I've been building https://www.usesatori.sh/ to give persistent context to agents
Would be happy to onboard you personally.
Ask HN: What is the best way to provide continuous context to models?
11–20 of 48 posts
Re: Ask HN: What is the best way to provide continuous context to models?
#12[deleted]
Re: Ask HN: What is the best way to provide continuous context to models?
#13It's called continuous learning. You can't do it with an LLM service but you can if in training mode with bigger hardware.
Cursor and AI coding doesn't do it. It uses agentic subtasks.
Re: Ask HN: What is the best way to provide continuous context to models?
#14I open 4 chat windows with Gemini 3.0 Pro. I paste in all file contents to each window. I ask them "which files would an AI need to do $TASK effectively?"
Each of the 4 responses will disagree, despite some overlap. I take the union of the 4 responses as the canonical set of files that an implementer would need to see.
This reduces the risk of missing key files, while increasing the risk of including marginally important files. An easy trade-off.
Then I paste the subset of files into GPT 5.2 Pro, and give it $TASK.
You could replace the upstream process with N codex sessions instead of N gemini chat windows. It doesn't matter.
This process can be automated with structured json outputs, but I haven't bothered yet.
It uses much inference compute. But it's better than missing key inputs and wasting time with hallucinated output.
Re: Ask HN: What is the best way to provide continuous context to models?
#15What would you cover not-continuous?
Best methods I’ve observed -progressive loading (claude skills) & symbolic search (serena mcp)
Re: Ask HN: What is the best way to provide continuous context to models?
#16I've been building https://www.usesatori.sh/ to give persistent context to agents Would be happy to onboard you personally.
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Re: Ask HN: What is the best way to provide continuous context to models?
#17> what according to you is the best way to provide context to a model. Are you talking about manually or in an automated fashion?
Automated fashion would be what I'm curious on.
Re: Ask HN: What is the best way to provide continuous context to models?
#18I open 4 chat windows with Gemini 3.0 Pro. I paste in all file contents to each window. I ask them "which files would an AI need to do $TASK effectively?" Each of the 4 responses will disagree, despite some overlap. I take the union of the 4 responses as the canonical set of files that an implementer would need to see. This reduces the risk of missing key files, while increasing the risk of including marginally impor…
That sounds cumbersome and even more wasteful than my own method of simply dumping a fixed selection of project code in Gemini for each set of requests. Is there any benefit to pruning?
Re: Ask HN: What is the best way to provide continuous context to models?
#19i dont understand why these questions are so common? is it not obvious how one should use these capabilities? i compose my context in md file and send it through API. i wrote a simple lms.exe to send context and append response to the same file. why doesn't everyone else do that? i never believed in agents that compose their own context like Cursor. and i always pass the lowest reasoning value parameter to the API I can. why doesn't anyone else do this? you become dependent on a tool, you're already dependent some of you on fancy IDEs and agents. we're already dependent on top 3 vendors and openai is the only one that no one complains about from API key configuration side. you're gonna become dependent not only on LLMs but on the tooling as well? no thanks. anyone with a different opinion regarding this down to exact work flow, you are walking down the wrong path. you have to become efficient at converting electricity to text. admit it, some are just better than others while some will never get it at all. you know you won't because you know people in your life that never change their opinions about something, or always get into car accidents because they're a bad driver. you cant change these people and you might be one of them.
Re: Ask HN: What is the best way to provide continuous context to models?
#20What works best for me using Claude Code is to let the CC engineer its own context. You need to provide it with tools that it can use to engineer its context. CC comes with a lot of tools already (grep, sed, curl, etc), but for specific domain you may want to add more, e.g., access to a database, a cms, a parser for a bespoke language, etc.
With these i'll mostly just give it questions: what are some approaches to implement x, what are the pros and cons, what libraries are available to handle x? What data would you need to create x screen, or y report? And then let it google it, or run queries on your data.
I'll have it create markdown documents or skills to persist the insights it comes back with that will be useful in the future.
LLMs are pretty good at plan/do/check/act: create a plan (maybe to run a query to see what tables you have in your database), run the query, understand the output, and then determine the next step.
Your main goal should be to enable the PDCA loop of the LLM through tools you provide.