
DWS REPORT — 2026-07-19 18:53 UTC
Real-time LLM-powered news aggregator surfacing trending stories with live updates.
tdubey · HN
DWS A LLM Generated, "Drudge Report" style news site
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Real-time LLM-powered news aggregator surfacing trending stories with live updates.
tdubey · HN
DWS A LLM Generated, "Drudge Report" style news site

AI course generator that assesses your knowledge and builds personalized learning paths.
u/graywolf724 · Reddit
167 users, 202 courses, 1,840 chapters. $0 in revenue, and that's on purpose. https://reddit.com/link/1v94i9o/video/epyh6f5t40gh1/player Built an AI course generator that asks you ~5 adaptive questions to figure out what you actually already know, then builds a course around the gap instead of a generic curriculum. No account needed to try it, and it's still completely free (for now). The numbers so far: 167 people have generated at least one course, 202 courses total, about 1,840 ch

Test small language models (8M-13M parameters) in your browser that work offline.
u/Live_Confusion_3003 · Reddit
I trained an LLM that runs on an ESP32 and directly in the browser Link to try it out yourself is: topk.sh The models download their weights directly in the browser so it works offline. Keep in mind they are very small and inaccurate. (8M and 13M parameters) However, I am building 500M and 1B+ parameter local models for agent based coding and other purposes. I will be shipping hardware designed for these tasks which connect directly to you computer or other device.

Compare how different AI models generate frontend code and view accessibility scores.
u/12qwww · Reddit
I built a live benchmark to see which AI actually writes the best frontend code Hey everyone! I built OpenVibeEval because I was tired of "vibe-checking" AI-generated frontend code. I wanted to know which model actually produces the most accessible and clean React/Tailwind output. What I built: •A leaderboard of 24 models (Claude, GPT, DeepSeek, etc.) ranked by axe-core accessibility scores. •A Harness Comparator to show how different system prompts change the same model's output. •

An LLM gateway for OpenAI, Anthropic, Google and Azure. Every request logged, priced to the token, and audited for waste you can actually recover.
@razdagan3 · X

Visual editor for configuring multi-agent LLM systems with local inference.
sascha10000 · HN
Multi-agent LLM editor with local inference via WebSockets

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]

Route LLM API traffic through a gateway with built-in cost tracking, latency analytics, and PII redaction.
charltonraven · HN
RavenGate – LLM gateway that redacts PII across SSE chunk boundaries

Compare latency and throughput performance across LLM API providers.
@QAInsights · X

Generate MCP endpoints and llms.txt files from any website for AI agents.
AshHackerNews · HN
AgentReady – MCP server that makes any docs site queryable by AI agents

Access thousands of AI models through a single OpenAI-compatible API.
@mageofweb3 · X

Compress prompts and reduce LLM token costs by detecting duplicate tool calls.
@DeveloperL92487 · X
I built my first app in 60min And now I got $500 MRR in one month Check here if you are interested It’s a tool to reduce agent token consumption, speed up agent response, and clean up memory cache