600 old episodes,
fixed in one weekend.
Here is a machine that quietly fixed my entire podcast back catalogue while I kept making new episodes. My podcast has close to 600 episodes built over six years, and times changed. The links in the descriptions pointed to products I no longer sell, and the early artwork was rough, because back then I was not paying attention to the little things. Fixing all of that by hand would have taken months, or cost a lot to hire out. So I built a machine that walks every episode one after the other, swaps the old description for the new one, swaps the old artwork for the new artwork, then goes back and checks the change landed. If it spots one telltale sign that the change failed, it retries that episode. Slowed on purpose so nothing broke, it updated close to 600 episodes in about 48 hours, and old listeners now reach my current offer.
Your back catalogue is not dead weight. It is hundreds of pages still sending listeners to the wrong place.
Every long-running show carries a back catalogue that quietly rots. Links point to offers that no longer exist. Early artwork looks nothing like the show today. People still find those old episodes, listen, and hit a dead link instead of your current offer. Fixing it by hand means opening every episode, one by one, for months. So I built a machine that walks every episode, swaps the old description and the old artwork, then checks the change landed and retries any that failed. Here is who it is for, what goes wrong without it, how it works, and what you get back.
Who it’s for
Anyone sitting on a big back catalogue that has drifted out of date. Podcasters, YouTubers, bloggers, anyone with hundreds of old items carrying links and artwork from an earlier version of their business. It works even if you have hundreds of episodes, because the machine treats one episode and six hundred episodes exactly the same way.
What goes wrong
Without it, your old episodes keep sending fresh listeners to links that lead nowhere, and your early artwork keeps making the show look dated. You put off the fix because doing it by hand would take months. You are not short on audience. You are wasting the audience you already have by pointing them at offers you no longer sell.
How the machine works
You give it the new description and the new artwork. It walks every episode, swaps both, then looks back to confirm the change landed. It watches for one telltale sign that means the change failed, and retries that episode if it sees it. You touch nothing by hand. The machine updates every episode and checks its own work.
What you get back
A whole back catalogue with the right links and the right artwork, updated in a weekend instead of over months. Old listeners now reach your current offer. And because hundreds of episodes now point at the thing you actually sell, a steady share of old listeners buy, month after month.
Six years of episodes, all pointing at products I no longer sell.
This one started as an odd job, but it saved me what I can only call months of grueling, annoying work. I have a podcast, and on that podcast I have close to 600 episodes. Over the six years I have been doing this, times changed. There were links inside the descriptions I needed to change, and various other elements I wanted to fix. The problem was that I had to do this manually, and doing it by hand would have taken years, or I would have had to pay someone a lot of money for it.
So I built a machine instead. It finds the description I want to change, then goes to every single episode, one after the other, and changes the description for me in the background while I focus on the real work, which is making new episodes. And it was not only the description. The machine also changed the artwork. When I started the podcast, I was not paying attention to details like the thumbnail, so the early images were not the best. I had already fixed the artwork for new episodes, but I wanted that change to reach all the way back to the very first one.
The clever part was the checking. I added a step that goes back to each episode after the change and makes sure the work was actually done, because in some cases there could have been a bug. There was one particular item that would only be present if no change had been made. So the machine checks whether that one telltale sign is there. If it is, the change failed at that point, and the machine retries that episode until it is clean.
That is the part that quietly changes everything. I was not babysitting 600 episodes. I was making new ones while the machine walked the whole feed and fixed the old ones for me. I slowed the machine down on purpose, just so it would not break anything by moving too fast. And in about 48 hours it had updated close to 600 episodes, each with the right link sending listeners to the right product, and each with the artwork I actually wanted.
The result went beyond tidy. It dramatically improved the quality of the podcast, and it made real sales, because a whole bunch of people were listening to old episodes and now had the right link to my newest program. The numbers here stay modest on purpose. If corrected links turn even a handful of old listeners into buyers each month, that is a steady, free stream from work you were never going to do by hand, and it compounds across a catalogue of 600 episodes over the year.
Proof point: I have documented how I run my business on autopilot and the income streams behind it on YouTube, in my 28 income streams breakdown and a real look at the daily work in a day in my life, so the conservative numbers on this page are checkable.
Three moves that update a whole back catalogue on their own
What made this work was treating the back catalogue as one long list to be walked, not a pile of chores to dread. Most people open episodes one at a time, get tired around episode twenty, and quit. But a machine feels no boredom. The loop here walks every episode in turn, swaps the old description and artwork on each, then checks its own work and retries anything that failed. That is how a job that should take months finishes in a weekend.
Walk every episode, one after the other
The loop starts by treating the whole feed as one list to work through. You point the machine at the podcast, and it opens every episode in turn, from the newest all the way back to the very first. It never gets tired, never skips ahead, never loses its place around episode twenty the way a person would. Whether the feed holds fifty episodes or six hundred, the machine handles them the same steady way. You slow it down on purpose so nothing breaks, and it quietly walks the entire back catalogue while you make new episodes.
Swap the old description and artwork on each
On every episode the machine does the actual fix. It drops in the new description, so the old link that pointed to a product you no longer sell is replaced with the right one. Then it swaps the old artwork for the new artwork, so even your earliest, roughest episodes now match the show today. You write the new description and pick the new artwork once, and the machine applies that same clean update to every single episode. No copy and paste, no opening hundreds of edit screens, no missing one because you lost count.
Verify the change, and retry anything that failed
The last move is what makes it safe to trust. After each swap, the machine goes back and checks the change actually landed on the live episode. It watches for one telltale sign that is only present when nothing changed. If that sign is still there, the machine knows the update failed at that point and runs that episode again until it is clean. You do not spot-check 600 episodes and pray. The machine checks its own work on every one, so what comes out the other side is a whole feed you can trust, with the right link on every episode.
Once those three moves are in place, the dread disappears. The machine walks every episode in the feed. It swaps the old description and artwork on each one. It checks its own work and retries anything that slipped. You get a whole back catalogue fixed in a weekend instead of over months, and old listeners now reach the offer you actually sell.
Before the system
- Hundreds of old episodes pointing at products I no longer sold
- Early artwork that made the whole show look dated
- A fix I kept putting off because it would take months by hand
- Fresh listeners finding old episodes and hitting dead links
- A quote to hire it out that cost more than it was worth
After the system
- Close to 600 episodes carrying the right link to my current offer
- The new artwork reaching all the way back to episode one
- The whole catalogue updated in about 48 hours, run slow on purpose
- Every change checked, and any that failed retried on its own
- Old listeners reaching the right product, and buying it
Prompt 1: decide exactly what needs changing across the catalogue
Before you touch a single episode, you need a clear list of what is out of date. The biggest mistake is fixing one thing and missing three others. Use this prompt to map every element in your old episodes that should change.
Back catalogue audit planner
Act as a podcast operations advisor. I have a long-running show with hundreds of old episodes, and the descriptions and artwork have drifted out of date. About my show: [describe your podcast, how many episodes, and what has changed since you started, for example old links, old offers, old artwork]. Map the fix: list every element in my old episodes that should be updated, which old links point to things I no longer sell, what the new version of each should say, and how to spot an episode that was never updated. For each item, one line on why it matters.
The output is a clear list of what needs changing across the whole catalogue. Get this right and the machine knows exactly what to swap on every episode.
Prompt 2: plan how the machine walks every single episode
A back catalogue is just a long list, and the machine wins by working through all of it without skipping. Use this prompt to plan how it moves through every episode in order, so not one gets left behind.
Full-feed walk planner
Act as an automation planner. I want a machine that opens every episode of my podcast in turn and applies the same update to each one. About my feed: [describe where the episodes live and roughly how many there are]. Plan the walk: how to move through every episode from newest to oldest, how to keep track of which ones are done, how to slow the pace so nothing breaks, and how to pick up again if the run stops partway. For each step, one line on why it matters.
The output is a plan that covers the whole feed with nothing skipped. Run it once and the machine walks all of it, slow and steady, on its own.
The 3-minute overview of how this works
Before the build steps, watch this short overview. It’s the exact video from the Automations Made Easy page, and it walks through the mechanics behind machines like this one. 1,000+ students have used these mechanics to save two hours a day, with zero coding.
Want to learn the mechanics behind content automations like this?
I teach the same mechanics that power this bulk podcast updater inside Automations Made Easy. 1,000+ students have used these mechanics to save two hours a day and build little machines that quietly handle the boring work. No coding required.
Week one: your new description written, your first old episodes fixed.
Most people put off updating a back catalogue because it sounds endless, so they leave hundreds of episodes pointing at dead links forever. That is exactly why this machine matters. A bulk updater is meant to start small and run quietly, not arrive perfect. In week one you write the new description, prepare the new artwork, and let the machine fix a first batch of episodes, so you see it works before you turn it loose on all six hundred.
Week one looks like this. On Monday you audit the old episodes and list what is out of date, then write the one new description and pick the new artwork. Then you point the machine at a small batch, say the first twenty episodes, and let it swap both on each one. By midweek you add the check that confirms the change landed and retries anything that failed. By the end of the week you have a batch of episodes carrying the right link and the right artwork, and a machine you trust to walk the rest.
The point of the first week is not the number of episodes fixed. The point is to confirm the machine swaps the right things, checks its own work, and retries anything that failed before it moves on. Once that is locked, you let it walk the whole feed, and every one of your old episodes gets the right link and the right artwork on its own, while you make new episodes.
From there the maths is simple and conservative. Say the machine fixes close to 600 episodes and each one now sends listeners to your current offer. If corrected links turn even a handful of old listeners into buyers each month, that is a steady, free stream from a catalogue you already own. Over three to five years, those old episodes keep getting found and keep pointing at the right offer, so that quiet stream of sales compounds without you touching a single episode again.
All of this runs while you record, sleep, or plan your next episode. The machine walks every old episode, swaps the description and artwork, checks its work, and retries anything that failed. No more putting it off for months, no more paying a fortune to hire it out, no more fresh listeners hitting a dead link. Your whole back catalogue quietly starts working for you again, sending old listeners to the exact offer you sell today.
Prompt 3: set the check that catches any episode that failed
The magic is not the change, it is the checking. Without it, a quiet bug leaves some episodes broken and you never know. Use this prompt to set the one telltale sign the machine watches for, and what it does when it sees it.
Verify and retry checklist
Act as a quality control advisor. After my machine updates each podcast episode, I want it to go back and confirm the change actually landed, and retry anything that failed. About the change: [describe what a correctly updated episode looks like versus an old one, and any telltale sign that is only present when nothing changed]. Set the check: how to confirm the new description and artwork are really in place, which one sign proves an update failed, what to do when that sign is found, and how many times to retry before flagging it. For each rule, one line on why it keeps the catalogue clean.
The output is the safety net that makes the whole thing trustworthy. Settle it once and every episode is checked, and any that failed gets fixed on its own.
Prompt 4: write the new description that actually sells
Fixing the link is step one. Making that link earn its place is step two. Use this prompt to write a new episode description that sends old listeners cleanly to your current offer without sounding like an ad.
Description and offer link writer
Act as a direct response copywriter. I am replacing the description on hundreds of old podcast episodes, and I want the new one to send listeners to my current offer. About my offer: [name your current product or program and the one clear result it gives a listener]. Write the description: a short, warm summary that fits any episode, a natural line that points to my current offer, and a simple next step for the listener. Keep it honest and useful, so it reads like a helpful note, not a pitch bolted onto an old episode.
The output is a description the machine can drop into every episode. Get it right and every old listener lands on the offer you actually sell.
The exact build, step by step
Point it at a catalogue that has drifted out of date
Start where the waste is. Your podcast has years of episodes, and the links and artwork inside them belong to an earlier version of your business. You point the machine at that feed, and that single choice sets the whole job in motion. This is the step most people never take, because they imagine opening hundreds of episodes by hand and give up before they start. But you are not opening anything by hand. You are handing the machine one feed and letting it treat every episode in it, close to 600 of them, the exact same steady way.
Let the machine walk every episode in turn
Instead of editing episodes one at a time until you burn out, the machine walks the whole feed for you. It opens each episode in turn, from the newest all the way back to the very first, and works through the entire list without stopping. It never loses its place, never skips ahead, never gets bored around episode twenty the way a person would. You slow it down on purpose so nothing breaks. By the time you check in, it has quietly moved through hundreds of episodes, one after the other, and it keeps going until the whole catalogue is done.
Swap the old description and the old artwork
On every episode the machine does the real fix. It drops in the new description, so the old link that pointed to a product you no longer sell is replaced with the right one. Then it swaps the old artwork for the new artwork, so even your earliest, roughest episodes now match the show today. You write the new description and choose the new artwork once, and the machine applies that same clean update to every single episode. There is no copying and pasting, no opening hundreds of edit screens, and no chance of missing one because you lost count somewhere in the hundreds.
Go back and check the change landed
Now the machine protects the work. After each swap, it goes back to the episode it just touched and confirms the change actually landed on the live version. It checks that the new description is in place and the new artwork is showing, not just that it pressed the button. This quiet step is what separates a job you can trust from one that silently half worked. Editing 600 episodes is worthless if a hidden bug left a hundred of them untouched. By checking every one as it goes, the machine makes sure the whole feed really is fixed.
Retry any episode that failed
Now the machine handles the misses. There is one telltale sign that is only present when an episode was never actually changed. The machine watches for that exact sign on each episode after the swap. If it finds it, the update failed at that point, so the machine runs that one episode again, and again if needed, until the sign is gone and the change is clean. You do not comb through the feed hunting for the ones that slipped. The machine finds its own failures and fixes them, so nothing quietly stays broken in the middle of your catalogue.
Read the finished feed and let sales follow
Final piece. In about 48 hours, run slow on purpose, the machine hands you a whole back catalogue that is fixed. Close to 600 episodes now carry the right link to your current offer and the artwork you actually wanted. These are not dead pages. They are episodes people keep finding and listening to every day. Over the following weeks, a share of those old listeners follow the corrected link and buy your current program. This is the part that compounds. Your back catalogue keeps getting found, keeps pointing at the right offer, and keeps making sales with no more work from you.
Point at the feed
You hand the machine one podcast with close to 600 old episodes to fix.
Walk every episode
It opens each one in turn, from newest to oldest, without skipping any.
Swap and verify
It swaps the old description and artwork, then checks the change landed and retries any that failed.
Sales follow
The whole catalogue now points at your current offer, and old listeners start buying again.
Build this bulk updater inside the same playbook 1,000+ students use
Automations Made Easy teaches the mechanics behind content machines like this one. Step by step, no code, plain English. Save two hours a day and own little machines that fix the boring work for you, while you spend your time making the content that matters.
The six months after I switched it on
Here is the shape of the first six months after the machine fixed my back catalogue. The line tracks the value of the sales from old listeners who now reach my current offer through the corrected links, which is exactly how this machine pays off in practice.
Monthly value from old episodes now pointing to the right offer
Three things matter on this chart. The value climbs steadily as more old listeners find fixed episodes and follow the right link, not in a spike. The gains come from a catalogue you already owned, fixed once in a weekend. And every one of those months happens with no more work from you, because the episodes keep getting found on their own.
What other students built
I teach the simple skills behind machines like this in Automations Made Easy. Students who built their own version sent back what changed in their first month.
“I had years of episodes with links to a product I killed off ages ago. The machine walked all of them in two days. I would still be doing it by hand otherwise.”
“The checking step is what sold me. It went back and confirmed every episode really changed, and retried the ones that slipped. I trusted the whole feed by the end, not just the first few.”
“My early artwork was embarrassing and I had given up on ever fixing it. The machine pushed the new art all the way back to episode one while I recorded new shows.”
“Old episodes started making sales again within weeks, because they finally pointed at the thing I actually sell now. I never touched a single episode myself.”
What’s inside Automations Made Easy
AME isn’t a library of pre-built automations. Every business is slightly different. What’s reusable across all of them is the underlying mechanics: how to set up little machines that listen, write, and follow up while you sleep, and how to wire the pieces together without writing code.
The program walks you through six modules: The Right Tools (the cost-effective, no-code stack I actually use), Task Selection Mastery (which automations are worth building first), Design Secrets (mapping an automation before you build it), Zero to Hero (complete beginner to confident automator), Real-World Application (we build a full automation together, end to end), and Monetization Mastery (turn the skill into a side-business).
It also includes done-for-you templates you import in two clicks, over-the-shoulder training videos, and the same playbook 1,000+ students have used to save two hours a day. No coding required. If you can copy and paste, you can build this.
The bulk podcast updater: common questions
Pulled from what readers and Automations Made Easy students ask most.
Do I need to be a developer to set this up?
No. You write the new description once, pick the new artwork, and tell the machine what the old telltale sign of a failed change looks like. Then you let it walk the feed. The skills you need are knowing your own show and writing a clear description, which is exactly what Automations Made Easy teaches. The walking, swapping, and checking is handled for you.
How does it change every episode without breaking anything?
It walks the feed one episode at a time, slowed down on purpose, and swaps the description and artwork on each. Moving slowly is deliberate, so nothing is rushed and nothing breaks. After each change it looks back to confirm the swap landed, which is why close to 600 episodes came out clean in about 48 hours.
What happens if an episode fails to update?
The machine catches it. There is one telltale sign that is only present when nothing changed, and the machine checks for it on every episode after the swap. If it finds that sign, it knows the change failed there, so it runs that episode again until it is clean. Nothing quietly stays broken in the middle of your catalogue.
Will this work for something other than a podcast?
Yes. A podcast is just the easy example. The same approach fits any big back catalogue where old items carry links or artwork from an earlier version of your business. You point the machine at the list, tell it what to swap, and it walks through every item the same steady way. The mechanics stay the same whatever the catalogue is.
Does fixing old episodes really lead to sales?
It did for me. A whole bunch of people were still listening to old episodes, and once those episodes pointed at my current program instead of a dead link, some of them bought. The numbers on this page are kept deliberately modest. Even a handful of old listeners buying each month adds up to a steady stream from a catalogue you already own.
More Money Makers like this one
Built from the same handful of mechanics. Each one captures, converts, or earns money that would have walked out the door.
Build this bulk podcast updater yourself, or learn the mechanics inside Automations Made Easy.
If you want to learn the mechanics behind content automations like this and build your own at home, Automations Made Easy is the playbook. Step by step, no code, plain English. If you want to talk through how to audit your catalogue, write the new description, and set the check that keeps every episode clean, I take a small number of consulting clients each month.
€497 one-time · Lifetime access · 1,000+ students
