Ask HN: How do you manage your AI agents' context across clients and projects?

39 pointsby Michel_Aventin 1 day ago30 comments

Hi Guys, like many of you I work with AI agents every day and across several clients. The major time cost for me is to re-explaining context and past decisions, client rules, that we already do. To finish every tools as its own memory. So I’m curious how you actually handle this: 1. When you start a new session, how do you give context to the agent (context came from chat, mail, ticket ...) ? 2. Do you use more than one agent type (claude, codex ...) ? And if yes, how do you carry context between agents ? 3. If you work for several clients, how do you keep their context separate ? 4. The last time something went wrong ( an agent used a rejected approach, forgot a decision ...), what happened, and how much time did it cost to you ? 5. Did you paid or built a tool that helped you with these problems ? Do you still use it ? I’m exploring whether to build something, so I’m trying to learn how other people really work. Thanks for your return.

Discussion

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charlesabarnes · 3 hours ago

I use a gitignored ADR (Architecture Decision Record) directory in all of my repos right now. I mainly use Claude code, but I am dabbling in self hosted llms with oh my pi. There's no additional tools needed because usually llms "get it" natively. Also I tend to use a gitignored status doc for resuming where I left off. I tend to leave this stuff gitignored since it's all pretty "sloppy" and not really for consumption with others.

murillians · 2 hours ago

Spec driven design helps, OpenSpec/Git SDD Kit/ GitShipDone helps with the previous decision problems and design context. Most of these live in the project repos so they won’t pollute each other

m00dy · 2 hours ago

md files ?

chrisweekly · 2 hours ago

Matt Pocock's skills library^1 is the basis for my approach. 1. https://github.com/mattpocock/skills/blob/main/README.md

dumbmrblah · 2 hours ago

Self hosted Gitea wiki. Tell it to reference previous projects if applicable, standard setup principals etc. Agent continuously references and updates it.

stikit · 2 hours ago

Skills and good memory management are perfectly fine for cross project and client specific context. How are you currently using them in your workflow?

twodave · 2 hours ago

re: #1 I have a skill that essentially manages a daily board in json format and pulls in active or potential tasks from all my work streams (email, slack, grafana, ado, or even manual input). I have this management plane keep a journal for each day and then spin off sub-sessions to work individual items. I pretty much just run the thing on a loop, and since context is stored with the board itself there’s no issue closing down and restarting the session or clearing context occasionally.

option_greek · 2 hours ago

Context has to come from some project management mcp. Either good old JIRA or recent ones like agentcron.ai

edg5000 · 2 hours ago

I let agents read their own pre-compaction history often, as well as history form other sessions. I use both Codex and Claude Code. The main friction right now is keeping an overview of the sessions. Sessions don't have a max length for me. I run them as long as I want, but I keep session scope somewhat limited, usually to one discipline (e.g. software, CAD, electrical, sales, website). But I'll switch to the GUI apps soon, because they seem to have reached parity over the terrible CLIs that I use.

jen729w · 2 hours ago

Use my Johnny.Decimal system. [0] (Disclosure: I'm Johnny.) Every part of my life and business has a well-defined ID. This ID has: - A defining entry in my index [1], which is an Obsidian vault. - Therefore, also a Markdown note(s). - A folder on disk. I have a CLI [2] and agent skills [3] that help your LLM understand these relationships. Then you just: jd 21.15 // or search by title claude and now Claude has access to: - All of your notes from your index. This is your shared memory: it's designed to be human-readable. - All of its memory and transcripts from the fact that you launch it in the same folder whenever you do this piece of work. This is its internal memory. - With this comes the ability to easily `--resume` past conversations and so on. That's … it. Carefully-named Markdown files and folders. My numbers aren't a prerequisite – there's nothing magical about them – but they sure help. You can do this all for free. It takes about half an hour to set up. My MCP server [4] adds some quality-of-life but is paid (and means I can buy lunch :). > I’m exploring whether to build something I really wouldn't. I get 10 emails a week from people who already are and I don't see the point. It's a solved problem. [0]: https://johnnydecimal.com/ [1]: https://johnnydecimal.com/documentation/the-jdex [2]: https://johnnydecimal.com/documentation/jd-cli [3]: https://johnnydecimal.com/documentation/agent-skills [4]: https://johnnydecimal.com/software/mcp-server

raleighm · 2 hours ago
I recently experimented with breaking my life into segments (like the reporting segments of a company) and organizing Dropbox, text journals, and Claude chats in accordance with those segments. What you are describing is far more advanced and I'm intrigued. Checking out the site now.
- jen729w · 52 minutes ago
  …and your task manager and email and archives and physical papers and…

mapontosevenths · 2 hours ago

Karpathys LLM wiki with QMD. I have a small gatekeeper.py script the agent has to run to complete a round or begin a new one. One of the things it does (in addition to record keeping, linting, etc) is validate that the wiki has been updated with all the findings, lessons learned, and documentation for the round. The agent can't proceed until it's done. Then in the AGENTS.md they're told they can use QMD to perform semantic search of the wiki , and should before starting any significant work. It's expensive, in terms of tokens, but well worth it. I could reproduce any stage of my project if I wanted. I always know why they did what they did (if they do), and the agent's can't really forget anything important.

cpinto · 2 hours ago

so i built https://estratos.ai (5.) to ensure context from one client never pollutes a different client (or project, etc.) happy to explain the architecture and save you the sign up. it's set up as a layer-cake, you get layers like `root`, `agent`, `client`, `project`. 1./2. tell your agent to read/store its context from eg. `root.agent_name.client-a.project-a1` 2./3. next client is setup as `root.agent_name.client-b.special-project-b1` 3. when the agent loads the memory from there, it concatenates all the instructions from root, agent, client, project. 3. isolation is enforced by estratos so the llm doesn't get to know that there's a client-a subtree next to the client-b subtree this works better for me instead of the knowledge graphs, etc. because of the enforced isolation and the domain that it targets (accounting firms, where sharing context from one client to the next is deadly).

anyonecancode · 2 hours ago

I built a tool for myself for this. It runs on localhost and uses sqlite as a storage engine for metadata, and the XDG paradigm for content (eg ~/.local/share, ~/.local/state) I create topics, eg localhost:8080/topic/1. Each topic can have tickets, artifacts and sessions. Tickets are linked task tracking tickets (eg Jira, though not actually Jira in my case), artifacts are documents etc produced during sessions, and sessions are Claude Code sessions (though it wouldn't have to be Claude, that's just what I use). Sessions run in a terminal emulator in the browser. What makes this work is that I have some general purpose directions/context each topic gets, but there's also a running topic.md that gets updated at the end of each session. This way my context builds up and persists specific to that topic. Artifacts the agent produces (eg specs, plans) open up in a sidebar and render as HTML even though they're stored as markdown, and its easy to go back and find them from previous sessions. Session transcripts also are accessible from the Topic page. I do regularly run compaction on the topic.md, moving the full content to an archive and keeping the working context smaller.

hyldmo · 2 hours ago

I built a tool for this: https://farero.ai It stores every single chat regardless of ai provider in an indexed sqllite database on my mac and it injects a couple of extra mcp tools + a tiny prompt into codex/claude/opencode so the agent can search every single decision / chat I've ever had. I've also connected grok bot to this app, and i set up one for each project that can launch coding worktrees, monitor analytics for bugs, etc. Lets me run everything pretty hands off, I mostly jump in to review PRs or make decisions

akst · 2 hours ago

When I start a new project, I point to other ones where I'm happy with the quality as exemplars. I think its probably simpler to copy relevant stuff allow older projects go out of date until I start working on them again, then I tell the agent to look at the newer project to update its style. I have 2-4 on going projects I tend to a bit of that, normally 2 at a time, when I pick up one of the others, I really just do that; point to the older one. But within projects I don't really try to manage context, more so I just have an issue tracker which I add to keep track of stuff. In 2 of my long running projects I have some bootleg issue tracker built in (along with a screenshot QA tool which sends issues to the tracker) into the UI of the tool. I guess to extent I can, I try to avoid keeping some preferences in the context like formatting and linting (including directory structure and white listing imports in certain parts). I've been trying to find more ways to automate that way, so I keep my prompts and skills and goals limited to objectives where possible, so preferences like styles and structure are automatically enforced. When I have multiple agents, I just tell them to maintain write only ledgers to coordinate to avoid overlapping work, but it's easier when your project is broken up into self contained components with communication boundaries (defined in protobuf) like a FE/BE split or seperate service codebases (I reassemble it as a google style modular monolith to avoid running too many processes)

synapsomorphy · 2 hours ago

It seems many have built similar tools for solving this. Mine lets me run Claude and Codex (and pi but then you have to pay API rates) from the same localhosted webserver, and also schedule feature implementations to always hit the weekly usage cap. chats logs in jsonl (used by both) are saved per project in a never-pushed git branch. All agents run in Podman containers. I am just starting to play with a higher-level agent that just pushes the repo in a direction based on the human answering a thorough list of clarification questions. These have been really useful - Encourage short, commit-linked chats, to avoid the expensive cache writes. - Plot of LOC over time. Use better models until this starts not spiking a ton with every new feature. - Terminals kinda suck for agentic stuff IMO and we should stop cramming agent loops into them. Minimalism doesn't really help here, it's really nice to have built-in STT, real buttons, easy scrolling, etc etc etc. - The minimal delta is a commit. Every implementation turn must end with one or multiple, and a clean worktree. - Crystal clear, extremely granular usage data. This is something Claude Code and Codex will never give you, instead you get dark patterns nudging you to forget about the spend, while changing plan quotas every couple weeks.

hzz4444433333 · 1 hour ago

Here is a good suggestion: try using OKF (Open Knowledge Format) to store your context. Log every transaction in the OKF format as you process tasks. Even if you change your AI, simply reading the OKF file will do the trick.

jwilliams · 1 hour ago

As many have said - my strong steer build something[^1]. There are _great_ tools for this, but the biggest part of this is managing your own attention, and mental load. You can craft something that really helps _you_ manage all the spinning plates. In the case of my harness, I hoover up all the PR state into one place and then have a bunch of rules on how I interact with them (or not). Even down to a "swipe right to merge" card system. Works for me. My recommendation: A cloudflare PWA fully vibe coded with zerotrust on the front. Don't get too attached, tools are changing fast. Make it work and be prepared to ditch it when something better comes along. [1] https://jonathannen.com/build-your-own-lightsaber/

syngrog66 · 1 hour ago

in cases where no AI involved (which is 100% of cases) I just use my mind and English text in the form of written notes

petesergeant · 54 minutes ago

I keep my agents strongly sandboxed from each other using byre[0] (of which I am the author). I then use chezmoi[1] to manage my byre config -- including instructions for every box -- across multiple physical machines: shared instructions, tool preferences, etc 0: https://github.com/pjlsergeant/byre 1: https://www.chezmoi.io/

giancarlostoro · 46 minutes ago

> 1. When you start a new session, how do you give context to the agent (context came from chat, mail, ticket ...) ? This is what agents.md / claude.md is for, its the first file Claude Code and Codex read. Bonus: You can just ask Claude / GPT for tips on how to use these things more effectively.

spike021 · 30 minutes ago

I haven't used an AGENTS or CLAUDE file as much lately. I'm not sure how much more it helps, but generally I try to have one or more project md files. These are curated to whatever I am currently working on. Perhaps references to certain modules, commands, schemas for DB, etc. This way the agent doesn't get too much context it doesn't necessarily need. Again, not sure how much more effective or efficient it is but it seems to do better for my needs at least.

MadBrad-Develop · 27 minutes ago

Yo! I made a database that is based on the old school IBM1401 punchcard system, and set a wake phrase which works in the IDE's MCP so that the state is held with just a couple hundred tokens being used to wake and continue the work! I use multiple agents, and they all use the same database to maintain continuity. It allows me to use more than one at a time if needed(I do research) or switch between turns depending on the output required. I am using the Gemini's right now, but have used all the LLM's an a few smaller local models. I keep the clients context separate in different directories is all. My main agent works on all my projects. Last time something went wrong... agent said task was complete and verified but when I checked it was not "working" as planned. I suggested that there was a possibility of a reason, and my agent fixed it next run. Cost me 7 mins or so. I keep an eye on everything they do so things going wrong are typically easy fixes. I built it using my agents, and use it all day everyday. :-) The db has some other features I built in like a context odometer and a cabinet if workflows so I dont have to teach it stuff every time. I feel your pain, and hope you find a solid solution! Peace!

lp92 · 23 minutes ago

For the application I'm working on right now, I have tons of documentation. Every feature and even bug fixes have a TDD, FDD, Implementation Plan and/or RCA document in Markdown format. And these are grouped under logical sub folders. I also maintain a up to date master System Architect and Design document. Oh and a master index document listing every file along with a brief overview of the file. Its very easy to give specific contexts and reference this way. The index file really helps cut down the scanning done in a cold new session.

matthewslotkin · 14 minutes ago

Built a tool that locally indexes all past sessions for search and continuously builds and maintains a wiki https://smatt989.github.io/agentremote-site/

encruxx · 13 minutes ago

I’m using obsidian vaults. Currently I’m not collaborating with people a lot, so I use helpful plugins like Kanban to organize tasks. This helps me stay in the loop about projects and tasks, since Claude can create requirements. A friend of mine recently built campus [1] and while I personally haven’t gotten to use it, I’m currently trying to rebuild it as an obsidian plugin, which I hope will further help me stay organized. [1] - https://campus.flutterflow.io/

mceachen · 9 minutes ago

1. Minimal, sometimes only a link or a sentry ID and a skill name 2. Both. Context is kept up to date for every nontrivial task in a "technical project plan": https://photostructure.com/coding/claude-code-tpp/ 3. If you have separate clients, I would use a different username/login for each client so session transcripts (like in ~/.claude/... are segregated. 4. The more slack I give to agents, the more likely a session's work will have to be discarded. TPP (and looking at them before implementation starts) help avoid these very-off-course sessions from happening at least in my experience. 5. I've been iterating on coding and reviewing skills, and also just released the local reviewboard/PR tooling I've been using for the past couple of weeks. Everything is open source: fork and tweak to your content. https://photostructure.com/coding/

ksajadi · 4 minutes ago

i find the best way to think about this (and build around it) is to think how we as humans learn by doing: we have an idea of what to do (plan), then do, and then learn from what we did (right or wrong). you can also extend this to the entire team/company through what's usually called "institutional knowledge". here is how i approach it in practice: i've seen many try to generalize rules before doing things (design principles, guidelines, architecture,...) but often the best way is to start small, guide the agent step by step and (this is the most important part) at the end ask the agent to summarize what it learned and write it down. then on the next cycle, ask the agent to read the previous notes and do this again: read, do, write. i've been doing this for about 14 months now and have ended up with 2 categories of "knowledge": general (runs across multiple projects) and specific (per project). these are kept in two formats: markdown and "decision records". each decision is a markdown but has meta data around its state: approved, rejected, failed, etc. this growing body of knowledge works very similar to experience. one note about agent memory: first i find it opaque, secondly not sharable across team members, and thirdly not very human friendly (basically as the agent does more, you learn less about your own project due to the opacity of the memory). one thing i haven't been able to do figure out well yet is how to extract this from an existing codebase into this structured library of markdown and decisions. i'm keen to see how others do this. once you have this library, you can get your agents to respond to inbound signals (slack, sentry, axiom alerts, etc) and work with a high level of quality and confidence, provided that they follow the read, do, write cycle EVERY TIME. when i started this system, i used a committed markdown in git, then moved it to an obsidian (with MCP), then to Notion (so it's available team-wide) and finally built a product around it (bench47, if you care to check it out, disclosures, etc)