44:47Greg Isenberg · Interview
Most Valuable Skill of 2026: Managing AI Agents
Ryan Carson explains why running a one-person AI startup in 2026 means becoming a full-time manager of cloud coding agents, not a part-time coder.
July 24thThe argument in one line.
Selling AI agents as completed work instead of software seats taps a market bigger than SaaS ever was, because the buyer is paying for labor, not licenses.
Read if. Skip if.
READ IF YOU ARE…
- You want to start a business built around AI but don't have a clear idea yet and want a structured way to find one.
- You run or want to run a service that sells automation to small businesses like restaurants, home services, or med spas.
- You're comfortable starting with manual, human-in-the-loop work before building full software.
- You want a concrete 30-day plan for going from no idea to a paying pilot customer.
SKIP IF…
- You're looking for enterprise AI agent architecture or technical implementation details — this is a business/GTM playbook, not an engineering guide.
- You already have a validated agent product and are past the pilot stage.
The full version, fast.
The video argues that agent-based businesses are a bigger opportunity than the SaaS era because they sell completed work, not software licenses, tapping the multi-trillion-dollar labor market instead of just software budgets. It lays out a seven-step playbook: find a workflow that already has a paycheck attached to it, shadow the human who currently does the job before building anything, ship the smallest useful agent (draft-and-approve, triage, coordinator, or bounded-action), wrap it in a trust layer of logs and approvals that makes it feel like software, sell it manually as a pilot before productizing it, price it like labor with a setup fee plus a simple recurring fee, and grow through workflow-teardown content that contrasts the old broken process with the new agent-run one. It closes with a concrete 30-day, zero-to-pilot execution plan.
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00:00 – 01:38
01 · Intro
The host states the thesis that agents are the new SaaS, argues the labor market makes the opportunity bigger than software alone, and previews the full playbook: niche, workflow, first agent, proof, packaging, and selling agents as labor.
01:38 – 04:11
02 · Building Agents is the new SaaS
Frames the core mental model: SaaS sells software, agent SaaS sells work. Uses a restaurant phone example (Slang AI) and a home-services dispatch example (Sameday) to show agents replacing a specific job rather than providing a tool.
04:11 – 06:12
03 · Pick a valuable workflow
Lays out five traits of a good agent workflow (frequent, clear finish line, touches existing software, edge cases are learnable, buyer feels the loss) and a scoring method for picking a workflow inside a chosen niche.
06:12 – 09:34
04 · Shadow the Human First
Argues founders should shadow 10-20 runs of a human doing the job before building anything, extracting trigger/context/tools/rules/escalation/success criteria from the real (not assumed) workflow.
09:34 – 12:50
05 · Build the Minimum Useful Agent
Introduces the minimum useful agent (MUA) concept and its four starting shapes — draft-and-approve, triage, coordinator, bounded action — citing Anthropic's guidance that agent problems should start as predictable workflows.
12:50 – 15:50
06 · The wrapper makes it SaaS
Explains that the trust wrapper — logs, approvals, controls, and a way to test the agent before going live — is what separates a real agent SaaS product from a plain automation script, plus the role of a 50-example eval set.
15:50 – 18:37
07 · Sell the Pilot Like Labor (and Pricing)
Describes selling a manual, AI-assisted pilot to three customers in one niche before productizing, with sample pricing structures (setup fee plus flat monthly, or setup plus per-outcome pricing).
18:37 – 21:45
08 · Own the workflow
Covers distribution via workflow-teardown content contrasting the old broken process against the agent-run process, and recaps the zero-to-100 sequence in one slide.
21:45 – 24:14
09 · The Zero-to-100 Plan in 30 Days
Gives a concrete day-by-day plan: pick niche, interview operators, pick workflow, write spec, run manually, build MUA, build eval set in week one; sell two pilots in week two; add the product wrapper in week three; publish teardown content in week four.
24:14 – 26:03
10 · Closing Thoughts
Closes by restating that the opportunity is finding the smallest painful, repeating workflow in a niche you understand and making it disappear, and invites comments on what to cover next.
Lines worth screenshotting.
- A normal SaaS product says 'here is a tool your team can use'; an agent SaaS product says 'here is a job your team no longer has to do,' and that's a mindset shift for both buyer and builder.
- The total addressable market for agents is bigger than SaaS because agents compete with human labor, not just software budgets.
- A good agent workflow happens at least daily (ideally hourly), has a clear finish line, touches existing software, has learnable edge cases, and creates a loss the buyer can feel when it fails.
- Shadow 10 to 20 runs of a human doing the job before writing a single prompt — the real workflow is always deeper than the obvious version.
- Most people imagine a fully autonomous employee when they hear 'agent,' which produces flashy demos and bad businesses; start with a much smaller minimum useful agent instead.
- The four minimum-useful-agent shapes, in order of increasing autonomy, are: draft-and-approve, triage, coordinator, and bounded action.
- Anthropic's own guidance says many agent problems should start as workflows with a predictable path, and only earn dynamic judgment once that path proves it creates value.
- The agent does the work, but the wrapper — logs, approvals, controls, and the ability to test before going live — is what actually makes a customer trust it enough to call it software.
- Run a 50-example eval set before promising autonomy; it doubles as a sales asset when you can tell a prospect exactly how many cases it got right, how many it flagged, and how many it got wrong.
- The fastest path to a real agent business is a manual pilot where you do the work with AI assistance, then productize only the parts that repeat across customers.
- Constrain the pilot to one niche and one workflow across three customers — spreading across niches or workflows early produces weak, unfocused results.
- Outcome-based pricing (e.g. dollars per qualified appointment) is described as the eventual future of agent-business pricing, but the advice is to start with a simple setup fee plus flat monthly fee and earn your way to outcome pricing.
- Workflow teardown content — showing the painful old way next to the clean agent-run way — is presented as the distribution format that's working right now for this category.
- The recommended sequence for content and sales is: sell painkillers not vitamins, since a buyer who feels the pain of missed calls or dropped leads converts faster than one being pitched a nice-to-have.
- The suggested 30-day path is: pick a niche (day 1), interview 10 operators (day 2), pick one workflow (day 3), write the agent spec (day 4), run it manually with AI (day 5), build the smallest useful version (day 6), build a 50-example eval set (day 7), sell two pilots in week two, add the trust wrapper in week three, and publish workflow teardowns while turning pilots into proof in week four.
Sell the finished job, not the software behind it.
AGENT BUSINESS PLAYBOOK
Buyers pay more readily for a job that disappears than for a new tool to learn, so the highest-leverage AI businesses package agents as completed labor and only build the software wrapper once a manual pilot proves the work.
02Building Agents is the new SaaS
- The core mental shift is that agent SaaS sells completed work, not a tool the team has to operate themselves.
- Real examples like an AI phone host for restaurants or an AI dispatcher for home-services companies show the pattern: the agent takes over one specific, painful job end to end.
03Pick a valuable workflow
- Score candidate workflows on frequency, pain, ease of knowing when the job is done, tool access needed, and who already controls the budget.
- Start by picking one niche and listing 20 jobs people in it complain about, rather than searching for an idea in the abstract.
04Shadow the Human First
- Watch and record 10-20 runs of the actual human doing the job before building anything — ask what makes a case easy, what makes it weird, and where mistakes happen.
- Extract the agent spec's seven parts (trigger, context, tools, allowed actions, approval points, escalation rules, success definition) directly from what you observe.
05Build the Minimum Useful Agent
- Choose the smallest of four agent shapes — draft-and-approve, triage, coordinator, or bounded action — rather than attempting full autonomy on day one.
- Anthropic's own agent guidance recommends starting with a predictable workflow and only adding dynamic judgment once it's proven to create value.
06The wrapper makes it SaaS
- Customers need to see logs, approvals, and controls — the wrapper is what earns trust even though the agent itself does the actual work.
- Build a 50-example eval set before promising autonomy; it both catches errors and doubles as a compelling sales asset.
07Sell the Pilot Like Labor (and Pricing)
- Sell a manual, AI-assisted pilot to about three customers in a single niche before building repeatable software.
- Start pricing simple — a setup fee plus a flat monthly fee — and move toward outcome-based pricing only after understanding what the customer actually values.
08Own the workflow
- Workflow-teardown content that contrasts the painful old process with the clean agent-run process is the distribution format working right now for this category.
- Pick one workflow to be known for, and build proof (checklists, benchmarks, teardown examples) around it before running paid ads.
09The Zero-to-100 Plan in 30 Days
- Week one: pick a niche, interview 10 operators, pick one workflow, write the agent spec, run it manually with AI, build the smallest useful version, and build a 50-example eval set.
- Weeks two through four: sell two pilots in the same niche, add the trust wrapper (logs, approvals, analytics), then publish workflow-teardown content while turning pilot results into proof.
Terms worth knowing.
- Minimum useful agent (MUA)
- The smallest version of an AI agent that's still useful in production, as opposed to a fully autonomous system — the four starting shapes are draft-and-approve, triage, coordinator, and bounded action.
- Draft-and-approve agent
- An agent that reads context and drafts a reply, quote, or next step, but requires a human to approve it before it goes out — used when there's creative or approval risk.
- Triage agent
- An agent that classifies inbound work (a ticket, a call, a request) and routes it to the right place or person.
- Coordinator agent
- An agent that sits between systems and people, checking availability, sending reminders, and asking for missing information to keep a process moving.
- Bounded action agent
- An agent that can independently perform a specific action under clear rules, such as booking an appointment or processing a refund under a fixed dollar limit.
- Eval set
- A fixed batch of real historical examples (e.g. 50 past calls or tickets) with marked correct answers, used to test an agent's accuracy every time its prompt, model, or tools change.
- Product wrapper
- The layer of logs, approvals, controls, and testing tools built around an agent that gives customers visibility and trust — what turns a working automation into something that feels like software.
- Outcome pricing
- A pricing model that charges based on results delivered (e.g. per qualified appointment or per ticket resolved) rather than a flat seat or subscription fee.
- Workflow teardown
- A content format that shows a business's painful current process step by step, then contrasts it with how an agent would handle the same process — used here as the primary distribution/marketing format.
Things they pointed at.
02:45productSlang AI
03:12productSameday
11:31linkAnthropic's agent guidance (building effective AI agents)
Lines you could clip.
00:00
“Building agents is the new SaaS.”
02:27
“SaaS sells software. Agent SaaS sells work.”
14:05
“The agent does the work, but the wrapper creates the trust.”
19:49
“You want to be in the business of selling painkillers, not vitamins.”
50:55
“Start with the job. Then build the agent people pay for.”
Word for word.
Read-along
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metaphoranalogy
Okay. I'll say it. Building agents is the new SaaS.
I mean, we saw billions of dollars of value creation during the SaaS era. People, founders, 21 years old, 24 years old, you name it, come up with SaaS ideas that change their lives.
Of course, not everyone was successful, but this is a new wave that's happening. And I want you to understand what this wave is, how you can take advantage of it, how you can build startups in this space.
And in this episode, I'm basically gonna clearly explain this entire agents is the new SaaS opportunity. By the end of this, you're gonna understand the playbook, you're gonna ascend understand how to find the niche, you're gonna understand how to pick the workflow, how to, you know, build your first agent, how to prove it works, how you can package it like SaaS, and how you can basically sell these agents as labor.
And it's really important because that that labor point because labor is a multi trillion dollar market.
Right? So I think why people say agents is bigger than SaaS is because the total addressable market for agents is just way bigger.
You know, it's human capital. And I wanted to just do an episode where I explain everything step by step just clearly for people who are interested in building agents, who are who are interested in selling agents, and who are, you know, just want their creative juices flowing around this.
This is for anyone who wants to build a business or who just want wants to be more productive. This episode is for you.
So the first thing you need to understand is the product is the job. So, you know, the mental model I have for this is SaaS sells software.
Agent SaaS sells work. A normal SaaS product says, here is a tool a team could use, basically.
But an agent SaaS product will say, here is a job your team no longer has to do by hand, and then you're selling that service.
So it sounds like a a small change, but it's a it's a really big mindset change for the customer and for you, the person who's gonna build be building it. So take restaurants, for example.
You know, a restaurant wakes up thinking our phone is ringing during, you know, dinner time, and the host is busy, right, dealing with, you know, seating people.
People are asking the same questions or missing reservations, and private dining calls are getting lost.
So they're basically missing out on lost revenue. This is why a company like, you know, Slang AI is interesting. Basically, it's an AI super host for restaurants.
I'm not affiliated. I just think it's an interesting, you know, example. Uh, it answers inbound calls.
It handles guest questions. It manages reservations. It routes VIPs, it alerts staff about high priority topics like private dining or guest complaints, and it integrates with systems like OpenTable and Yelp and stuff like that.
I'll give you another example. Home services, a plumbing company, HVAC company, a roofing company, pest control company, missed calls, you know, jobs are booked, customers followed up with, dispatches are less overwhelmed, more revenue from the same demand if they integrate something that picks up their phone twenty four seven.
You know, an example of a startup that's doing this is same day. So they focus on home services, and then they basically sell these AI, you know, dispatchers, sales agents, receptionists that answer calls, respond to text, books jobs, reschedule.
Again, the product is the job. These examples matter because they're just understandable. And so when you're thinking about coming up with an idea for a startup here, think about I handle this one annoying job better than a junior employee, faster than an agency, and it's cheaper than adding headcount.
That's the mental model I think that you should be thinking about. The second step I have here is pick a workflow with a paycheck attached. So, you know, how do you find the right agent idea?
You want to start with the paycheck. Right? If people are already paying for the work, they're paying an employee, they're paying an agency, a receptionist, a coordinator, dispatcher, they there's an opportunity to sell that service cheaper and then unload some of that work that that person is doing to do more high highly creative creative work.
So a good agent workflow has five traits. The first is it happens all the time. So daily is good, but hourly is better.
You know, every inbound lead, every call, every tech ticket, every quote request, every appointment, every order, every maintenance request.
Second, it has to have a clear finish line. The job got booked. The ticket got categorized.
The refund got approved. Uh, the vendor got scheduled. Um, the customer got a useful answer.
Uh, third, uh, if it touches already software. So if it touches Gmail or Slack or Shopify, HubSpot, Zendesk, Stripe, um, agents need these tools so they can use it, and they also need the context that they can read.
The fourth is the edge cases are actually really annoying, but they're learnable. So if a workflow is too basic, basically, the problem is basic automation, know, zaps and stuff like that can do it.
If it's pure human judgment, the first version will break. So the sweet spot is repetitive work with enough judgment that AI can help.
The fifth is the buyer can feel the loss. Missed calls, slow replies, dropped leads, empty calendar slots, expensive humans doing low value coordination.
So if this is, you know you know, if you wanna start a business here, here what's a first rep to get started? Well, pick one niche and write down 20 jobs people complain about.
If it's roofers, you know, maybe it's missed calls, financing questions, insurance paperwork, appointment reminders.
If it's med spas, it's maybe lead qualifications or no show recovery, membership upsells.
If it's Shopify brands, maybe it's returns, exchanges, wholesale lead follow ups.
And then you wanna score each job on five things. How often does it happen?
How expensive is the pain? How easy it how easy is it to know when the job is done? What tools does it need access to, and who already owns the budget, and that is where agent SaaS starts.
So you wanna start with the job that has a paycheck attached. Super, super key point here. Once you've done that, you actually and this is this is the thing that a lot of people miss.
You you actually wanna shadow the human before you build. So once you find the job, right, you you you've identified what the job is, before you, like, prompt, before you start coding, just shadow a human being who does the job.
I know a lot of founders want to skip this, but it's usually what's gonna help you get, you know, an unfair advantage and insight into building an agent that is high quality.
So just watch someone do the job, 10 to 20 jobs. Ask them to screen record it. Ask them to narrate what they're doing.
Ask them what makes a case easy. Ask them what makes a case weird. What did they check before they make a decision?
Ask them where the mistakes happen. Basically, you're looking for the real workflow. And even if you've done these tasks before, having having it, you know, fresh in your memory is just gonna be super, super helpful when you're building out this.
So, you know, for example, a restaurant host. If they answer, what time are you open? The real workflow is actually deeper than that.
They know when the kitchen closes, which tables are good for strollers, when the patio is closed, how to handle a VIP, and, you know, when to route to a private dining inquiry.
So . Um, and when you're specking out your your agent, you know, I think it should have seven key parts.
What wakes the agent up? What context does it need? What tools can it use?
What is it allowed to do itself? Where does it need approval? When should it escalate and and bring a human in the loop there?
And what does success look like? And if you understand all those things, you're, you know, you're not just gonna build an agent slop.
Right? We wanna build agents that are high quality, that are exceptional, that do the work as well, if not better than humans and way more consistently.
And that's what people are going to pay for. So really helpful to just sort of internalize that.
Now you're gonna want step four is you're gonna wanna build the smallest useful agent. I call it the minimal useful agent, the M U A.
Most people hear agent and imagine a fully autonomous employee. And that's how you you get these demos that you see on Twitter, and they don't really work, and it ends up being a bad business.
You want to start smaller, actually. So there are four good first versions. The first is a draft and approve agent.
So it reads context, it drafts the reply, the quote, the summary, or the next step.
A human approves it. Uh, so this is great when there's workflow risk.
Um, maybe there's creativity involved, uh, approval processes, that that sort of thing. The second is a triage agent.
So it classifies inbound work and routes it to the right place. Maintenance requests, uh, billing issue, or, uh, you know, refund, that sort of thing.
The third is a coordinator agent. So this goes between systems and people. So it'll check availability, it'll send reminders, it asks for missing info, and it keeps the work moving, basically.
And the fourth the fourth is the bounded action agent. So it can do a specific thing under clear rules.
You know, book an appointment, send a follow-up, you know, process a refund under $50. These are the sorts of things you'll you'll now see you'll notice it in the wild.
Like, for example, at Uber Eats, you order something and your salad doesn't arrive, automatically you'll get the refund based on an agent that will do it.
So that's basically the the ladder here when you're building the the minimum useful agent. Draft, triage, coordinate, and act.
I was looking at Anthropix agent guidance recently, and they made a really important point, a really important simple point.
They said many agent problems should start actually as workflows.
So a workflow follows a predictable path. An agent decides more dynamically. Founders should earn autonomy by starting with a predictable path and adding judgment only when it creates value.
So if I were building this, I would start with one workflow and one promise. For example, like, we answered missed we answered missed calls for roofers and book qualified jobs, or we triage maintenance requests for property managers and schedule the right vendor.
We handle reservation calls for restaurants and alert staff when a human should jump in.
That's enough. That's really enough. And one workflow that works enough is is good enough for day one.
And it's gonna help just like build confidence not just in you that it's working, but also in this customer. Because keep in mind, people are buying agents for the first time ever. So they they want to they don't want all of it at the same time, especially if you're not Microsoft or you're not Salesforce.
So step five in building an agent is the product wrapper is what makes it a SaaS. So you don't wanna just build a cool automation, and I think what separates a cool automation from a real agent first SaaS product is the agent does the work, but the wrapper creates the trust.
So customers actually need to see what happened. They need to see logs.
They need approvals, controls, handoff rules, that sort of thing. And they need a way to test the agent before it goes live.
They need to know basically why the agent did what it did. So that wrapper is the SaaS, and the agent actually lives in the phone system, the inbox, the Slack channel, CRM.
So the dashboard can be really simple, but the customer customer actually still needs the control room.
At least that's what I'm noticing is working right now. So for a restaurant phone agent, the control room might be, you know, call summaries or reservation outcomes, missed human handoffs, that sort of thing.
For a property maintenance agent, maybe it's, you know, tickets that have been created, vendor routes, or tenant updates, owner approvals, that sort of thing.
And that's really why evals matter a lot when you're building an agent first business.
Because before you promise autonomy, you wanna create a basically, small test a test set is the best way to think about it.
So, you know, take 50 real examples of the job and then mark the right answers, like 50 calls, you know, 50 leads, maybe, you know, 50 maintenance requests, depending on what it is.
And then you wanna run the agent system against them. So did it classify the problem correctly?
Did it ask for the right missing information? Did it use the right policy? This is what's called an eval.
Right? Your eval set is, you know it's basically like the gym.
You know? Every time you change the prompt, the model, the tools, the workflow, the agent goes back through the gym and and is able to, you know, basically know what's good and know what's bad.
It's also, like, low key a really good sales asset because imagine telling a property manager, you know, we tested this on fit you know, 50 of your old maintenance requests. It routed 42 correctly, flagged six of them for human review, and made two mistakes.
Here are the two mistakes, and here's how we fix them. So it just helps you actually build trust, especially with people who are like who own boring businesses, but who can actually really use some of these agents.
When you when you just are transparent and open about these sorts of things, you're gonna build a lot of trust with them. So the sixth step on building an agent is you're gonna wanna sell the pilot like labor, and then you're gonna wanna productize it.
So the fastest path is usually a pilot where you manually do the work with AI, and then you productize the repeated parts.
I'll explain what I mean by by that. But, you know, basically, would start with three customers in one niche. So the same niche, same workflow, same pain, and then you sell the outcome.
You actually want to be like very, very constrained on this, or else you're going to get bad results. So if you're selling the outcome, it's we will answer and qualify your missed calls.
We will triage your maintenance request. And then you charge a setup fee and a simple monthly fee.
You can keep the pricing just easy to understand, and then you could add usage or outcome pricing once you understand the value.
I'm a huge believer if you're, you know, listen to the Startup Ideas podcast here and, you know, you're a subscriber here, you know I I I really believe that outcome pricing is the future of how a lot of these agent first businesses and software is going to be priced because, you know, it just makes sense.
Like, you know, the customer only wants doesn't want to pay for another seat for something. So but don't just jump there initially.
So you you'll get there. And you have to have patience with it a little bit. You know, the the pricing model, like, do you think about pricing something like this?
You know, maybe it's like a 1,500 setup, $1,500 setup, and then like a thousand dollars a month for one workflow. Or maybe it's like $2,000 setup plus $30 per qualified appointment.
So that's more of the outcome base eventually. Or 3,000 a month up to 500 handled tickets.
So the exact price actually matters less than the learning. Uh, you basically wanna find out what the customer values and then, uh, where the agent breaks, uh, what needs approval, and what would they miss if you took it away.
Pretty much the most important question there is. And then you build a product around the repeated pattern.
So if every roofer needs the same emergency call script, service area checked, financing question, and estimate follow-up, boom, you have a product.
If every med spa needs lead scoring, consultation booking, no show recovery, post treatment follow-up, boom, you have a product.
So this is agent SaaS. You know, you earn the software by doing the work first.
Step seven is distribution. You know, you're gonna wanna get you need obviously, you need people to hear about the thing you're building, hear about the agent, see it, and be like, I need this.
And how can you do it? What are some tips to to be thinking about this? Workflow teardowns is what I'm seeing in real time that's working really, really well.
So show the old way of doing a process. Right?
A call comes in, nobody answers, the customer calls the next company, or or the CSR answers, asks five questions, checks the calendar, checks the service area, books the job, you know you know, writes the notes, sends a reminder, and then forgets to follow-up.
And then the heart of the owner, of the manager just absolutely breaks. And then you show the agent way.
A call comes in, an agent answers. It asks the right questions. It checks the service area.
It checks the urgency. It books the appointment. It updates the CRM.
It sends the confirmation. It flags edge cases for a human.
That's the type of content that works because the manager, the executive, the owner feels that pain. And, you know, you wanna be in the business of , and that's why I love these building agent businesses, because you are.
You know, if you do this right and you go through some of these steps and and and these frameworks and this playbook for coming up with an idea, building an idea, you're building something that's really, really helping people. Like, is very, very valuable to them, and the only way to really, really get them to book a call or do something is to show them, sort of make fun of the old way, and then show them the new way.
Pick one workflow, make the internet associate you with it, and, you know, the way I think about it is you wanna make the checklist, you wanna make the bet benchmark, make the teardown, make like 50 examples of this workflow post, and you're gonna be in the content game, you know.
A lot of people listen to this, you know, don't wanna create content, and I totally understand, but you know, you have to create content around this because it's just the you know, there's just a opportunity in creating content.
And then you can use some of those assets that are starting to work and then put paid paid ads around it. So, you know, distribution, think about these these teardowns, think about poking fun of the old way, think about creating memes around it, and then creating content, picking the winners, putting paid ads against it.
I would suggest focusing on one platform to start, and, you know, I'm gonna be doing more episodes on just how do you how do you get how do you get customers to your your vibe coded apps and stuff like that in the future.
So stay tuned for that. But just, you know, how I'd be thinking about it. The last step, you know, the zero to a 100 plan.
Like, if I was starting this from zero, you know, I feel like people would wanna know what would be my plan. So I'll give you my, you know, call it week four week plan.
My first day, what I would do, like how to build a business how do you build an agent business in thirty days? Okay. Day one, we pick a niche where missed work cost money.
We talked about this. Home services, property management, you know, insurance agencies. Day two, I would interview 10 operators, ask them to screen share the workflow, Keep the calls as research, and just watch them.
You can pay them for this, by the way. Day three, pick one workflow with frequency, pain, software access, and a clear success metric.
Day four, write the agent spec, Trigger, context, tools, rules, handoffs, evals.
Day five, run it manually with AI. You know, use Claude or ChatGPT and copy and paste the context, draft the output, ask the human to approve, and you are testing whether the AI helps before you build the software.
Day six, build that smallest useful version. Draft and approve or triage is usually enough here. Day seven, create the eval set from 50 real examples.
Week two, sell two pilots in the same niche. Week three, add the product wrapper.
Right? The logs, the approvals, the settings, the analytics, the handoffs, and use AI to actually build that, you know, software. I'd probably be using something like Claw Design and, you know, assuming that Fable is live, using Fable to actually code it up.
Week four, I'm publishing workflow teardowns, I'm turning the pilots into Proof, and I'm doubling down on my content strategy.
So, you know, while you know, I I should have mentioned this, but while I'm doing all this, while I'm thinking about building this business, I'm building an audience all the way throughout. And by the end of week four four, I have formats that are working. I know where to double down.
I know where I can spend money, pay paid money to acquire customers, and that's when I you know, my second and third month, I'm trying to understand what my LTV is, you know, what are the channels that are working, where can I double down on it, and I keep going? I think that's the episode.
You know, basically, where I'm at is I think agents are the new SaaS because software is moving from help me do the work to do the work with me.
And I think that a lot of people are just they're not partaking in the shift. They see the shift. They understand the shift.
You're listening to me, and you're like, yeah, of course. But they're not building they're not building agent first businesses.
I think the opportunity is basically to find the smallest painful workflow that repeats all day in a niche that you understand and make it disappear.
You know? Answering a phone, booking a job, triaging the ticket, updating the system, escalating that weird case.
And I think there's a ton of money to be made here and a ton of value to be created. So if you're watching this, you're listening to this, and you're thinking, I wanna build with AI, well, start start with the job.
You know? Find the job, shadow it, spec it, run it manually, build the smallest useful agent, sell the pilot, then productize the repeatable parts.
This is how you build an agent that people will pay for, and this is why I think building agents is the new SaaS. Hope this is helpful.
Hope this got the creative juices flowing. People charge thousands of dollars for this type of thing, but it is free. Like always, on the Startup Ideas podcast, let's I'll see you in the comments section.
I'll see you let's talk, and let me know what you want me to cover next, if this is helpful, and I read every single comment on YouTube. I appreciate every single like, and subscribe if you want more of this stuff in your feed.
Thank you, and I'll see you next time.
The Hook
The bait, then the rug-pull.
The host opens by declaring building AI agents the successor to the SaaS boom, then spends the episode turning that claim into a concrete seven-step playbook for finding, building, pricing, and selling an agent business.
Named ideas worth stealing.
04:11list
Five traits of a good agent workflow
- Happens frequently (daily to hourly)
- Has a clear finish line
- Touches existing software
- Edge cases are annoying but learnable
- Buyer can feel the loss when it fails
A scoring checklist for picking which workflow inside a niche is worth building an agent for.
Steal forqualifying any automation or agency service idea before building it
09:34list
Seven-part agent spec
- What wakes the agent up
- What context it needs
- What tools it can use
- What it's allowed to do itself
- Where it needs approval
- When it should escalate to a human
- What success looks like
A specification checklist to fill out before building any agent, used to avoid building 'agent slop.'
Steal forscoping any AI-assisted internal tool or client deliverable, not just customer-facing agents
09:34model
Minimum Useful Agent (MUA) ladder
- Draft and approve
- Triage
- Coordinate
- Bounded action
Four increasingly autonomous starting points for a first agent build, in order of how much trust/autonomy each requires.
Steal fordeciding how much autonomy to grant any new AI feature before it's proven
00:00list
Seven-step agent SaaS playbook
- Product is the job
- Pick a workflow with a paycheck attached
- Shadow the human before you build
- Build the minimum useful agent
- The wrapper makes it SaaS
- Sell the pilot like labor, then productize
- Distribution via workflow teardowns
The full end-to-end sequence the episode is structured around.
Steal forthe overall structure for building any service-turned-product business, not limited to AI agents
How they asked for the click.
VERBAL ASK
25:53next-video
“let me know what you want me to cover next... and subscribe if you want more of this stuff in your feed”
Soft, low-pressure close asking for comments and a subscribe, no hard product pitch — consistent with the video being free educational content for the podcast's audience.
FROM THE DESCRIPTION
PRIMARY CTAWhere the creator wants you to go next.
Visual structure at a glance.
