Productivity1 month ago
Recall | AI memory for your work sessions
Organize and retrieve your work sessions with AI-powered memory.
@vitverb · X
hi :) One tap back to the work you meant to finish. No tasks to manage. Nothing to set up. Local-first
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Organize and retrieve your work sessions with AI-powered memory.
@vitverb · X
hi :) One tap back to the work you meant to finish. No tasks to manage. Nothing to set up. Local-first
Store shared memories once and reuse them across AI systems and your team.
Repeater22746 · HN
ContextVault – Shared memory layer for your AI and your team
Add persistent memory and knowledge to AI agents with drop-in files, URLs, and native MCP integration.
kitforai · GitHub
kitforai Kit for AI developer hub — official SDK, Claude Code plugin, MCP setup, and llms.txt.
Share context across AI agents so they remember your codebase and task history.
@dorikuio · X
AI agents have amnesia — Claude Code figures out the codebase, an hour later Codex starts from zero. So I built a shared memory + task board for every MCP agent — Claude Code, Codex, Cursor, Gemini CLI: Is this just my problem? Help me find out.
Log and retrieve decisions with complete provenance for humans and AI agents.
@burn2delete · X
Persistent memory system for AI agents in Claude Code, Cursor, and other MCP-compatible applications.
FabianBeiner · HN
CMEM – Persistent Memory for AI Coding Agents
Save connections from X and LinkedIn with context to reconnect at the right time.
@aditya_founder · X
A lightweight Python runtime that runs in your browser, weighing under 200 KB.
dylansuttonc · HN
When I started programming Edge Python more than six months ago, I was looking for a version of Python that weighed less than 200 kb so it could reach any device, sandboxed by design, built with browsers in mind, decoupled from the operating system and very fast. Today the closest competitor would be MicroPython. However, it did not solve my real problems or the problems of the people who use the project. * Managing async and blocking code on the event loop. MicroPython inherits CPython's blocki
Versioned memory workspace for your ideas and code, readable by connected AI assistants.
@JohnTremendol · X
does this look vibe coded?
Semantic caching reduces LLM token costs and latency for AI queries.
u/ornymo_official · Reddit
how to reduce ai costs there are lots of way to reduce costs but there all complex to setup i know this cause i tried one in production so i built ornymo we cache meaning not the exact string allowing us to give same awnsers thus reducing llm costs and latency check it out at ornymo.com free for a limited time and let me know your feedback submitted by /u/ornymo_official to r/buildinpublic [link] [comments]
Drop a file to get a shareable link—no signup required.
@gonelf · X
So many things - dead simple way to share projects within your team - dead simple base - no backend forms - ez directory submissions - a Lego event
Calculator to estimate crypto airdrop token values based on market cap and distribution parameters.
@baofuzailushang · X
有位大兄弟制作了一个计算variational积分价值的网站，使用起来很方便： 我以市值1.5B，总积分9.3M，空投25%来计算，每分的价值是40u，1000分就是40000u 我认为这是保守估计，如果8月份variational上线了swaps和api，数据会更好看，而且以var的格局来看，空投应该不止25%,可能30%以上！