AgentMorph separates an AI agent’s identity, tools, knowledge, permissions, and execution instead of locking them into one assistant. Morph the same agent across Work, Learn, and Relax experiences, with BYOK and provider flexibility. Work Mode adds real multi-agent workflows, human review, and WebMCP integration. This release was extensively reworked with GPT-6 Astra to turn a fragmented multi-mode POC into a usable product.
What real task does your product handle with GPT-6 Astra?
Maker
GPT-6 Astra handles complex, multi-step software engineering across AgentMorph’s existing codebase through Codex.
I used it to audit and repair cross-module architecture, implement WebMCP integration, build real multi-agent Research and Reviewer workers, add observable worker events and human review, validate provider portability, and recover broken Work, Learn, and Relax workflows.
Rather than generating a new demo from scratch, Astra had to understand an existing system, trace failures across modules, preserve working capabilities, implement targeted changes, and repeatedly validate real browser and product golden paths.
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Maker
📌
Hi Product Hunt! I’m Waldo, the solo maker behind AgentMorph. 👋
I started this project after repeatedly running into the same problem with AI agents: an agent is often packaged as one fixed assistant. If I want a different role, set of tools, knowledge, or behavior, I end up rebuilding or duplicating much of the setup.
AgentMorph explores a different approach.
Identity, tools, knowledge, permissions, and execution are separated instead of being locked together. The idea is that an agent can “morph” for different contexts—from Work and Learn to more interactive Relax experiences—without rebuilding everything from scratch.
This started as an experimental agent architecture. For the GPT-6 Astra Challenge, I spent the past two weeks using Astra to revisit and rework the project across multiple layers—from WebMCP and real multi-agent workflows to provider portability, Work Mode, Learn Mode, Relax Mode, and the product’s golden paths.
Astra didn’t create AgentMorph from scratch. It helped me take a fragmented POC, trace problems across an existing codebase, repair integrations, and push it toward something people can actually try.
It’s still an early POC, and that’s why I’d especially love honest feedback on one question:
**When you try AgentMorph, is it immediately clear what “morphing” an agent gives you that a normal AI assistant doesn’t?**
Thanks for checking it out! I’ll be here reading and replying to feedback throughout the launch. 🙌