came when Melissa described being a single mother with no place to live. She talked about asking for help, finding an apartment she did not want but turning it into a home, and writing down what she wanted her future to look like even when nothing around her matched it yet.

That mattered because her story is not really about motivation. It is about momentum.

She believes people wait too long for confidence before they act. Her argument is almost the reverse. You move first. Confidence follows later.

“Don’t wait for everything to be perfect for you to take that step,” she said. “You will stumble. Forgive yourself for stumbling. And keep going.”

Melissa’s upcoming memoir, The Life I Designed, comes out in October. The title fits the conversation perfectly. Her life was not handed to her in a finished form. She had to build it piece by piece, often while exhausted, scared, and unsure of what would happen next.

A lot of people think reinvention belongs to younger people. Melissa’s story argues the opposite. Reinvention belongs to anybody willing to keep moving after the world tells them to stop.

You can check out all of Melissa’s work on her jam-packed website and book some time with her here.

Before he built six companies, before the bestselling books and the keynote stages, he was teaching biology and physics. He had an idea for an airplane design and wanted to turn it into a business. The problem was simple. He had never taken a business class in his life. He was scared of failing.

But he realized something else scared him more. He did not want to become an old man who never tried. The fear of regret outweighed the fear of failure.

That idea sits underneath almost everything he talks about now. Most people think entrepreneurs are fearless. They are not. They are just more afraid of standing still than moving forward.

Burrus also said something I had never heard framed quite this way before. He said entrepreneurs usually have success metrics but almost never have failure metrics.

He gave the example of hiring someone you know is not right for the role. Deep down you know it after a week, but you spend months trying to fix it before finally letting them go. You already saw the failure coming. You just delayed acting on it.

That applies to almost everything. Businesses. Projects. Careers. Relationships. We hold onto broken things because motion feels harder than denial.

A lot of the conversation focused on AI, which Burrus sees less as a replacement for people and more as an amplifier. He argued that companies are making a mistake by focusing only on the tools. First comes mindset, then skillset, then toolset. Most firms skip directly to the software and never rethink how they actually work.

He also pushed back on the panic around AI replacing everyone. His point was simple. Jobs have always changed. The danger is not the technology itself. The danger is pretending your current role will stay frozen forever.

One line stuck with me. “You can only coast downhill.”

That feels true right now. A lot of people are waiting for stability to return before they adapt. But the stable version of the world they remember is probably not coming back. The people who do well over the next decade will likely be the ones willing to relearn things while everyone else argues online about whether change should exist at all.

Burrus is relentlessly optimistic, sometimes almost aggressively so. Normally that kind of thing annoys me. But his optimism is grounded in systems and patterns, not motivational slogans. He studies technology, demographics, and behavior and asks what becomes inevitable once those things start moving together.

His broader point was that most people underestimate the future because they spend too much time staring at the present. Burrus is a unique thinker in that he sees where the puck has gone and where it is going… years and years into the future.

You can check out his books here and hire him at his website.

On this episode of Innovators, I spoke with Judickas, VP of Strategic Alliances at IPXO, a company building what is essentially a marketplace for internet infrastructure. IPXO leases IPv4 addresses from companies that have large unused reserves to startups, hosting firms, telecoms, and AI companies that need them to operate. It sounds obscure at first, but the deeper we got into the conversation, the more it started to resemble real estate.

Back in the early days of the internet, engineers assumed 4.3 billion IPv4 addresses would be more than enough. Instead, the modern internet burned through them. Companies that arrived early, IBM, Apple, major telecoms, ended up sitting on massive blocks of addresses, while newer firms often struggle to get even a few hundred.

Judickas explained how IPXO emerged from that imbalance. The founders originally ran a hosting company and began leasing their own unused IP addresses to customers. Demand exploded almost immediately. That experiment eventually became a global marketplace that now manages millions of addresses.

What makes the story interesting is that the business is not really about software alone. It is about trust. Judickas described the challenge of convincing large enterprises that the IP addresses sitting idle on their books could become a revenue stream. In many cases, companies did not even realize those assets had value.

We also talked about the strange half-finished migration from IPv4 to IPv6. For decades, the industry has talked about replacing IPv4 entirely, yet much of the internet still depends on it. Judickas sees a world where both systems coexist for years to come, especially as AI systems and connected devices increase demand for network infrastructure.

The conversation eventually turned toward AI. Every AI endpoint needs connectivity. Every distributed system needs addresses. Judickas believes the next wave of infrastructure demand will come not from traditional hosting companies but from AI firms gathering data, training systems, and deploying agents across the web.

There is something almost invisible about this market. Most people never think about the plumbing underneath the internet until it starts running short. But scarcity changes behavior. IPXO is betting that IP addresses will increasingly behave less like technical resources and more like financial assets, leased, managed, and traded much like commercial property.

It sounds harsh at first. But the more he talked, the more it made sense.

Gillen’s life did not begin in anything close to stability. He described being abandoned as a child in Ireland during the violence of the Troubles before being moved to London’s East End, where he was eventually pulled into organized crime at a young age. He spent years in prison, including long stretches in solitary confinement.

Today he runs companies, advises brands, works in television and film, and moves through circles that would have seemed impossible from the position he started in.

What interested me most was not the redemption arc. Everybody loves a redemption story because it makes life feel orderly. The thing that interested me was how practical his thinking is now. He talks less like a motivational speaker and more like somebody who learned survival the hard way and simply translated it into business.

At one point he described entrepreneurship as the most powerful form of personal growth he knows. Not because business is glamorous, but because it forces you to confront yourself constantly. Your habits matter. Your discipline matters. Your ability to finish things matters.

That word kept coming up. Finish.

He said many people are not finishers. They get excited at the beginning, panic during the middle, and disappear before the hard part is over. Gillen’s view is that finishing is not really about talent. It is about deciding there is no acceptable path backward.

He also had a line that felt brutally accurate. “Challenge is only growth trying to happen.”

Most people interpret resistance as a sign to stop. A failed deal, a bad quarter, rejection, debt, embarrassment. His argument is almost the opposite. Resistance is often proof that you are finally pushing against something real.

There was also something interesting in the way he talked about criminal life. He did not romanticize it at all. In fact he sounded exhausted by it. He described it as people searching for survival, belonging, and identity in the wrong place. The money and status look attractive from the outside, especially when you are young and broke, but he was clear that it only leads to bad endings.

The strangest part of the conversation was hearing him move seamlessly between stories about prison and stories about working with Sean Bean and Orlando Bloom on television projects. But maybe that is the point. People are rarely one thing forever. A life can split hard in another direction if somebody decides to keep moving long enough.

And honestly, that may be the real theme of Keep Going anyway.

Not perfection. Not reinvention. Just motion.

Some people stop where they started. Others refuse to.

Next week I’ll be helping to host the Generated Awards, the first AI video awards show on the planet. It’s going to be an amazing time with AI video creators, marketers, and artists who will join together to celebrate a brand-new medium of expression. I’d like you to attend. There are two options. Feel free to RSVP to both.

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Lu is the co-founder and COO of Memoket, a startup building what she describes as a “context layer” between the physical world and AI. The company’s product combines a wearable recording device with software that tracks conversations and projects across time. Instead of generating isolated meeting summaries, Memoket tries to reconstruct relationships, decisions, and discussions as they evolve.

“The core idea is not just summarizing one meeting after another,” Lu said on The Innovators podcast. “What we want to provide is the full picture.”

The system works by recording conversations throughout the day, then using AI to organize and connect information over weeks or months. If a salesperson meets a client multiple times, the AI can track changes in requirements and priorities. If a founder interviews ten customers, the software can compare responses automatically instead of forcing someone to read ten separate reports.

Lu said the idea came from frustration with current AI note-taking tools, which often treat every conversation as a separate event.

“In the past, the AI note takers would give me ten reports,” she said. “I had to read through them and piece everything together myself.”

The company also sits in the middle of a growing debate over AI, privacy, and always-on recording. Lu argues that AI systems need better access to real-world context if they are going to become more useful over the long term. At the same time, she acknowledged the sensitivity of recording personal information and said users control whether data is uploaded or analyzed.

One use case Lu described involved helping her mother keep track of conversations with doctors.

“My mom is not able to repeat all that information to me word by word,” she said. “So I have her record the conversation.”

Unlike many AI tools built entirely around smartphones or laptops, Memoket also includes custom hardware. The wearable device can be worn as a wristband, pendant, or clip and allows users to start recording with a single button press.

Lu said the hardware became necessary because many important conversations happen away from screens.

“Sometimes I’m driving and an investor calls,” she said. “I wish I could record that, but I’m not going to risk my life reaching out to the phone.”

Memoket is currently recruiting beta users ahead of launch and they just launched their ProductHunt where you can find more info.