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SuperAgent is a multi-agent orchestration system built to automate complex, multi-step workflows across research, planning, coding, and general problem-solving tasks.
The platform uses a hierarchical Hub-and-Spoke architecture powered by LangGraph and Google Gemini. A central Supervisor agent interprets the user’s goal, breaks the task into smaller steps, and routes work to specialized agents based on capability.
The system includes a Coder Agent with isolated local code execution, a Generalist Agent for research and ideation, and persistent shared state to maintain context across agent handoffs. A React-based management dashboard provides visibility into agent activity, workflow progress, and approval-required actions.
Safety is a core part of the design. SuperAgent applies iteration limits to control runaway execution and requires human approval before sensitive code execution steps proceed. The code-execution workspace is isolated through Docker-based containerization.
I designed and developed the agent architecture, orchestration flow, safety model, code-execution environment, persistent context layer, backend services, and management dashboard.
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Aditya Chemicals — Corporate Manufacturing Website
Designed and developed the corporate website for Aditya Chemicals, a chemical manufacturing company serving international markets.
The website was structured to communicate the company's manufacturing capabilities, product portfolio, certifications, global presence, and industry experience through a modern and professional digital experience.
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Super clean typography and layout, Himanshu! Designing an impactful corporate site for international markets is executed really well here.
DebugTrace is Here 🔥
What if debugging could explain the problem, not just point to it? 🤔
DebugTrace pushes AI-assisted debugging through Bubble AI, bringing together workflow logic, database actions, JavaScript, speech recognition, and real Groq API integration with openai/gpt-oss-120b. 🔗
💪🏾Built to help developers trace problems, understand workflow logic, and give actionable fixes.
While pushing the project further, we encountered limitations with some advanced backend, API, and JavaScript workflow connections through the Bubble AI agent. Some integrations required manual intervention, but we continued pushing the build and brought the core AI idea to life.
This challenge is only the beginning. I plan to continue developing Debug Trace beyond this submission, refining its AI capabilities and pushing the idea further.
This is Debug Trace. Built to investigate what happens when AI meets real debugging workflows. 🔥🔥🔥
hey how do you make money from it ? tried to use but nothing happened