Where the AI market is talking

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 …

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

Data engineer with 3.5 years, built PySpark pipelines processing billions of records daily, dimensional models, and Unity Catalog governance serving 10+ teams. Recently hands-on with LLM systems: RAG on Bedrock, multi-agent POCs, MLflow tracing. Looking for data/AI engineering or forward-deployed roles,. Location: Austin, TX Remote: Yes (US) Willing to relocate: No Technologies: Python, SQL, PySpark, Databricks, Delta Lake, dbt, Airflow, AWS (S3, Glue, Bedrock, EMR), Snowflake, Redshift, Kafka, Docker, Terraform | AI: RAG, LangChain, CrewAI, MLflow, LLM orchestration Résumé/CV: github.com/analondhe Email: anaghaalondhe7@gmail.com

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

Location: Tashkent, Uzbekistan Remote: Yes Willing to relocate: Yes Technologies: Python, FastAPI, LangChain, RAG (pgvector, FAISS), classical ML (XGBoost, LightGBM, CatBoost, scikit-learn), React, Next.js, TypeScript, Flutter, PHP, MySQL/Postgres, Supabase, Docker Résumé/CV: https://drive.google.com/file/d/12O_duaC2O47aFvF_7OoSc97XEP9... GitHub: https://github.com/ioa2205 LinkedIn: https://www.linkedin.com/in/ibodullo Email: ioa22052005@gmail.com Full-stack AI engineer — production RAG systems, LLM integration, and full-stack apps/platforms built from scratch. Shipped an ERP voice AI agent across four production platforms, an AI-powered ATS (TezHR, live), and an EdTech platform (FastAPI/Supabase/Flutter&…

Show HN: Rowboat – Open-source, local-first alternative to Claude Desktop

Rowboat markets itself as "local-first," but if you look in the actual codebase, transcription is Deepgram cloud, voice is ElevenLabs, analytics is PostHog, and the LLM is a cloud API.

Show HN: Rowboat – Open-source, local-first alternative to Claude Desktop

Fair list: 1. True - no OS-level container today. The constraint is approval gating: consequential actions surface as a permission ask before they run (a separate supervisor LLM flags anything outside your intent). 2. True today. We'd deprioritized generic IMAP (drafts-on-thread is unreliable cross-provider), but you're the third person in this thread to raise it, so we'll scope it properly. 3/4/5. Today: Deepgram for STT, ElevenLabs for TTS, Exa for search. At least for search we supported more providers earlier (e.g. Brave) and found the assistant's skills degrade when they can't lean on provider-specific capabilities, like Exa's granular search. So we trimmed and went deep on a few. Feel free to raise a GitHub issue with what you want us to support and we'll do our best.

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

Location: New York, NY Remote: Yes Willing to relocate: Yes Technologies: Python, PHP, TypeScript, AI Agent, RAG, Prompt-Engineering, LangChain, LangGraph, React, Vue.js Résumé/CV: https://drive.google.com/file/d/1lycaftoYFy-Y-wmNJ70zUbliS3s... Email: kevintom9605@gmail.com Senior AI & Data Engineer with 8+ years of experience designing scalable data platforms, machine learning solutions, and Generative AI applications. Experienced in building enterprise data pipelines, cloud-native AI systems, Retrieval-Augmented Generation (RAG) platforms, agentic AI workflows, and production ML infrastructure on AWS. Strong background in Python, SQL, distributed data processing, vector databases, LLM orchestration, and MLOps. Passionate about delivering reliable AI solutio…

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

Location: Knoxville, TN 37932 Remote: Yes Willing to relocate: Yes Technologies: Python, TypeScript, React, Next.js, Node.js, FastAPI, Django, PostgreSQL, MongoDB, Redis, GCP, Azure, AWS, Docker, Kubernetes, OpenAI, Claude, Vertex AI, LangChain, RAG, MCP, CI/CD Resume: https://drive.google.com/file/d/1OpfHwNWTTY3FYWZpeatTP0IkNmr... Email: patrick35353@outlook.com

Local, CPU-Friendly, High-Quality TTS (Text-to-Speech) with Kokoro

Easy to send one’s clipboard to Microsoft Azure and have their DragonHD voices read the text, say with Keyboard Maestro (or presumably Alfred, Raycast, etc.). Should work with selected text too. You’d definitely get to pay for it, not what I consider cheap. (“$15 per 1M characters”) But IMO just about best-in-class (maybe ElevenLabs has a voice I’d like even better).

Local, CPU-Friendly, High-Quality TTS (Text-to-Speech) with Kokoro

Another endorsement - I used Kokoro pretty extensively with an app I was developing over the last year and it's been excellent, both on- and off- GPU. Even with Elevenlabs (long time subscriber) the comparative quality of Kokoro keeps up really well until you get to their larger models with their professional voices. I do wish there were better support for SSML, as well as deeper documentation of how to influence inflection in-line, but the default does well with standard emphasis (e.g. putting asterisks around text elements). Both asks are getting outside the zone of reasonable asks for this sort of distribution, though, and I remain incredibly grateful for the quality of what hexgrad and nazdridoy have put out in the world.

Show HN: Instant GraphRAG over any Postgres database

Hi HN, I’m Dale. I’m building Polygres with my twin brother and a longtime friend who is a decade older than us lol. Polygres is an all in one Postgres-based database that combines relational data, graph traversal, vector search, full-text search, and reranking over the same source-of-truth data. We built this because we kept seeing devs building RAG or agent systems having to sync the same data across several stores: Postgres for application data, Qdrant or Pinecone for vectors, Neo4j for graph traversal, and then a lot of glue code to keep everything consistent. That adds operational complexity, stale-index problems, and awkward retrieval logic. Polygres is our attempt to keep more of that inside Postgres. You can insert and update data with normal SQL, represent relationships as a grap…

Show HN: Instant GraphRAG over any Postgres database

Hi HN, I’m Dale. I’m building Polygres with my twin brother and a longtime friend who is a decade older than us lol. Polygres is an all in one Postgres-based database that combines relational data, graph traversal, vector search, full-text search, and reranking over the same source-of-truth data. We built this because we kept seeing devs building RAG or agent systems having to sync the same data across several stores: Postgres for application data, Qdrant or Pinecone for vectors, Neo4j for graph traversal, and then a lot of glue code to keep everything consistent. That adds operational complexity, stale-index problems, and awkward retrieval logic. Polygres is our attempt to keep more of that inside Postgres. You can insert and update data with normal SQL, represent relationships as a grap…

Show HN: Revector – Alembic-style schema migrations for Qdrant

Hey HN! I'm Diego. I've been extensively using Qdrant for hybrid search, but there's no standard way to track and manage schema migrations. I've used alembic in the past for relational databases, so I decided to develop something similar for Qdrant: revector. You write declarative YAML migrations, commit them next to your code, and apply or roll them back with a single static binary. Repo: https://github.com/diegoglozano/revector Docs: https://diegoglozano.github.io/revector/ Thanks for taking a look, happy to hear your feedback!

Ternlight – 7 MB embedding model that runs in browser (WASM)

so this is really cool and I think could be the missing piece for something I wanted to build, I found this awhile back and using https://github.com/npiesco/absurder-sql you could keep the entire raw corpus in browser (persisted via IndexedDB/SQLite)...then you could generate + cache embeddings on demand with Ternlight (instead of pre-indexing everything i.e., https://weaviate.io/blog/chunking-strategies-for-rag ). then this opens up the door for Reciprocal Rank Fusion (RRF) aka hybrid retrieval where you combine FTS5/BM25 from the native SQLite plues the semantic search using from TernLight!

Show HN: LangChain's OpenWiki agent based on PI.dev harness

What does Jeff Bezos think is going to happen?

Nothing is going to happen. Amazon is like a very large redwood tree that is all grown. It has no interest in fire, drought, animal life, human culture, or anything else you value. Your old Kindle is as one of its pinecones on a mantelpiece somewhere.

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

Location: Bhopal, India Remote: Yes, remote only Willing to relocate: No Technologies: Python, TypeScript, PyTorch, TensorFlow, Hugging Face, scikit-learn, RAG, LLM fine-tuning, LoRA, PEFT, LangChain, LangGraph, LlamaIndex, OpenAI API, Anthropic API, FAISS, Pinecone, Chroma, PostgreSQL, FastAPI, React, Docker, AWS, GCP, Azure Résumé/CV: https://adityasnehai.github.io/aditya-sneh-links/ Email: adityasneh09@gmail.com I’m Aditya Sneh, an AI/ML Engineer focused on applied ML, RAG systems, LLM applications, computer vision, and mobile-sensing AI. I have built production-style RAG systems, agentic AI tools, on-device ML systems, and real-world mental health/mobile sensing pipelines. I have also authored 5 AI/ML research papers. Looking for remote AI Engin…

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

Location: Bhopal, India Remote: Yes, remote only Willing to relocate: No Technologies: Python, TypeScript, PyTorch, TensorFlow, Hugging Face, scikit-learn, RAG, LLM fine-tuning, LoRA, PEFT, LangChain, LangGraph, LlamaIndex, OpenAI API, Anthropic API, FAISS, Pinecone, Chroma, PostgreSQL, FastAPI, React, Docker, AWS, GCP, Azure Résumé/CV: https://adityasnehai.github.io/aditya-sneh-links/ Email: adityasneh09@gmail.com I’m Aditya Sneh, an AI/ML Engineer focused on applied ML, RAG systems, LLM applications, computer vision, and mobile-sensing AI. I have built production-style RAG systems, agentic AI tools, on-device ML systems, and real-world mental health/mobile sensing pipelines. I have also authored 5 AI/ML research papers. Looking for remote AI Engin…

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

Location: Bhopal, India Remote: Yes, remote only Willing to relocate: No Technologies: Python, TypeScript, PyTorch, TensorFlow, Hugging Face, scikit-learn, RAG, LLM fine-tuning, LoRA, PEFT, LangChain, LangGraph, LlamaIndex, OpenAI API, Anthropic API, FAISS, Pinecone, Chroma, PostgreSQL, FastAPI, React, Docker, AWS, GCP, Azure Résumé/CV: https://adityasnehai.github.io/aditya-sneh-links/ Email: adityasneh09@gmail.com I’m Aditya Sneh, an AI/ML Engineer focused on applied ML, RAG systems, LLM applications, computer vision, and mobile-sensing AI. I have built production-style RAG systems, agentic AI tools, on-device ML systems, and real-world mental health/mobile sensing pipelines. I have also authored 5 AI/ML research papers. Looking for remote AI Engin…

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

Location: Washington, US Remote: Yes Willing to relocate: No Technologies: TypeScript, React, Next.js, Node.js, Python, FastAPI, Django, .NET/C#, PostgreSQL, Redis, Elasticsearch, GCP, AWS, Docker, Kubernetes, GraphQL, REST APIs, LangChain, RAG, AI agents, Vertex AI, Amazon Bedrock, Pinecone, Chroma, CI/CD, Prometheus, Grafana Résumé/CV: https://1drv.ms/b/c/72678D79CE44BE0F/IQB8hB_vXguzRJgoXbXd5se... Email: chadbooth93@outlook.com About me: I’m a Senior Software Engineer with strong full‑stack expertise in TypeScript, React, Next.js, Node.js, and Python, combined with hands‑on AI engineering experience building RAG pipelines, LLM features, and multi‑agent systems using OpenAI, Claude, Gemini, LangChain, Pinecone, and Vertex AI.

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

Location: Washington, US Remote: Yes Willing to relocate: No Technologies: TypeScript, React, Next.js, Node.js, Python, FastAPI, Django, .NET/C#, PostgreSQL, Redis, Elasticsearch, GCP, AWS, Docker, Kubernetes, GraphQL, REST APIs, LangChain, RAG, AI agents, Vertex AI, Amazon Bedrock, Pinecone, Chroma, CI/CD, Prometheus, Grafana Résumé/CV: https://1drv.ms/b/c/72678D79CE44BE0F/IQB8hB_vXguzRJgoXbXd5se... Email: chadbooth93@outlook.com About me: I’m a Senior Software Engineer with strong full‑stack expertise in TypeScript, React, Next.js, Node.js, and Python, combined with hands‑on AI engineering experience building RAG pipelines, LLM features, and multi‑agent systems using OpenAI, Claude, Gemini, LangChain, Pinecone, and Vertex AI.