Why I Needed a Prompt System in TypingMind
I didn’t start here because I thought GPT needed prompting magic. I started here because I was tired. I had over 40 tabs open researching a blog post, and every time I wanted a quick summary, I’d open ChatGPT, type the same five-sentence description of my writing tone and intent, paste the content, reword the paste, realize I forgot to mention the context, go back – you get it. It was a mess.
TypingMind was already my go-to wrapper because of its keyboard shortcuts and easier chat memory management. But it didn’t have what I needed out of the box — nothing that would let me set up a reusable system to generate briefings for blog posts. No better way to say it: I needed to stop acting like a support team building custom queries from scratch every single time.
So yeah, this was born from burnout. I wanted a prompt system I could clone easily and re-use on different topics, with structured inputs for each blog task. Here’s exactly how I set it up, why it’s way better than snippets or bookmarks, and where it quietly breaks under pressure 🙂
How to Actually Build the Prompt Template System
First thing: forget the auto-text feature in your head. You’re not just using canned responses. You’re building kinda like a mini-form, where you drop in variables each time. In TypingMind, do this by using the Prompt Library section. This is different from ‘Custom Instructions’ — which are global, not tied to each message.
So here’s what went into mine:
Title: “Blog Post Template – SEO Tech Deep Dive”
Prompt Body:
“`
You are a deeply human automation blogger. Tone should be casual but accurate. Do not summarize. Do not use generic structures. Focus on specific tooling problems, actual bug behavior, screen locations, pace of automation.
Topic: {{topic}}
Intent: {{intent}}
Tools Mentioned: {{tools}}
What should the result teach the reader: {{what_should_reader_learn}}
“`
Every time I run it, TypingMind highlights those double-brace `{{variable}}` fields and prompts me to enter them. Then it builds the full prompt with my new context auto-inserted. It’s way more dynamic than saving templates in Notion or Bear, which I tried — but I always had to copy-paste and rewrite the context gaps.
If you’re new to TypingMind — the Custom Prompts area is under ⚙️ Settings > Prompt Library.
Now whenever I’m mid-research, I can keep one chat thread per article. The prompt system updates each time without wrecking the tone, and I can even change one field (like tools or intent) without starting over.
The Variable Names That Saved Me Hours
If you get the variable names wrong, TypingMind won’t always warn you. It’ll just send a prompt that includes `{{wrong_variable}}` in the body, which GPT then replies to like a confused intern. Learned that the hard way 😂
So I kept my field names as short and human as possible:
– topic
– intent
– tools
– what_should_reader_learn
I first tried making more fields like writing_level or link_limit, but I never ended up changing them between projects. More fields = more friction. The goal’s to fill out this thing in under 15 seconds.
Also made one called quote_snippet, but honestly, GPT started hallucinating quotes unless I gave it a full copy-paste from a real source. It was easier to just include that directly in the raw body when I needed it.
I also force lowercase for my inputs unless I need a sentence. Caps mess up tone predictability. It started swerving formal just from seeing Title Case :/
Why Not Just Use ChatGPT Custom Instructions
Okay, I tried that. I really did. But the problem is, Custom Instructions are “always on.” So if I’m researching browser extensions in one tab and writing about inventory automations in another thread, both chats use the same background logic. You can’t clone threads with different custom setups.
In TypingMind with prompts, each chat can use a different template. It’s local to the message you send, not the full model behavior. Also: if you mess up a prompt in ChatGPT, it doesn’t show you the full input ― you have to guess what part of your instruction triggered the weird reply 🙃
I could stay consistent within a single project way better with the TypingMind prompt system. And when I wanted to make a new prompt system for a different voice (say, for writing social copy instead of longform), I just duplicated the old one and changed 2 fields.
What Happens When You Hit Prompt Cache Bugs
So here’s where things got weird — and probably the reason you’re here. One day I opened my longform prompt, entered new variables, hit run… and the result looked like I hadn’t added any inputs. The old values from my last use were showing up instead. Like:
“`
Topic: air purifiers
Tools: none
“`
In a thread where I had clearly entered something about newsletter automation and ConvertKit 🤯
Turns out, TypingMind has a caching behavior where if you hit the prompt and then accidentally click away before submitting, it keeps the last-run values in memory. And if you re-open the prompt editor later with the same name, it sometimes re-renders with the old cache values already filled in — but invisible unless you re-edit every field.
I worked around this by renaming prompts after major changes — like “Blog Post Prompt v3”. Also started including a dummy variable at the top with a timestamp like:
“`
prompt_started: {{today_date}}
“`
That way, if the response still showed yesterday’s date, I knew the inputs didn’t go through. Super hacky? Yep. But it saved me from publishing a post that referenced the wrong app in every paragraph.
Faster Than Bookmarks or Notion Templates
I used to keep article prompt structures in a Notion template — you know, those pre-baked checklists with headings like “Hook angle,” “Top search queries,” “Call to action.” But I always ended up copying them with a mouse, tweaking text over and over, then eventually pasting whole copies into ChatGPT and realizing the result lost all formatting anyway.
TypingMind’s prompt system was the first time I felt like I wasn’t working for my own system. I filled in just the editable parts that mattered, tapped return, and it generated stuff in the consistent tone I needed. That’s what good systems should feel like: semi-invisible, not heavy.
Also pairs weirdly well with Raycast or LaunchBar. I set TypingMind as a browser launch target for specific URLs for each article — like `typingmind.dev?chat_id=airtable_post`. So I could open the workspace and immediately reuse the same thread + prompt system.
Bookmarks opened too slow. I could never remember if I saved V2 or V3 of the doc. Having it baked into TypingMind’s UI cut out so much duplicate confusion.
When the Model Still Completely Misreads the Prompt
This happens occasionally. Even with a well-structured prompt, sometimes Claude or GPT just goes off somewhere weird. It’ll summarize the article instead of generating a fresh one. Or just start listing bullets instead of composing paragraphs.
When that happens, the best fix I’ve found is to add a tiny bit of framing BEFORE the variable inputs. Like this:
“`
Write a longform article with specific SEO tone. Do not list bullets unless content requires them. Do not summarize. Answer a fix-based question.
Topic: {{topic}}
“`
Also, I found that prompt success varies between models. GPT4 (not turbo), Claude Opus, and even Mixtral will all give slightly different interpretations. So when one acts like it “forgets” its assignment halfway through the response, I just click regenerate with a different model.
In TypingMind, just hit the little model drop-down at the bottom-left before resending. No need to rewrite anything. But yeah, still frustrating when you forget and wonder why “Write a fix-based post” turned into “Here are five general tips.” ¯\_(ツ)_/¯
Missing Feature Requests I Wish Existed
Right now, there’s no way to export prompt templates. So if I build a new blog system on one machine, there’s no easy sync unless I manually copy-paste the whole body and rebuild the variables. This also means no version history.
I’d love:
– Prompt duplication with diffs
– Prompt export and import (JSON maybe)
– Warnings if variable replacements fail silently
– Shared prompt templates (for teammates)
Also wish prompts could run automatically when a new chat is started — like “Use this template every time I create a Doc-style chat called BLOG.” It’s not there (yet). For now I use naming discipline to make sure I know which chat uses which version.
Someone in the GitHub repo actually posted:
> “Would love conditional logic in variables, like if topic includes API, use Engine A.”
Totally wild idea. I don’t need that specific setup, but it *would* unlock different tones or formatting without needing separate templates for each tool stack.
Anyway, if they don’t add it soon I might just patch a local wrapper around the TypingMind API and pretend I’m building productivity software again for fun 😛