What is wrong with the current coding agent workflow
Hi, as the LLM models are getting smarter in coding tasks, we will soon be using agents as co workers, as current tools like github copilot and cursor are not optimized for team collaboration, we began building PhantomX, please give your feedback, if you think we are in the right direction or what should be changed for finding the optimized development workflow which works for both humans and agents.
In plain words
PhantomX is an AI coding agent designed for team-based development environments. It addresses limitations in existing tools like GitHub Copilot and Cursor that lack collaborative features. The tool aims to function as a coding coworker, helping teams establish optimized workflows that integrate both human developers and AI agents effectively. PhantomX is in early feedback stages, seeking input on whether its approach addresses real collaboration challenges in modern development teams.
written from the facts on this page · September 2026
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Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
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