At a glance: AI has made competent work cheap. Knowing which work is worth doing stays expensive.
AI has driven the cost of competent work close to zero. What it has not touched is the harder thing, knowing which work actually matters and which problems are worth solving.
A sustainable independent practice protects that judgment and builds systems to carry everything else.
Three guests from the Wisepreneurs podcast show what that looks like in practice:
- a conversation that demonstrates your expertise before you propose paid work,
- a way of generating client conversations that replaces the feast and famine cycle, and
- an automation setup resilient enough to keep a business running through two months away.
You can't sell knowledge anymore, but you can sell wisdom. You can sell insight. You can sell a deep understanding of something.
Jon Younger
Building a sustainable independent practice has become a different problem than it was five years ago. AI has driven the cost of competent work close to zero, while the cost of understanding which work is worth doing stays high.
A practice that lasts protects the one thing AI cannot replicate, the judgment you have built through years of real work, and puts reliable systems around everything else. Three conversations from the Wisepreneurs podcast show how this works:
- Jon Younger on why experienced professionals keep their value,
- Melisa Liberman on winning the right clients, and
- Anna Burgess Yang on building a practice that survives a crisis.
Why competent work got cheap and judgment did not
Jon Younger, a Forbes contributor who writes on the open talent economy, describes the career stages AI disrupts: earning trust as a newcomer, becoming expert at something the organisation values, moving into mentoring others, and finally shaping the culture and the work environment.
The disruption lands on stage two. The value of technical knowledge has always faded over time. AI has sped that up. Knowledge that once took years to build is now available to anyone with a well-constructed prompt.
The way I see it, this is the heart of the Wisepreneur's situation. What AI makes cheap is procedural competence, the ability to follow an established process and produce a sound result. What stays scarce is the discernment you assemble through years of sustained practice.
Over many years your brain has been storing patterns from every problem you have worked on, and those patterns let you read a situation and see what matters, work out which method fits which case, and walk into a tangled problem and form a view based on hundreds you have seen before.
Younger gives a specific example. Advising on a corporate acquisition, he reframed it as a "compassionate acquisition" to manage what employees expected would change. Nobody could look that up. It's his discernment about organisational psychology and change, built from years of watching these efforts succeed and fail.
He uses the Gleicher change formula (change equals dissatisfaction plus vision plus first steps, divided by the cost of change) as a practical read on where change efforts break down:
As leaders we get so excited by the vision and the first steps that we hardly ever think about the cost of change and the dissatisfaction for 90% of our organisation.
The positioning point is sharp. If your value rests on knowledge AI can reproduce, your rates face constant downward pressure. If your value rests on discernment that only real practice builds, you sit in a position that grows more valuable as the routine layer gets commoditised.
The question worth sitting with is whether your practice is built to make that difference visible to the people who need your depth.
How systems protect the work only you can do
In the companion article on make-or-buy decisions Make or buy is a cognitive decision, not just a cost calculation I argue that what you delegate is really a decision about your own thinking: what keeps the expertise that makes you valuable, and what can safely go elsewhere.
Melisa Liberman, a coach for independent consultants, and Anna Burgess Yang, a writer who built her practice around automation, both show what that looks like day to day, though neither puts it in those terms.
Liberman coaches consultants to treat business development as their most important client. With three active engagements, your own business is the fourth, and it gets the same protected time.
Her Business Development Formula replaces hoping referrals turn up with working backwards from the number: start with your revenue goal and find the quantities you need at each stage.
A $500,000 target at a 50% close rate means a million-dollar pipeline. Break that into your average contract value and the number of deals, and the abstract becomes concrete. You need a specific number of conversations this month to produce a specific number of opportunities.
Liberman's formula turns a revenue goal into the number of conversations to book this month.
This matters because it separates the part only you can do, the diagnostic conversations where your experience generates real insight, from the supporting machinery, the pipeline tracking, the scheduling, the follow-up, that makes sure those conversations happen. The conversations need your depth. The system that makes them happen does not.
Yang shows the same separation under real pressure. Diagnosed with a brain tumour that needed surgery with an uncertain outcome, she had six weeks to get her business ready to run without her.
Her answer was systematic automation:
- Zapier flows she could feed by dictating into her phone, an automation that sent transcripts to an editor, then another that passed the finished content to her virtual assistant to publish,
- Pre-scheduled social posts,
- Guest contributions to her newsletter,
- Publishing that ran itself.
There is a useful way to picture an independent practice as four parts.
- The work only you can do, your thinking, your editorial judgment, your voice, stays yours.
- The automated layer, Zapier, ChatGPT for sorting, scheduling tools, handles the routine.
- People you can hand work to, an editor, a virtual assistant, supply human judgment that does not have to be yours.
- And the relationships you have built, friends and clients, hold the whole thing steady.
This is the Neo-Shamrock model I use in the Wisepreneurs framework, and Yang's preparation maps onto it almost exactly.
Yang's preparation, mapped to the four parts of a practice. When her own part shrank to voice dictation, the other three kept working.
When her own part was reduced to its smallest form, voice dictation, the other three kept going. The result, in her words:
All I had to do was dictate into my phone and with help of two people and automation, my words got out into the world.
Her expertise kept operating, stripped back to its essential core, because systems carried everything that did not need her specific judgment.
How a diagnostic conversation wins the right clients
David C. Baker, whose work on the business of expertise I draw on often, separates the vendor from the expert.
- A vendor pitches services and competes on price and availability.
- An expert demonstrates depth and gets sought out for judgment that cannot be copied.
Liberman's approach to winning work sits firmly in the expert's room.
She reframes the whole sales process:
If you can engage your consulting skills ahead of time by asking really good questions to understand and help people to see where they may have blind spots, that's the most powerful way to sell.
Her "foot in the door" offer is a 45-minute diagnostic conversation. You ask questions and produce a short report showing the opportunities and the constraints. No charge for that first engagement. The value comes from showing your judgment at work before you propose anything paid.
This is the cost of understanding applied to winning clients. The cost of understanding is a phrase I take from Karl Fast's research, which has been an important influence on how I think about Wisepreneurs.
Your prospect is trying to work out, at the lowest effort possible, whether you have the depth to help with their particular problem. A diagnostic conversation lets them feel your judgment in action. After that they do not need persuading.
They need to confirm what they have already seen.
Melisa ran into exactly this when hiring a fractional COO:
She asked me the most simple question about my process and I hadn't even thought about it. That's what made the difference, knowing she knows what she's talking about.
She did not pitch. She showed what she could do through the quality of one question, drawn from patterns built across hundreds of prior engagements, and it did what no proposal could.
Younger also shows expert positioning in knowing when to walk away. Asked to join a consulting team where the CFO rather than the CEO would make the hiring call, he declined, because the CEO cannot grow if someone else makes the key decisions for them.
The CFO's reply:
I like the logic. I hate the answer.
Younger adds:
Thank goodness I didn't need the money at that moment.
That read on which engagements serve both sides is a call no AI can make for you. It comes from years of watching leadership play out.
Liberman sees consultants struggle here because they confuse expertise with credentials:
So many of us have imposter syndrome. People with PhDs, people with all the letters behind their names.
Her exercise: write down every way you have done something close to what you are proposing, paid or unpaid.
They come back with pages and pages. We get amnesia.
Your expertise works quietly and produces good calls without always being able to explain itself, which is the same articulation gap I wrote about in the Crafting Your Professional Monopoly article. Naming what you do is its own skill, and it is the one that builds a client's confidence.
How to use AI without handing over your judgment
All three guests treat AI as something that lifts what you can do rather than something that does your thinking for you. This is the augmentation idea from the make-or-buy article: let AI raise your output while you stay engaged with the substance.
Younger frames it through how organisations divide their work. He names three kinds: strategic work, the source of competitive advantage; support activities like finance, HR and marketing that enable the core; and essential support, work you would remove or automate if you could.
Drawing on research from the RBL Group, he puts essential support at roughly 65% of the work in large companies.
His former employer had 300 people in payroll. He doubts anyone is left in payroll now.
That opens two doors for wisepreneurs. Organisations need help automating that 65% well, which takes the judgment to tell genuine routine from strategic work that has been miscategorised as routine. And the professionals who used to do the routine work now face AI competition, which pushes real expertise upstream into the scarce, higher-value position.
Yang uses AI for efficiency inside clear limits:
ChatGPT runs through blog posts via Zapier and picks categories. Is it right 100% of the time? Probably not. Is it right 90% of the time? Probably. And that's good enough for the time saved.
AI drafts LinkedIn posts from her new articles, which she then edits. It turns voice notes into publishable text.
Her judgment stays the gate:
They do not go out as ChatGPT wrote them. They're not good, even with all the training in the world. The draft is there so I can edit and publish.
Liberman sees the same line with her clients:
I can tell when they didn't even read what AI generated. This is so generic.
AI handles research, first drafts, and routine tasks. Your judgment decides which outputs fit a specific client. A consultant who publishes raw AI output is back in the vendor's room competing on volume. A consultant who treats AI output as raw material for their own thinking stays in the expert's room.
There is a quieter risk here too. Each time you accept AI output without staying engaged with the problem, you lose a little of the friction that keeps your judgment sharp.
Researchers Caosun and Aral call this slow erosion the augmentation trap, and it can happen even when you use AI for support rather than replacement.
Yang's habit is the guard against it. She uses AI to draft, then always edits, so she stays in contact with the substance even when the routine layer runs itself. The edit is quality control, and it is also how she keeps the judgment that gives her writing its voice.
Yang names the test plainly:
People can generate LinkedIn posts or blog posts with speed and it's always going to be generic because AI is always just a regurgitation of everything else on the internet. It's not original thought. Having an opinion or a voice or something that makes you different, that's what makes you stand out.
AI makes competent output cheap. The judgment, the point of view, and the understanding that make professional work worth reading come from somewhere else.
Building a practice that survives a crisis
Yang's experience is a stress test for how a practice is built. From diagnosis to surgery she had six weeks. She stopped client work three weeks out because she was too stressed to do her best work, and in the end she did not work for two full months. Her practice came through because she had built three kinds of resilience at once.
Financial resilience: "
When I first started working for myself, I immediately started squirreling away money. Anytime I had a really good month, I would shove money in a savings account.
A practice built around something only you can do carries a built-in vulnerability. The one thing it depends on is you being able to work.
Operational resilience: systems that kept producing value without her constant input. The automation, the pre-scheduled content, the editorial flow that reduced her part to voice dictation. The four-part structure was already in place, so when her own part was compromised, the rest kept going.
Relational resilience:
People made guest contributions so I didn't have to keep writing. Clients said they were willing to wait for me if I wanted to keep working with them.
The relationships she had built through steady generosity returned the favour exactly when it counted.
Liberman builds the same resilience by a different route. Her Business Development Formula, by keeping pipeline activity steady and predictable, heads off the feast and famine cycle that makes a practice fragile. With consistent lead generation producing a steady flow of opportunities, an unexpected pause does not sink you. The relationships and opportunities can wait, because they came from an ongoing system rather than last-minute scrambling.
Younger points to the network. He talks about building "hunting parties for work," collaborations that turn up opportunities you would never find alone. His advisory boards, his Forbes column and his professional networks keep generating value whether or not he is chasing new work on any given day.
Designing your practice around the work that needs you
Yang's health crisis forced a question every Wisepreneur should ask before circumstances force it:
What would bring me joy? I love talking about tools and automation but the reality is I just don't have the energy for those things right now.
Beyond financial survival, how you design a practice is a decision about your own thinking: which activities feed the judgment that generates your value, and which drain it.
Younger uses what he calls the Hamming question, after the Bell Labs scientist who would ask researchers:
What are you working on? If you could work on anything with infinite resources, what would you work on? Why aren't you starting work on that?
At 73, he has made deliberate choices about where his value still runs strong. He sits on advisory boards for the specific contribution only his experience allows, rather than for the money.
At one board meeting about 40% growth, he asked:
How does it change the executive management of this place?"
A question only years of watching companies scale badly could produce.
His days balance what he and his wife call "head, heart, and body": advisory work for the mind, time with grandchildren for the heart, morning exercise for the body. This connects to the companion article on cognitive maintenance [LINK: cognitive maintenance article]. The system that produces your professional value needs more than intellectual engagement to stay healthy.
Younger puts the change honestly:
I have a new set of relative values. If I were upset that I wasn't making the money I made when I was on top, I'd be driving myself crazy instead of understanding things change.
He is describing the considered use of his remaining energy, directing his best thinking at the work that genuinely needs his depth and letting systems carry the rest. The core shifts as your energy, interests and circumstances change. The core shifts as your energy, interests and circumstances change. The principle holds steady. More on building a practice around your accumulated expertise: [Relational Enterprise hub]
Your accumulated wisdom is what separates you from AI. That advantage only counts when you build judgment into systems that make it visible, position your discernment as the thing clients pay for, and build a practice resilient enough to survive the disruptions that come with depending on a single irreplaceable resource: you.
Frequently asked questions
What is the minimum viable system for a solo practice?
The test from Yang's experience: could your practice sustain a two-month pause without catastrophic damage?
If not, identify what would break first. Usually it is visibility (no content going out), pipeline (no conversations being generated), and client communication (no updates or delivery).
Automate or systematise whichever would fail fastest.
You do not need complex technology. Yang's core system was voice dictation plus two people plus Zapier.
Liberman's is protected time for business development conversations plus simple tracking.
At what point should I stop trying to keep up with technical changes and focus on wisdom positioning?
Younger's answer is pragmatic: when your knowledge half-life has expired but your judgment remains valuable.
The signal is that you can still see what needs to happen in a situation (pattern recognition intact) but can no longer implement it at the technical level yourself (procedural knowledge outdated).
This is not failure. It is the natural evolution toward the structural scarcity position where your accumulated understanding commands premium value precisely because it cannot be replicated through technical training or AI assistance.
How do diagnostic conversations differ from free consulting?
Younger observes that about half of freelancers in UK studies reported offering free work and feeling uncomfortable about it. The distinction is purpose. Free consulting gives away your non-delegatable core without strategic intent.
A diagnostic conversation demonstrates your productive mindware in action while qualifying whether the prospect's problem actually matches your expertise.
One depletes your positioning. The other builds it.
Liberman's framing is precise: you are engaging your consulting skills ahead of time, which is the most powerful way for the right client to experience your value before committing.
References
- David C. Baker, The Business of Expertise (2017). The vendor and expert distinction applied to building a sustainable practice.
- Megan Beck and Barry Libert, "Management Consulting's AI-powered Existential Crisis" (MIT
Sloan Management Review). On why even elite advisory work faces the same market forces. - Jon Younger, "CEOs Explain How AI Will Super Charge Independent Management Consulting" (Forbes). The guest's own writing on AI and independent consulting.
- David A. Fields, The Irresistible Consultant's Guide to Winning Clients (2017). On pipeline and the conversations that win work.
- Caosun and Aral, "The Augmentation Trap" (MIT Sloan, 2026). Research on protecting judgment through self-directed AI use.
- Lynda Gratton and Andrew Scott, The 100-Year Life. On long working lives and staying adaptable.
Listen to the full conversations:
Melisa Liberman Solopreneur Business Development for Experienced Consultants Wisepreneurs podcast conversation on diagnostic conversations, value-based consulting, and systematic business development
Anna Burgess Yang Business Automation for Independent Solopreneur Practice Wisepreneurs podcast conversation on how distributed systems survived a two-month absence through surgery recovery
Jon Younger Professional Relevance: Positioning Expertise When AI Does the Routine Work Wisepreneurs podcast conversation on the freelance economy, knowledge half-life, and why experienced professionals keep working