
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

Compress LLM prompts and documents to reduce token usage and API costs.
@marcusyul · X
THEY JUST GAVE AWAY 100 MILLION FREE TOKENS SO YOU CAN STOP BURNING THROUGH YOUR CLAUDE CODE BUDGET. if you code with AI you already know: the session fills up, starts failing, and on top of that you're overpaying there's a tool that fixes this: it shrinks the context before the model even sees it same model, same response, a fraction of the cost in a real session: from $154 to $43. a 72% drop and right now: → extend your Fable sessions in Claude Code → 100M free tokens to try it out you don't switch models you don't touch your code you just stop paying to repeat yourself link below ⬇️

Compress prompts before LLM API calls to reduce token usage and costs.
@asgujjuasitgets · X

Interactive LLM chat interface running on Enclave's confidential compute platform.
SteveDeFacto · HN
Hi HN, I built Enclave, self-serve confidential compute on GPUs. Technical documentation is on the site, but I'd rather show than tell. Here are a couple apps hosted live on the platform: LLM Chat bot: https://cc1f4f3f.app.enclave.host AI Image Generation: https://da09d0f2.app.enclave.host If you have any questions, I would be more than happy to discuss.

Send your question to a panel of LLMs that peer-review each other and return one synthesized answer.
u/Puzzleheaded-Log-27 · Reddit
Building a multi-model AI deliberation tool taught me something about trust LLM Counsel isn't another wrapper around one model - it sends your question to a panel of frontier LLMs, has them peer-review each other anonymously, and an impartial "chairman" model returns one synthesized answer. Free to start, pay-as-you-go after, credits don't expire. What I've learned so far: people trust a synthesized answer a lot more once they can see that the models actually disagreed and how that disagree

Inspect RAG chunks and visualize AI agent workflows, memory architecture, and execution traces.
@Higgs0110 · X

Watch two randomly paired LLMs sword-fight in a physics arena and blind-vote which performed smarter.
u/Time-Shelter-35 · Reddit
I built a site where two LLMs sword-fight in real physics and you blind-vote who's smarter Two months ago I thought: what if the AI benchmark was just… watching them fight. So: https://stickblade-arena.vercel.app Two random LLMs get stickman bodies in a pymunk physics arena They each turn output JSON moves (swing, block, dash, shoot bow, throw flail…) Ragdolls, momentum, weapon collisions, the whole bit You watch the replay without knowing which model is which and vote who f

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

Capture and store project context to pause and resume work anytime.
@naumanthanvi · X

Analytics dashboard for LLM API spending by model and environment with optimization suggestions.
ATsimbalistov · HN
Show HN: Tracking GenAI cost and endpoint fragility so app teams don't have to

Monitor AI model calls, agent steps, and retrieval with token tracking, cost analysis, and latency metrics.
ephraimduncan · HN
Observability for Coding Agents and LLM Applications

Collaborate on AI projects using a spatial node canvas to organize LLM context.
jebuehler55 · HN
I built a spatial node canvas to fix LLM context drift