Setting up a basic prompt chain
When I first tried to set up a prompt chain with Claude I opened way too many tabs and honestly forgot which one was the live Zap and which one was just a test. If you are just starting out the idea of a prompt chain might sound scarier than it actually is. Think of it like passing notes in class except each note adds a little more context until you finally have the full answer. The first prompt tells Claude what role to take, then the second adds context like what data you are feeding it, and then the later steps handle specific formatting or tone you want.
On my end I started with a simple test in the console. I used Claude’s chat interface and literally pasted text like:
“`
System: You are a strict proofreader
User: Fix this paragraph and remove passive voice
“`
But then in the Zapier integration I had to break it into multiple steps. The problem there is if you try to stuff everything into one input field you will hit the character limit. That left me confused until I realized I should split the system role into one Zap step, the main instruction in another, and then the context in a third.:
| Step | Text Passed |
|---|---|
| 1 | System Role with style rules |
| 2 | User Instructions |
| 3 | Raw Data or Draft |
That structure made the chain act far more predictable. Even then sometimes Claude would act like the second step never existed and would rewrite things in a way I did not want. When that happened I copied the whole transcript into a local text file to see where the chain broke. Usually it was because Zapier silently cut off the context field.
Fixing when Claude ignores the chain order
The single most frustrating bug I ran into was when Claude just skipped step two like it was invisible. I typed very specific instructions like “do not change my numbering” and then it went ahead and reindexed them anyway. What fixed it was making the instructions sound less like commands and more like a role description. For example instead of saying “Do not change my numbering” I wrote “Your job is to leave the numbering exactly as it is.” For some reason Claude respects role style instructions more than negative commands ¯\_(ツ)_/¯.
Another weird issue I noticed is that if you feed Claude too much context at the start it basically becomes blind to later steps. My fix was to move the long draft text to the last step in the chain so the rules and style instructions stay fresh in memory. I tested this by running the same text twice, once with the long text in step two and once in step three. The first version came back messy and ignored my style, while the second version actually followed the directions.
So if you are pulling data from a Google Sheet or Airtable record, keep the lightweight framing prompts on top and the heavy dataset at the bottom. It feels backwards but it works.
Testing chains with dummy content first
Early on I jumped straight into using real customer support transcripts. Big mistake. Claude would hallucinate summaries that looked polished but had wrong details. After banging my head against that for a while, I now always test chains with dummy content. For example I paste in a fake transcript like “User asks about cats. Response given was vague.” to see if Claude is actually preserving the flow of steps. Only once the chain behaves correctly do I switch to real data.
One trick I picked up is using nonsense filler like “banana banana banana” on purpose to prove whether Claude is keeping my context intact across steps. If I put the filler in step two and it vanishes later on, that tells me the step got dropped. If it shows up untouched, then I know the pipeline is carrying data. It’s low tech but it saves hours.
Dealing with Zapier field limits
Zapier’s interface looks clean until you realize the actual input character limits are buried and not warned about up front. I learned this when my chain silently cut off a block of text mid sentence. At first I thought Claude was glitching, but looking closer at the task log I literally saw:
“`
Input content: This is the deta…
“`
and it just ended. No warning, nothing. To fix this I now split long context into two separate fields and then I reassemble later. It takes an extra Formatter step but it works. Zapier’s Formatter can merge text fields, which then become one big input to Claude.
If you are pulling from Google Docs it helps to insert a short marker text like “END OF SECTION ONE” so you can check whether anything was cut off. Without markers you won’t know where the text got truncated. This tiny thing prevented a lot of confusion for me.
Chaining prompts inside Make
While I mostly work inside Zapier I also tested Make for more complicated chains. Make is clunkier to set up but has a neat trick where you can store the output of each prompt as a variable. With that you can pass the output back into Claude with extra context like, “Here is your previous answer, now expand it with examples.” This looping style made the responses way more consistent.
However Make has the same problem where if you dump too much into one module, Claude just ignores the tail end. On one attempt half the text was gone without warning. The run log showed no errors at all. So again, I started putting markers inside the prompt like “SECTION BREAK” to prove if everything traveled downstream. 😛
Comparing Claude prompt chains with OpenAI
I also tinkered with running the same chain structure in OpenAI’s API just to see if the bugs were Claude’s fault or Zapier’s. Interestingly the same cutoff issue happened with OpenAI, which means the culprit is Zapier’s character limits not Claude itself. But the ignoring of rules in certain steps seemed unique to Claude. When I told OpenAI to not touch the formatting it usually behaved, while Claude felt more eager to rewrite anyway, almost like it was too eager to be helpful.
So in short, expect that Claude chains may need extra phrasing tweaks to work properly. On the flip side Claude produced answers that felt more natural in tone once I got the flow right. OpenAI was more mechanical but more obedient. I kept both for different tasks since honestly they both break in different ways.
Sharing prompt chains safely with teammates
A thing I wish someone told me earlier — never paste your entire working chain into Slack without triple checking. I once shared what I thought was just prompt text but it accidentally included sensitive data from a support ticket. Not great. Now I strip everything down to template style text like “Step one role definition goes here” rather than the real fields.
If you do want to share reproducible chains with friends or coworkers, I recommend using dummy filler for personal data and attaching a simple text file. The chat apps often mangle indentation or quotation marks. I learned this after one teammate copied from Slack and it broke completely. Ever since, I just put chains in plain text and send as file attachments.
When chains completely stop working
Sometimes even with clean setup the entire process just stops working for no reason. One day the Zap ran fine, the next day Claude outputs an empty response. No error code. No explanation. I tried refreshing the integration, reauthenticating the API key, nothing. After wasting time, I ended up copying the whole Zap into a new Zap and for some reason it started working again. No logical reason why. Just the classic automation gremlin.
I now keep a bad habit of cloning automations as backups. It clutters my account but at least when something decides to disappear overnight, I’m not starting from scratch. It’s not elegant but it has saved a lot of late nights.
Honestly every time I build one of these chains I expect they might stop working tomorrow. It’s messy, but that’s just how living with these tools feels sometimes 🙂