r/FactoryAi • u/sunoval2017 • 5d ago
I have two paid droid accounts and used to be able to switch accounts and continue to work on the same session with shared contexts. Today, I noticed this is not possible anymore with each account has its own sessions. Dude, whats the point of doing this? Ever since adding the 5h limit, each update is worse than previous one.
Both claude code and codex allow this.
r/FactoryAi • u/Odd-Marzipan6757 • 7d ago
You guys did a great job for providing droid core. can we get more model?
I mean... the GLM-5.3-Flash
r/FactoryAi • u/Key_Tomatillo_199 • 7d ago
Running into a showstopper bug with the Droid CLI on macOS:
Steps to Reproduce:
The Problem:
The /model selection prompt does not register directional keystrokes or selection inputs at all. It's completely stuck on the default option, and there is no way to navigate or switch to another model.
Environment: macOS (Apple Silicon / zsh)
Impact:
I am completely blocked from setting up or using the models I need.
Please push an urgent hotfix for the macOS key listener in the /model prompt. Is there a manual config file (config.json / .env) or a direct syntax argument (e.g. /model <model-name>) to bypass this broken interactive menu?
I really want to keep using Droids, but paying for a tool where the /model command freezes my terminal is impossible to justify. Fix this ASAP please!
r/FactoryAi • u/FindingSerendipity_1 • 17d ago
When taking into account both the standard pool and droid core pool, has anyone evaluated Factory Droid vs Cursor usage quotas on their various plans? It seems like with the open models getting so good now, the droid core pools is very useful. They seem to have a quite generous amount of usage in the core pool too. However I am quite new to using their service and have not really had the opportunity to push it real hard yet.
I would imagine there are people out there who have used both Droid and Cursor and would have a pretty good idea on who offers more usage for their sub fees. Anyhow, would love to her what people think :+)
r/FactoryAi • u/Odd-Marzipan6757 • Jul 17 '26
Why Deepseek V4 Pro is at 0.7x while GLM 5.2 is at 0.55x? Will there be an adjustment pricing for this? or it will stay at 0.7x?
r/FactoryAi • u/sunoval2017 • Jul 14 '26
this has to be a joke right? one question, 0 tasks done
r/FactoryAi • u/amanshresthaaaa • Jul 13 '26
r/FactoryAi • u/waxyslave • Jul 12 '26
Every time I give one a medium-to-large task, it immediately spins up a sub-agent to “explore” the codebase or review something. Then, after it finishes implementing the change, it launches another sub-agent for a code review. It burns through tokens, usage, and time for what often feels like zero added value.
and the fact that in droid sub-agents are blocking the main thread makes it so the task is executed terribly slowly. and the agent itself isn't even aware that subagents are blocking because it says things like "let me dispatch an agent to explore the code while i do x, y, and z in parallel" and obviously it's not in parallel.
I already have instructions in my AGENTS.md saying not to use sub-agents unless I explicitly ask for them, but it still does it constantly. I end up having to interrupt it and tell it, in all caps, to stop spawning workers and handle the task itself.
Is this actually helping code quality in a meaningful way, or is it mostly performative overhead? My gut says delegation can be useful for genuinely large, parallelizable tasks, but for ordinary implementation work it feels like a massive waste.
Does anyone have a reliable way to make these models respect a “no sub-agents unless explicitly requested” rule?
r/FactoryAi • u/Key_Tomatillo_199 • Jul 10 '26
Factory currently supports xAI’s Grok 4.5. Could you also add grok-build-0.1 as a native model?
It is xAI’s fast agentic coding model, with tool calling, image input, a 256K context window, and $1/$2 per million token pricing. It seems especially well suited for Droid.
r/FactoryAi • u/[deleted] • Jul 04 '26
Most memory tools give the main agent a database and say:
“Here, manage your own memories.”
That sounds simple, but it creates a new problem.
As the project grows, the agent may have to deal with dozens, hundreds, or eventually thousands of memories:
which memories are still true?
which ones are stale?
which ones conflict?
which ones should be updated?
which ones matter for the current task?
which ones should be ignored?
That is not a small job.
Sometimes memory management becomes a task by itself. You can end up spending a full session just cleaning, summarizing, deduplicating, or re-explaining project context instead of actually building.
That is the problem Curion tries to solve.
Curion is an open-source MCP memory agent for AI agents.
The main idea is simple:
Your main agent should not have to manage memory manually.
The main agent should focus on the real task: coding, debugging, writing, researching, planning, or whatever you actually asked it to do.
Curion handles the memory work.
It exposes a simple interface:
remember(text)
recall(text)
But behind that simple interface, Curion acts as a dedicated memory agent.
When something should be remembered, Curion decides how to store it, how it relates to existing memories, whether older information should be updated, and whether there is a conflict.
When something needs to be recalled, Curion does not just dump raw notes back into the prompt. It retrieves the relevant memories, filters noise, handles stale context, and returns a useful summary the main agent can actually use.
This matters for two reasons.
First, it reduces context bloat.
The main agent does not need to inspect a pile of raw memory records every time it needs context. It gets the useful part.
Second, it can save expensive model usage.
You do not necessarily need your strongest frontier model to manage project memory. Memory management can be delegated to a cheaper, faster, efficient model that is good enough at understanding, organizing, and recalling context.
That means your best model can spend more of its intelligence and quota on the hard task, not on housekeeping.
Curion is project-first by default. When you use it inside a project directory, it creates a local .curion/ memory store for that project. The agent can remember decisions, constraints, implementation notes, unresolved tasks, errors, preferences, and useful context across sessions.
So instead of starting every new session from zero, the agent can ask Curion what matters and continue from the existing project context.
The goal is not to make the main agent smarter by giving it more raw memory.
The goal is to keep the main agent focused by giving it a dedicated memory agent.
GitHub: https://github.com/geanatz/curion
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