This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
SwitchNext is a multi-model AI workspace built around persistent work. Switch models mid-thread with the context you choose, compare different approaches, and when the work becomes implementation, carry the same thread into Code where Agent Mode can implement, improve, and audit code workspace changes with reviewable diffs. No provider API keys required. Sign in and start with 50K complimentary SwitchNext tokens.
Hi Product Hunt community, this is Gonzalo, the engineer behind SwitchNext.
The best AI model changes depending on the work. Your workspace shouldn't.
I built SwitchNext because switching models was easy. Continuing the same work across them wasn't.
My workflow was fragmented across ChatGPT, Claude, Gemini, DeepSeek, coding tools, and separate conversations.
Every switch made me the integration layer.
Copy the prompt. Rebuild the context. Explain the decisions again. Move the useful output back. Repeat.
I wanted the work itself to survive changing the intelligence working on it.
That's what SwitchNext is built around.
SwitchNext is a multi-model workspace built around persistent work: one thread across Chat and Code that survives model changes.
SwitchNext handles model routing through direct provider APIs in a unified routing layer and orchestrates the context behind that workflow. Agent Mode is built by SwitchNext and works directly in the code workspace, letting you change the model powering the agent while carrying forward the thread context, code workspace state, and previous changes.
Start with one model. Switch mid-thread with your conversation context carried forward by default, or choose exactly what carries forward. Compare models against the same problem, keep the perspectives that matter, and continue from them.
And when thinking becomes implementation, the thread moves with it.
Take that same conversation into Code, where Agent Mode works across multiple files and generates reviewable changes directly against the code workspace.
Change the model powering the agent, and the next intelligence can continue from the conversation, decisions, files, and changes already established, whether that means implementing, improving, challenging, or auditing what came before.
The model changes. The work persists.
The point isn't to automate the human out of the workflow.
You choose the model. You choose the context. You choose the direction. You decide what becomes part of the work.
SwitchNext started as the workspace I wanted for my own AI workflow.
Today, I'm opening its first public release.
The core workflow is here. What gets deeper next will be shaped by real usage, feedback, and how people choose to work with SwitchNext.
I’d especially love to hear where SwitchNext fits, or doesn’t fit, into your own AI workflow after trying it. What would make it more useful for the way you work?
Try SwitchNext: switchnextai.com Keep the work. Change the intelligence.
↓ The launch demo follows one continuous thread as an engineer: compare → plan → implement → improve → audit. It's engineering-shaped because that's my own workflow, but persistent work across models isn't code-specific.
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About SwitchNext on Product Hunt
“One thread across models, Chat, Code & Agent Mode”
SwitchNext was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #143 on the daily leaderboard. SwitchNext is a multi-model AI workspace built around persistent work. Switch models mid-thread with the context you choose, compare different approaches, and when the work becomes implementation, carry the same thread into Code where Agent Mode can implement, improve, and audit code workspace changes with reviewable diffs. No provider API keys required. Sign in and start with 50K complimentary SwitchNext tokens.
SwitchNext was featured in Artificial Intelligence (479.1k followers), Bots (110.9k followers) and Tech (632.9k followers) on Product Hunt. Together, these topics include over 295.8k products, making this a competitive space to launch in.
Who hunted SwitchNext?
SwitchNext was hunted by Gonzalo Lara. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how SwitchNext stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Gonzalo Lara
Hi Product Hunt community, this is Gonzalo, the engineer behind SwitchNext.
The best AI model changes depending on the work. Your workspace shouldn't.
I built SwitchNext because switching models was easy. Continuing the same work across them wasn't.
My workflow was fragmented across ChatGPT, Claude, Gemini, DeepSeek, coding tools, and separate conversations.
Every switch made me the integration layer.
Copy the prompt. Rebuild the context. Explain the decisions again. Move the useful output back. Repeat.
I wanted the work itself to survive changing the intelligence working on it.
That's what SwitchNext is built around.
SwitchNext is a multi-model workspace built around persistent work: one thread across Chat and Code that survives model changes.
SwitchNext handles model routing through direct provider APIs in a unified routing layer and orchestrates the context behind that workflow. Agent Mode is built by SwitchNext and works directly in the code workspace, letting you change the model powering the agent while carrying forward the thread context, code workspace state, and previous changes.
Start with one model. Switch mid-thread with your conversation context carried forward by default, or choose exactly what carries forward. Compare models against the same problem, keep the perspectives that matter, and continue from them.
And when thinking becomes implementation, the thread moves with it.
Take that same conversation into Code, where Agent Mode works across multiple files and generates reviewable changes directly against the code workspace.
Change the model powering the agent, and the next intelligence can continue from the conversation, decisions, files, and changes already established, whether that means implementing, improving, challenging, or auditing what came before.
The model changes. The work persists.
The point isn't to automate the human out of the workflow.
You choose the model. You choose the context. You choose the direction. You decide what becomes part of the work.
SwitchNext started as the workspace I wanted for my own AI workflow.
Today, I'm opening its first public release.
The core workflow is here. What gets deeper next will be shaped by real usage, feedback, and how people choose to work with SwitchNext.
I’d especially love to hear where SwitchNext fits, or doesn’t fit, into your own AI workflow after trying it. What would make it more useful for the way you work?
Try SwitchNext: switchnextai.com
Keep the work. Change the intelligence.
↓ The launch demo follows one continuous thread as an engineer: compare → plan → implement → improve → audit. It's engineering-shaped because that's my own workflow, but persistent work across models isn't code-specific.