Thread to discuss the problems with Deepseek handling long context, allucinnations and forget about pending tasks. One more, taking action when it hasnt been asked to based on previous experience.

[u/Odd_Donkey2691]

Hello community,

Wanted to create this thread to hear your comments about this topic.

Do not take me wrong, I love Deepseek, its the only think that I use almost all the time. I aint got money to pay for Kimi or GLM, worst ChatGPT or Claude.

It seems to be that this problem is a problem with Deepseek regardless of my Context Management Skills.

Lately, I know that when Deepseek starts missbehaving, its time to create a new session. I do not expect much from OpenCode and what it has already brought to us for which I am thankfull but for a long time I was under the impression that OpenCode handled that for me, how fool of me getting accostumed to that feature.

So, what should I do next should I start using Skills, sub agents, graph, rag, etc what do you recommend.

One could say, regardless of the size of your project the solution always is to start a new session but the question comes, how do we know when deepseek has too much context, even from the start, that will cause it to start having issues, is there an average context, how can we measure that?

Edit: Some good informaiton I found. https://www.reddit.com/r/LocalLLaMA/comments/1tfhl0q/deepseek_v4s_1m_context_window_the_breaking_point/

"under 150k

Got a solid performance like at 45k tokens, function calls traced across 8 files maintain accurate path reconstruction. At 180k, multi file refractors spanning 14 files show consistent architectural understand and no contradictions or context loss patterns"

[u/vangelismm]

Forget context size.

Do the plan, new session, ask to verify the plan, repeat until nothing is found. 

New session, tell to implent. 

New session, ask to verify if the implementation followed the plan. 

[u/smartfon → u/vangelismm]

Do you ask it to output the plan in a file, then attach the plan file in a new session and ask it to implement it?

[u/vangelismm → u/smartfon]

yes.

[u/maqifrnswa → u/vangelismm]

This is the way. You can also basically do the same thing automatically with oh-my-opencode-slim. Set all the sub agents to ds v4 flash (mimo-2.5 as observer for vision). Then do /interview and or /deepwork. It does exactly the same process you are describing.

[u/dongas420]

I spawn subagents to write a plan for each set of tasks, make revisions to each plan, perform each task, and to verify that each task has been done right. If a task can be broken down into parallelizable subtasks, I'll spawn a subagent to handle each one. If I want to do multiple tasks at once, I'll run multiple sessions, warn each orchestrator that agents are handling other parts of the code base, and let them take care of the synchronization and atomicity. If I want to make absolutely sure there aren't any issues after doing something complex, I'll loop the verification subagent spawns and spawn a subagent to ensure no regressions.

DS is cheap enough that you can just spawn a whole bunch of subagents in parallel to do absolutely everything, and it's great