Using two or three AI assistants without losing the thread
Short answer: none of the assistants can see the others, so the thread has to live somewhere you control — a notes file or a local archive searchable across all of them — and decisions have to be carried between them on purpose.
Most people now have more than one. One writes better, one reasons better, one has the larger window, one is what work pays for. The cost is that your thinking ends up split across services that know nothing about each other.
The three real problems
Context does not travel. Everything you established in one conversation has to be re-explained in the other, by hand, from memory.
History fragments. The answer you want is on one of three services and you cannot remember which. Each has its own search and none of them cross.
Allowances are separate and invisible. You discover you are out on the one you needed, while another sat untouched. More on limits.
Habits that help
- Assign roles deliberately. Drafting on one, review on another, long-document work on whichever has the window. Arbitrary switching is what makes the fragmentation feel random.
- Keep the artefact outside the chat. If the document lives in a file rather than in a conversation, moving between assistants costs a paste rather than a re-explanation.
- Write a reusable brief. One block describing the project, the constraints and the style, pasted at the start of any conversation anywhere. Ten lines beats re-deriving.
- Use the second one to check the first. The most valuable pattern in having more than one, and it needs almost no shared context — paste the output, ask what is wrong with it.
What does not work
Pasting whole transcripts between assistants. It burns the window immediately, and the receiving model weights the conversational filler as heavily as the conclusions. Carry decisions, not dialogue. The handover format.
Where a cross-platform archive changes things
The fragmentation is a search problem wearing a workflow problem's clothes. If one search covers every assistant you use, "which service was that on" stops being a question you have to answer.
Tvara archives locally from six platforms into one searchable store on your machine, so a phrase you remember finds the conversation regardless of where you had it — and Context Bridge pulls that answer into whatever you are typing now, on whichever site you are on.
Common questions
Can I share context between ChatGPT and Claude?
Not directly; neither can see the other. Carry decisions across with a short reusable brief, or use Tvara's Context Bridge to pull a past answer from any supported platform into the prompt you are writing. Context Bridge is part of Pro.
Is it worth using ChatGPT and Claude together?
For many people, yes: one for drafting, one for review. The most useful pattern needs almost no shared context: paste one model's output into the other and ask what is wrong with it.