Engineering
Engineering deep-dives from the Barb team: how we build memory infrastructure for AI agents — retrieval, embeddings, the memory graph, and performance.
17 posts
SMFS: making agentic retrieval 55% cheaper AND more accurate
We launched SMFS.ai (Barb Filesystem) a few weeks ago, with a simple bet: We can redesign the filesystem specifically for agents, with special files, structures, and commands that it can use for it's tasks. Today, SMFS is used by hundreds of companies to power their agents. TLDR: You can rea
Introducing Dynamic Dreaming: barb now connects the dots, for you.
Dreaming is magical. TLDR: We're launching Dynamic Dreaming in barb today, which automatically works if you're using barb in any way - API, OpenClaw, Hermes agent, etc. We (humans) dream to condense and reflect on our thoughts, not only things that happened today, but a weird blend o
Dear reader, we just made barb insanely cheap... the Context Cloud
When I first started building barb, I had one goal: To build the best memory system for AI. I would talk to customers, and find out that memory was not the only thing they needed - They were all setting up 7-8 different vendors at the same time. Memory, Retrieval, Profiles, reranking, embedd
Introducing @barb/tools v2.0.0
Today we're releasing v2.0.0. This release unifies the API across all agents sdk integrations from AI SDK to Mastra, makes conversation identity a first-class concept, and ships with memory saving on by default. What's new in v2.0.0: * Unified config-object API * customId: required conversation
barb will make your Hermes-agent crazy powerful
Today, we are launching barb support to your Hermes agent TLDR: you can use barb now in your Hermes agent, it totally free to get started - https://barb.ai/docs/integrations/hermes In case you missed it: Hermes Agent is a self-improving AI agent from Nous Research. It meets yo
Solving the Precision-Recall Tradeoff: Search Result Aggregation
When you're building memory for AI, search is your foundational layer. The way search generally works is straightforward: the user defines a query, and then sets a limit (top-K) on how many search results they want returned. Usually, this is set to 10 or 20. Once the request hits the server, a resp
We broke the frontier in agent memory: To prove a point.
Read the follow up here! https://x.com/DhravyaShah/status/2036243995500966260?s=20 TLDR: This was a big social experiment that we did to create a new standard for reporting memory system’s quality. It was a parody. A few months ago, we published our first research report showing Barb achi
Infinitely running stateful coding agents
We built a plugin for Claude Code and OpenCode that gives your coding agent persistent memory. It remembers your preferences, learns your codebase, and never loses context mid-conversation. The result is an agent you can run for months without starting over. Here's how it works, in the order you'll
Why everyone is complaining about OpenClaw's memory (it sucks) - and why barb fixes it.
TLDR: Today, we are releasing a new version of our openclaw plugin - https://github.com/barbai/openclaw-barb. This post is going to be a bit technical, so bear with me (or bookmark for later!) In this post, I will talk about what we do about OpenClaw memory, and how we fix it. BENCH
We added barb to Claude Code. It's INSANELY powerful now...
Today, we are launching the Barb plugin for Claude Code! TLDR: You can use barb in claude code now. - https://github.com/barbai/claude-barb Claude code has genuinely changed how I work. But there's this one thing that drives me crazy... Every day, I have to explain the
Clawd / Molt bot's memory SUCKS. We gave it barb.
I'm the founder of barb. Clawd/Molt bot is blowing up right now, with many, many use cases. I set it up, too, and have been using it through telegram. TLDR: just go to https://barb.ai/docs/integrations/clawdbot to set up barb for your clawd bot. However, me and some other fri
Building code-chunk: AST Aware Code Chunking
At Barb, we're building context engineering infrastructure for AI. A huge part of that is dealing with code: ingesting repos, understanding structure, and making it searchable. The problem is that most code chunking solutions are terrible. We built code-chunk to fix this. It's now the best A
Unified Memory That Works Where You Work: Your Second Brain With Barb
Hi everyone, I’m Dhravya, the founder of Barb. I want to start with a little story behind why this product means so much to me. You can also skip straight to what it is and how it works below. Anyways, when I started Barb one year ago, we were a consumer app that acted like a second
Barb just got faster on PlanetScale
What is Barb? Barb completes the missing part of the LLM puzzle: memory. Just as memory is crucial for human intelligence, it's essential for truly intelligent AI systems. We've built a portable memory engine that works seamlessly across different LLMs through multiple interfaces, inc
We solved AI API interoperability
One API to rule them all, One spec to find them, One library to bring them all and in the TypeScript, bind them. When we were building the the Infinite Chat API, initially, we only supported the OpenAI format. This was fine, until a lot of our customers started asking, asking for more. Skip to
The UX and technicalities of awesome MCPs
Last month, we launched the Barb MCP, mostly to test our own infrastructure and get some initial traction. It blew up. To my absolute surprise, the initial launch itself got half a million impressions (!!!). Then, we launched and got #2 on ProductHunt too. Seems like people absolutely loved
Architecting a memory engine inspired by the human brain
Language is at the heart of intelligence, but what truly powers meaningful interaction is memory — the ability to accumulate, recall, and contextualize information over time. Large Language Models (LLMs) have mastered language, but memory remains their Achilles’ heel. Every leap in context window s