... Projects . If you use AI across different products, clients, codebases, or areas of your life, one giant pool of memory can get messy fast. Projects let you keep related memories together, so your AI can pull from the right context without you having to explain everything again. You can create a project for something like: a product you are building a client you work with a research topic a codebase a long-running personal goal Existing tags can also become ... ... project aliases, so memories you already have can be organized into projects without manually moving or rewriting them. Since 3.0, we have also added: Prompt Capsules , so you can give AI tools a stable set of important context

... makers I m building MemoryOS, and I d love feedback from people working on AI agents. Most AI products already store context. What interests me is how they govern it as things change: A user corrects an earlier preference. Two sources provide conflicting information. Several agents update context

... correct repos, branching properly or delivering a PR without CI failing. And I end up repeating instructions and copy-pasting CI errors and asking to fix it. I tracked this and I spent on avg 75mins a day repeating context and instructions. Anyone also facing this or found a way around it? Comment from Tasos V(@cryptosymposium): @_tallha_ijaz  yeah exactly. persistence is actually the key word here. because context

... Context Flow reached 4200+ users in 10 months with new paid users coming in every week - proving that context

... everything and let it sort things out. It turns out that's close to backwards. Chroma published a study in July 2025 that put a name to something a lot of us had felt but couldn't articulate: context rot. They tested 18 frontier models the GPT-4.1, Claude 4, Gemini 2.5 and Qwen3 families on how well they held up as the input got longer. The finding is uncomfortable if you've been dumping everything into the prompt: accuracy ... ... actually spending, and it's a lot smaller than the number. This is why the vocabulary shifted this year. We used to call the job prompt engineering how do I phrase this. Now the serious version is context

... into a refactor yesterday, my agent wrote a helper function the exact same one it wrote 90 minutes earlier in a file it created itself. Then it apologized. It always apologizes. The easy diagnosis is "it ran out of context". Except my session was sitting at 120K in a 200K window. Nothing overflowed. The context

... building Myna Player, an open-source local-first video player around a subtitle timing problem: translate too early and the model has too little context wait for more context

... source without that layer is just another link in a folder. Your insight turns it into knowledge. And now that we do more of our research with AI, that layer matters even more. AI has Information. It needs Your Context. Frontier models already know more facts than any of us ever will. But they don t automatically know: What your team already knows Which sources you trust Why you collected a specific paragraph What conclusions you reached six months ... ... What you re actually trying to produce You can give the same source to ten people and get ten different insights from it. AI sees the source. Context

... these tools produced syntactically perfect SQL against a schema they didn't actually understand, confidently answering the wrong question because they guessed which table "revenue" lived in. Now we're in the agentic phase: systems that plan, retrieve context, run analysis, check their own work, and hand back a narrative answer. A bunch of products sit here now, including ada.im, various "chat with your data" startups, and the analyst-agent features being bolted onto the incumbents. What's interesting ... ... with Claude," June 2026) reports that ~95% of their business analytics queries are automated at ~95% accuracy in aggregate. But the useful part isn't the headline number, it's the diagnosis. Their core claim: analytics accuracy is a context

... been thinking about a mistake we make when discussing AI-agent context: We treat all context

... mode from the navigator options menu under `Split view mode`, or toggle split view with `Ctrl+S`. Link Handling Create and inspect filesystem links from the navigator. - Create link : create symbolic links, shortcuts, hard links, and junctions from the context menu (`Create link`); - Link columns : optional list columns for Kind, Links, Link target, and Link status (`Valid`, `Broken`, `Unknown`, `Unsupported`); - Open behavior : directory shortcuts and symlink folders navigate to their targets; other link targets open with the default app; Native ... ... Properties Window On Windows, open the native system Properties dialog for selected items from the context

... give it instructions like you would give an intern: check that folder, use that info, forget about this part. That's basically what we built with the @aicf handle. It's a custom instruction system baked right into AI Context Flow, you just add it to your prompt and tell it exactly what context

... Context is king. Yep, I know, we've tried to solve it a bunch of times. But moving that context

... Hello, I created Decispher ( decispher.com ) to enable human developers and AI agents working alongside each other to share their context. It has some pretty cool features, like Branch Story (explains why a branch's code looks the way it does) and Session Context

... total $10.40 $8.12 Wait, that is only $68/month savings on raw math. Where does the $200 come from? The bigger savings: I stay in sessions longer without hitting compaction. Before compression, long sessions hit compaction at 35 turns, forcing context loss and repeated work. Now sessions last 55+ turns productively. Fewer repeated file reads, fewer redundant tool calls, fewer wasted output tokens on re-doing work. Does Quality Actually Stay the Same? I was skeptical too. Here is what ... ... measured over 4 weeks: Code that compiles first try: 78% (before) vs

... plans) are seamless, but any mutating action triggers mandatory, multi-factor confirmation gates. Prompt-based rules aren't enough; safety must be backend-enforced. Context Intelligence: Agents fail when they are blind or overwhelmed. NexQL leverages schema-aware retrieval (filtering and truncating wide table DDLs based on lexical relevance) so the model gets highly specific context

... community We're in the middle of our AppSumo launch for AI Context Flow, and I wanted to start a real conversation here rather than just drop a link. The problem we're solving: most people using AI tools daily are paying what I call an "AI context

... building a product with AI tools, here's how your morning probably looks: Open ChatGPT. Paste your project context. Ask your question. Get a decent answer. Switch to Claude for something else. Paste your context

... When it needs help with memory commands, it runs: empirical doc memory When it needs installation help: empirical doc install When it needs to discover what's available: empirical doc The detailed documentation is loaded only when needed. Less context. Better timing. What's interesting is that this is becoming a pattern throughout Empirical. The CLI uses on-demand documentation. Memory retrieval works the same way. Conversation context

... write and review code. The feedback loop with an agent that has real context is genuinely different from a chatbot. Linear forces you to actually prioritize instead of just accumulating tickets. Warp made the terminal feel less like 1985. Posthog seeing where users actually go vs

... Hard to believe now, but back in 2024 when we named our concept the "Open Context Layer," every pitch and networking event ended the same way: "What the heck is context

... Product Hunt community! First off, a massive thank you to everyone who has supported us and upvoted AI Context Flow. Since the launch, we ve heard a ton of great questions from you about how the tech actually works under the hood. We've also noticed a massive, shared frustration in the comments: AI memory is currently broken. Right now, you re forced to deal with two extremes: AI Amnesia: It forgets your project context

... problem: The wiki lives on his machine. Every time he opens a different AI tool, it knows nothing about it. That's not a Karpathy problem. That's everyone's problem. Some other people like Allie Miller built a "context vault," structured summary docs she feeds into Claude to avoid re-explaining herself every session. Teams are using Notion as a memory layer. Developers are writing custom scripts to sync context

... path was to drop the idea entirely. We thought about leaving this vision and building something else multiple times, but just couldn't. It felt like this problem mattered. We went through multiple iterations: data plugs, smart profiles, open context layer. But the core conviction never changed: your digital data should be like a USB stick, pluggable into whichever platform you connect to, sharing only what you allow. Because we believed the infrastructure question who controls your context

... work. If it ever tempts you to sit and watch it, I built the wrong thing. And your capability-versus-visibility framing is the correct diagnosis, by the way. The models stopped being the bottleneck months ago. The human's perception bandwidth is the constraint now, and context