Where the AI market is talking

Show HN: LongTerMemory Study tool with no subscription built with QDrant and RAG

Nice use of Qdrant for the retrieval layer.Curious how you're handling the question generation, are you chunking the study material and generating per chunk, or doing something more document-level?

Show HN: LongTerMemory Study tool with no subscription built with QDrant and RAG

After trying out various study tools, I decided to create my own. I wanted a quick and simple way to upload any study material, have the app generate questions, and then set up a daily review schedule. So, I built it by creating a RAG system and a scheduler to trigger the daily review sessions.

GPT‑Live

I have. They are not to my taste. Here's a voice I really enjoy listening to. https://elevenlabs.io/app/voice-library?search=zNsotODqUhvbJ... If I could have Christopher Lee, or Stephen Fry, I would.

Show HN: A Pipeline for Making 10-minute AI Movies with Claude Code and Seedance

I've been working on this Claude Code pipeline for making 10-minute movies, gluing together Seedance (videogen), Nano Banana (image gen), and ElevenLabs (voice gen), and using Claude as the director. My repo contributes a markdown playbook and a worked example which should make it easier for other people to make their own short movies. A first-pass movie takes around 2.5 hours of wall clock time and costs around $200, and iterating is easy thanks to intermediate artifacts like storyboards and voice samples.

Speech Recognition and TTS in less than 500kb

I made a little python wrapper around it to serve an HTTP endpoint that’s OpenAI/elevenlabs compatible https://github.com/clayrosenthal/bootlegger

LM Studio Bionic: the AI agent for open models

Wouldn't most opensource harnesses work with lmstudio? I assume it has an "openai" style chat API like every other model provider? What's special about it vs langchain deep agents or pi or pydantic-ai?

Show HN: Companion eBook for The Odyssey audiobook narrated by AI Michael Caine

I've been enjoying the Michael Caine voice clone narration of the Odyssey, but noticed it uses Greek names (Odysseus, Poseidon, Zeus), whereas the William Cullen Bryant translation ElevenLabs used as the basis for the audiobook uses the Roman names (Ulysses, Neptune, Jove). I tried reading the WCB translation while listening, but it got so confusing I had a go at making a companion edition that matches the names in the narration. It's free, non-commercial, and obviously not an official ElevenLabs product, just a fan attempt. Mostly for my own use, but thought I'd share in case it helps anyone else reading The Odyssey ahead of the Nolan film :)

Open-source memory for coding agents, synced over SSH

I have developed an open-source memory system for agents accessible over MCP, which makes it possible to access it via any coding agent locally (claude-code) or via mobile (Claude AI, Mistral AI, etc). The primary storage mechanism is .md files stored as Notes in Nextcloud; however, since Nextcloud supports a rich ecosystem of apps such as documents, rss feeds, calendar, etc, your knowledge base can grow with you. All content can optionally be indexed and available via semantic search - powered by a Qdrant vectordb. The biggest cost drivers of a system like this is the memory required to host the vectordb - I'm really curious how others are optimizing their knowledge base. Thanks OP for doing to work in summarizing these tools! If you're interested either the MCP server or Nextcloud App f…

Ask HN: Who is hiring? (July 2026)

Full-Stack Developer | India (Open to Relocation & Visa Sponsorship) Tech Stack: React, Next.js, TypeScript, Node.js, FastAPI, PostgreSQL, MongoDB, Docker, GitHub Actions, REST APIs, AI/LLMs (LangChain, OpenAI, Gemini) Open-source contributor to Meshery (CNCF), KubeEdge (CNCF), and omegaUp. Built production-ready projects including Error404 UI and InsightCareer AI. GitHub: https://github.com/manishpatel00 � Portfolio: https://manishdevin.vercel.app Error404 UI: https://error404-ui.vercel.app Resume: https://drive.google.com/file/d/1g1feAoFWI7AVZBjEM0UYAFBpbr1... I'm interested in the Founding Full-Stack Software Engineer role and will also send my application via email. Thank you!

Show HN: Low-latency local LLM runner via OpenJDK Panama FFM (Java 22)

I addressed this a little bit in the comment below, but the cycles add up. I'm doing some pretty crazy things higher up in the stack, that I'm not quite ready to release yet. But even micro optimizations here add up at the scale I'm working at to allow me the headroom I need. I'm relying on a high-frequency recursive agentic loop that chokes a real-time guarantee without every optimization I can give it. I started by removing the IPC overhead from a weaviate db connection, and doing all my vector math in house with a lightweight sqlite db. This became the next obvious target for optimization once I saw how much that saved me doing things in-house.

Towards a Harness That Can Do Anything

I get what your saying, however we don't need to be stuck with the Claude code harness. You may find this interesting. https://www.langchain.com/blog/tuning-the-harness-not-the-mo...

Ask HN: Who is hiring? (July 2026)

Instrumentl | Senior (and above) Backend Engineer | REMOTE (US + Canada) | Full-time | 175,000 - 220,000 | Instrumentl is a profitable, hypergrowth, YC-backed SaaS platform building the operating system for grant-funded organizations. More than 5,500 nonprofits use Instrumentl to discover, track, and win grant funding, from local community organizations to the San Diego Zoo and the University of Alaska. Collectively they’ve moved over $1 billion through our platform. Looking for a strong Python engineer to build AI features end to end, from rapid prototype to production and the evaluation that keeps them honest. Join the engineering of 22 and company of almost 100 located all over the world. Note, AI experience is a plus, but not required. Stack: Python (FastAPI), Langchain, Postgres, Red…

The disk that never woke up: The Elasticsearch and Qdrant saga

Ask HN: Who is hiring? (July 2026)

Namecoach/Euphonia | Founding Voice AI Engineer (part-time, path to CAIO) | SF or Remote | REMOTE | Contract / Part-time, ~$30-120/hr by seniority, potentially converting to FT Namecoach has spent 10 years building the largest verified pronunciation dataset of its kind: ~2M self-recorded name pronunciations, plus a large corpus of human-verified phonetic spellings. We're now building Euphonia ( https://euphonia.namecoach.ai/ ), a provider-neutral middleware layer that makes any TTS engine pronounce names, acronyms, and other out-of-vocabulary terms correctly. The new wave of TTS (models from OpenAI, ElevenLabs, etc) sounds great but gives you almost no phoneme-level control, so it gets lots of names and words wrong and you can't easily fix it. We sit in front…

Apple's new SpeechAnalyzer API, benchmarked against Whisper and its predecessor

For my current purposes, I need a speech-to-text model/API to also emit word-level timestamps - for now, that makes ElevenLabs's Scribe v2 the best multiplatform, multi-language choice though it does look like this SpeechAnalyzer API provides them (although only for English).

Show HN: Self-hosted voice AI agent for Asterisk/FreePBX

Hi HN folks ! I am the author of AVA, a self hosted AI Voice Agent that plugs into Asterisk/Freepbx so you own all the aspects of an AI Voice agent in your own infrastructure. It uses Asterisk native Audiosocket/RTP with python engine to run STT,LLM and TTS loop. The project support several full providers openai, gemini, grok, elevenlabs out of the box and also provides options to build custom pipelines by choosing different stt tts and llm. It also supports full local agent if you have a GPU with 25GB RAM which enables realtime conversation along with tool calling. I started this as a hobby project last year when I started exploring voice agents and every saw every Saas tried to lock you in their eco system. Since then project has taken off and a lot of asterisk people started …

Ask HN: Who wants to be hired? (July 2026)

Location: Ahmedabad, India Remote: Yes Willing to relocate: No Technologies: Python, Django, DRF, FastAPI, PostgreSQL, LangChain, RAG pipelines, MCP servers, agentic AI workflows, Stripe integration Résumé/CV: https://www.linkedin.com/in/himanshu-more-dev/ ; https://todo-smoky-alpha.vercel.app/ Email: hmore7978@gmail.com Backend/AI engineer with production experience building RAG pipelines, custom MCP servers, and agentic workflows. Recently built an AI Todo Assistant (FastAPI + LangChain + MCP + Gemini Flash) and a multi-tenant SaaS app with real-time location tracking. Open to freelance/contract work, quick turnaround on RAG/agent integration tasks.

Spiel: Chrome extension that reads articles/PDFs aloud with local TTS

Sounds like a very cool project. I often use the ElevenLabs app/extension to listen to articles, but I would love to have a local option to do this. I'm on Windows though, so I look forward to your future updates.

Ask HN: Who wants to be hired? (July 2026)

Location: Skopje, North Macedonia Remote: Yes (CET timezone, comfortable with EU/US overlap) Willing to relocate: No Technologies: Python (FastAPI, LangChain, LangGraph), RAG systems (Neo4j GraphRAG, pgvector), LLM integration (OpenAI, Anthropic, local Llama via Ollama/vLLM), OCR pipelines (Google Vision, PaddleOCR), MLOps (MLflow, GitHub Actions CI/CD, Docker, AWS ECS/Fargate, ECR), classical ML (scikit-learn, regression and classification models), SQL/PostgreSQL, evaluation tooling (DeepEval, LangSmith), Frontend (React), Mobile apps (React-Native). Résumé/CV: https://github.com/hamzaarifi98/mycv Email: hamzaa.arifii@gmail.com Portfolio: https://github.com/hamzaarifi98

Ask HN: Who wants to be hired? (July 2026)

Location: Austin, TX Remote: Yes Willing to relocate: No Technologies: • Programming languages: Go, Python (FastAPI, Flask), Node.js, Java (Spring Boot), PHP. • Backend architecture: microservices, REST APIs, event-driven design, idempotency, concurrency. • Cloud and DevOps: Amazon Web Services (AWS) S3, Lambda, EC2; Kubernetes; Docker; CI/CD pipelines. • Data stores: PostgreSQL, MySQL, Redis, Memcached. • Messaging: Apache Kafka, RabbitMQ, Google Pub/Sub. • AI and machine learning: retrieval-augmented generation (RAG), vector databases (Pinecone, Weaviate), large language model (LLM) APIs. • Observability: Prometheus, Grafana, Datadog, Elasticsearch Logstash Kibana (ELK), distributed tracing. • APIs and security: gRPC, GraphQL, OAuth 2, JSON Web Tokens (JWT), role-based access …