Charles Wehan

Adaptive — The Agent Computer - The computer for AI to get things done

Adaptive is a computer built for AI agents. Connect your tools, give it a goal, and your agent handles the rest — browsing, clicking, filing, ordering, reporting. What makes it different is Encoded Memory: as it works, it learns your systems and preferences and turns those learnings into reusable programs. Every task makes the next one faster. This isn't an assistant that helps you do the work. It's agents that does it for you.

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Charles Wehan
Hey Product Hunt 👋 By the end of this year, AI agents will use more software than humans do. We built Adaptive for that world. Most AI tools give you a chatbot. Adaptive gives you a computer — one that connects to your existing tools, operates them on your behalf, and actually learns as it works. Here's what makes it different: Encoded Memory. Every time Adaptive completes a task, it doesn't throw away what it learned. It turns those learnings into reusable programs. So the second time you need something done, it's faster. The tenth time, it's instant. We've been using it ourselves to automate support inboxes, run creator outreach, track expenses, generate reports — all without writing a single line of code. Would love to hear what workflows you'd hand off first. Drop them in the comments 👇 — The Adaptive Team
Liora

I can actually see this being perfect for those 3am "update all my dependencies" tasks - the AI agent could handle the inevitable cascade of breaking changes while I sleep. The multi-step reasoning demo on your landing page sold me - watching it pause to "think" about whether to upgrade React 17 to 18 felt oddly human. Does it preserve the exact dependency tree state so I can roll back if everything breaks spectacularly?

Dennis Xu

@lliora there's a toggle you can enable (we call this production mode) that let's you roll back to a previous version!

Taimur Haider

Hi Adaptive team, the encoded memory detail is the one thing that separates this from every other automation tool launching this week. Every competitor says set it and forget it. But they all secretly mean set it up again when it breaks.


The idea that the agent gets faster the tenth time you run something... that's a completely different promise.


I read the homepage. It doesn't say that loudly enough. It's sitting in a PH comment when it should be the first thing someone reads.

And by the way, congrats on the launch, @charliewehan.

Sai Tharun Kakirala

The Encoded Memory concept is what sets this apart for me. Most AI agent tools treat every task as a fresh start, but having agents that actually learn your systems and preferences over time is a massive unlock. The idea that every task makes the next one faster is exactly how AI should work. Looking forward to seeing how this evolves!

Lien Chueh

Are there ways to limit the agent's access? Especially if there are files on my computer that I don't want it to have access to so that there is never the chance of it accidentally modifying or deleting something that it shouldn't?

Dennis Xu

@lienchueh that's the beauty of it actually, it doesn't exist on your computer — it lives inside a cloud computer. You choose which files/things you want it to have access to

Ignacio Borrell

The Encoded Memory concept is really compelling. When the agent learns from repeated tasks, how does it handle edge cases that differ slightly from previous runs? For example, if a report format changes between runs, does it adapt on the fly or flag the difference for review? Congrats on the launch!

Dennis Xu

@borrellr_ generally, the agent will try to leverage existing prebuilt tools and then fallback to just normal agent workflows — and update itself in the process.

Andrés Felipe González Vélez

Interesting take on AI agents! QQ How do you handle privacy?

Dennis Xu

@andres_felipe_gonzalez_velez hey! Can you elaborate on the question? Privacy in what sense?

Jared Salois

Curious how this works for small teams - if two people are using Adaptive on shared tools like Google Sheets or Slack, do their agents learn separately or is there a way to share encoded workflows across the team?

Madison Hernandez

Encoded Memory is the differentiator worth watching here. Most agent tools treat every session as day one. If this actually compounds task-level knowledge into reusable programs, you solve the biggest drop-off problem in automation: users building workflows that break the moment something changes. The cloud sandbox is a smart trust architecture choice too.

Henry Kojo Owusu
this looks powerful. curious how you’re thinking about managing multiple workflows or agents without things becoming hard to track or debug over time
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