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Why I stopped using ChatGPT for task planning cover

Why I stopped using ChatGPT for task planning

Yog Sharma5 min read

Why I stopped using ChatGPT for task planning (and built a better workflow)

For months, I had the same ritual every morning.

Open ChatGPT. Describe what I wanted to build that day. Wait for it to break down the feature into tasks. Copy each one. Open Linear. Paste. Format. Add labels. Repeat.

It worked. Sort of.

But something felt broken about using the smartest planning tool available, then manually transcribing its output into another system like it's 2015.

The copy-paste tax

If you're a solo dev or indie founder, you've probably done this too. You use AI to think through problems because it's faster than staring at a blank page. But then you hit the friction point: getting that thinking into your actual workflow.

The options are:

  • Copy-paste everything manually (slow, loses context)
  • Keep planning in AI and execution in your task manager (context split across tools)
  • Just wing it and skip formal task tracking (chaos when projects grow)

None of these feel right. And the worst part? You're paying the copy-paste tax multiple times a day.

I started timing it. Between describing the feature, refining the breakdown, copying tasks, formatting them, and adding metadata—I was spending 20-30 minutes per planning session just on data entry.

Why existing tools miss the mark

The obvious question: why not just use a task manager with AI built in?

I tried. Most "AI task managers" do one of two things:

  1. Auto-generate subtasks based on templates (rigid, doesn't understand your actual intent)
  2. Let you chat with your tasks (helpful for search, but doesn't help with creation)

What I actually needed was a tool that understood intent. Where I could describe what I'm building in plain English, and it would:

  • Break it into structured tasks
  • Keep the conversation context (so I can refine without starting over)
  • Let me execute in the same place I planned

Not "AI features" bolted onto a traditional task manager. A workflow designed around how developers actually think.

The "one thread" approach

Here's what I wanted the workflow to look like:

Before (5+ steps):

  1. Open ChatGPT
  2. Describe feature
  3. Get task breakdown
  4. Open Linear
  5. Manually create each task
  6. Lose all the context from the conversation

After (1 step):

  1. Describe feature in Zyvia, get structured tasks in the same thread, refine if needed, start building

The key insight: planning and execution shouldn't live in separate tools. The conversation where you figure out what to build should flow directly into the workspace where you track how you're building it.

What this looks like in practice

Let me show you a real example from last week.

I needed to add webhook support to Zyvia. Instead of opening a separate AI chat, I just typed in Zyvia:

"Add webhook system for external integrations. Support signing, retry logic, and payload validation."

The AI broke it down:

  • Design webhook event schema
  • Implement signing with HMAC
  • Build retry queue with exponential backoff
  • Add payload validation middleware
  • Create admin UI for webhook management
  • Write tests for failure scenarios

I refined a few tasks in the same thread ("Actually, let's use a separate service for retry queue instead of in-process"), and the tasks updated instantly.

Then I just started coding. No context switch. No copy-paste. The planning conversation lived right next to the execution.

When this workflow works (and when it doesn't)

This approach isn't for everyone. It works best if you:

  • Build solo or in small teams (under 10 people)
  • Ship fast and iterate rather than planning months ahead
  • Use AI regularly for thinking through problems
  • Want less project management overhead, not more

It probably doesn't work if you:

  • Need complex Gantt charts or resource allocation
  • Have rigid sprint ceremonies that require specific tooling
  • Prefer visual boards over chat-first interfaces

For me—and I suspect for a lot of indie devs—the goal is to spend more time building and less time managing the process of building.

Why I built Zyvia

After months of the copy-paste loop, I started prototyping a better workflow. That prototype became Zyvia.

It's not trying to replace Jira for large teams or be the next Notion. It's built specifically for developers who want to:

  • Think through features with AI
  • Get structured tasks instantly
  • Execute in the same workspace without losing context

No boards to set up. No ceremonies. Just describe what you're building, refine it in the thread, and start shipping.

The bigger shift

The real change isn't the tool—it's the workflow.

We've accepted for years that "thinking" happens in one place (docs, chats, whiteboards) and "doing" happens in another (task managers, code, production). But AI removes that boundary.

When you can describe intent and get structured output instantly, the line between planning and execution blurs. You don't need a separate "planning tool" and "execution tool" anymore.

You just need one workspace where both happen.

Try it yourself

If the copy-paste loop sounds familiar, try this workflow for a week:

  1. Next time you're about to open ChatGPT to plan something, use Zyvia instead
  2. Describe your feature in plain English
  3. Refine the task breakdown in the same thread
  4. Start executing without switching tools

You can sign up free at zyvia.app—no credit card, no setup required.

And if it doesn't click for you, that's fine too. The goal isn't to convert everyone to a new tool. It's to show that the old workflow—AI in one tab, tasks in another—doesn't have to be the default anymore.