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Most teams ignore their inference engine until the GPU bill forces the conversation, and by then they are migrating in production. vLLM is one of the most active open-source AI projects, with more than 2,000 contributors, and it credits PagedAttention for keeping attention key and value memory from going to waste. Worth knowing before the bill arrives.
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Some teams never seem to stop moving. They're on Attio, the agentic CRM.
Every customer signal is captured in one shared context layer, always current and compounding. Agents and workflows build pipeline, chase every buying signal, and move deals forward, an always-on revenue engine running alongside your team.
With Attio, you’ll get:
Leads automatically prioritised and routed to the right rep
Expansion and risk signals caught the moment they land
Follow-ups written in your voice, already there when you arrive
Teams like Parallel, Turbopuffer, and Wordsmith build on Attio. Are you one of them?
The Drops
Repovllm
93,039 stars · vllm-project/vllm
A high-throughput, memory-efficient inference and serving engine for LLMs, started in UC Berkeley's Sky Computing Lab.
Here is the real problem it solves. Attention key and value memory is where serving budgets go, and vLLM manages it with PagedAttention, continuous batching and prefix caching.
Quick start: pip install vllm, then vllm serve starts an OpenAI-compatible API server for popular Hugging Face models, so an existing client only needs a new base URL.
Catch: expect to tune batch size and KV cache settings yourself if your traffic comes in bursts.
Affiliaten8n
A serving engine handles the model; something still has to connect your agents to the apps they act on. n8n is a workflow automation tool with AI agents built into the editor. Connect over 500 integrations, deploy on your own infrastructure or their hosted cloud, and drop to code when the visual editor is not enough.
Use it for: running the plumbing between your agents and the apps they act on.
We may earn a commission.
Reposglang
36,702 stars · sgl-project/sglang
A high-performance serving framework for large language and multimodal models, from a single GPU to large clusters.
Use it for: workloads that mix text and image inputs where a single serving layer needs to handle both without duct tape.
Catch: smaller community than vLLM, so expect to read source when docs run thin.
RepocrewAI
59,269 stars · crewAIInc/crewAI
A framework for orchestrating multiple role-based agents that hand off work to each other.
Use it for: splitting a complex job into specialist agents (researcher, writer, reviewer) instead of one agent trying to do everything.
Catch: coordination overhead is real, debugging a five-agent crew is slower than debugging one script.
MCPjevmem
104 stars · Avinash-jetwani/jevmem
Automatic project memory for Claude Code: decisions, rules, and dead ends get saved and brought back next session.
Use it for: ending the "wait, didn't we already decide this" loop every time you reopen a long-running Claude Code project.
Catch: it's a young repo, triple digits in stars, worth watching rather than betting production workflow on today.
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From Our Partners
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Stop typing AI prompts. Start talking.
You think 4x faster than you type. So why are you typing prompts? Wispr Flow turns your voice into ready-to-paste text inside any AI tool. Speak naturally, tangents and all, and Flow cleans it up. Available on Mac, Windows, iPhone, and Android.
Start Here
Tell it what you don't want. Most people ask an AI tool for "something good" and get back something generic. The fix is telling it what to leave out.
1. Open any AI chat tool you already have.
2. Ask for something you need: an email, a workout plan, a product description, anything.
3. Before you hit send, add one sentence: "Do not use the words X, Y, or Z" or "Do not make it sound like a sales pitch" or "Do not include a greeting."
4. Send it and compare to what you'd normally get.
5. Compare the two answers and keep whichever sentence did the work.
TRY THIS: Take the last thing you asked an AI chat tool for. Ask it again, this time adding one sentence that says what you don't want in the answer.
One term, plain English: generic means written in a safe, average style that could apply to almost anyone, instead of sounding specific to you.
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Recommended
The same instinct that sharpens a single chat reply, ruling out the generic version before you ask, is what turns a pile of source links into a draft that actually sounds like you. HeyNews, the AI newsletter writer that sounds like you learns your voice from past issues, pulls stories from your sources, and hands you a publish-ready draft in minutes; 14-day free trial, then 50% off for 12 months with code WELCOME50. We may earn a commission. |
Frontier Signals
Matthew Green argues an agent worm is coming. In a post on sandboxing he describes agents in separate sandboxes leaving instructions for each other in a shared package cache, and calls that the two halves a worm needs. If your agents share files or inboxes, read it before wiring the next handoff. (Simon Willison)
Firebase's iOS SDK crashed apps worldwide for two to six hours. The Pragmatic Engineer reports a backend change crashed every app using Firebase analytics, and Google did not update its status page or publish a postmortem. Check how your own incident plan handles a vendor outage you cannot roll back. (Pragmatic Engineer)
Ars Technica reports a monthslong Pentagon data compromise, disclosed a month after a claimed FBI breach. The Pentagon records were stolen; the group behind the FBI claim says it has no plans to release that data. If your stack touches anything government-adjacent, check who has access to what. (Ars Technica)
Gemini 4 Argon claims a 1M-token output limit, but only government users and trusted cyber defenders in Google's Fairwind Program can use it for now. Third-party testers reached 1M with a new Long Decode Continuation feature that resumes long responses across calls; Google says it is rolling out to trusted testers first. (Latent Space)
Laya, a decision model from Convai Innovations, is free on Vercel's AI Gateway through October 31. It answers yes/no, choice, or scoring questions about context you give it, with probabilities. After that the standard model ID starts billing and the free ID stops serving. (Vercel Blog)
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