GPT-5
Show HN: Prompt-run – run .prompt files against any LLM from the terminal
I built this because prompts kept ending up in the worst possible places — Python strings, Notion docs, `.txt` files, Slack threads. There was no clean way to version them, diff them, or test the same prompt across different models without writing a throwaway script.prompt-run treats `.prompt` files as first-class runnable artifacts. A `.prompt` file is a YAML header (model, provider, temperature, variable declarations) followed by a plain text body with `{{variable}}` substitution. You run it f
Show HN: MemoryKit – Persistent memory layer for AI agents
Most AI agents forget everything when a session ends. MemoryKit is a lightweight Python library that gives any AI agent persistent memory across sessions.
Three core methods: remember(), recall(), compress(). Works locally for free with sentence-transformers, or with OpenAI embeddings. No external database required.
Built this over a weekend as a side project. Still early — would love feedback from people building AI agents.
Show HN: Voice-coded a Doom-scroll Hacker News (Twitter-style feed)
Built a mobile-friendly Hacker News clone where stories and comments flow in an infinite, Doom-scrollable timeline (think Twitter/X feed meets HN).Voice-coded the entire website from scratch using my yapboard voice keyboard + OpenAI Codex via a Discord bridge bot. Screen-mirrored with scrcpy for real-time testing. Forgot to turn on mic during the live build, so added narration afterward.Demo (try on mobile): https://hackernews.lukestephens.co.za
Full build video (voice coding tim
ClawShopping-Marketplace for AI Agents
ClawShopping is a Stripe-powered marketplace where OpenClaw agents buy, sell, and build trust with transparent reputation signals. Humans welcome to observe.
Join ClawShopping
Read https://clawshopping.com/skill.md and follow the instructions to join #ClawShopping
Show HN: IssueScout – Find open source issues worth contributing to
I built IssueScout to solve a problem I had as a beginner looking to contribute to open source: GitHub has hundreds of thousands of "good first issue" labeled issues, but there's no way to know if the repo behind one is actively maintained or if the issue is actually beginner-friendly.IssueScout adds two things on top of GitHub's search:1. A Community Health Score (0-100) per repository — computed from 7 factors: CONTRIBUTING.md, license, code of conduct, recent activity, sta
Ask HN: Whats the best friction approach to breaking phone habits
been thinking about friction design patterns vs pure blocking for phone habits. blocking feels punitive - you hit a wall every time. friction is different - you add a 5-60 second delay before opening the app, but you still decide to open it. the pause breaks the automatic reach and forces intention.<p>any hn folks tried approaches like this? does friction actually change behavior better than removal/blocking? curious what patterns work best in practice.
OpenAI's new GPT-5.3-Codex is 25% faster and goes way beyond coding now - what's new
GPT-5.3-Codex helped debug and deploy parts of itself. Codex can be steered mid-task without losing context. "Underspecified" prompts now produce richer, more usable results. OpenAI today announced ...
Show HN: Coding agents find the right GPU bottleneck 70% of the time, fix it 30%
One of the authors. Some things that surprised us while running these experiments:The tasks are pulled from real merged PRs in vLLM and SGLang, so there's a known-good human solution for each one. Agents get the full codebase, the issue description, and a test harness. Pretty generous setup.What we didn't expect: the agents are genuinely good at diagnosing the problem. They read the code, find the bottleneck, describe the right fix. But then the generated code has subtle bugs. Off-by-o
Show HN: The best agent orchestrator is a 500-line Markdown file
I’ve tried agent teams, subagents, multi-terminal setups, and several open-source orchestration frameworks. This Claude Code skill (~500 lines of Markdown, no framework, no dependencies) has outperformed all of them for my team’s daily workflow.It turns your session into a dispatcher that fans work out to background workers across any model (Claude, GPT, Gemini, Codex). Workers ask clarifying questions mid-task via filesystem IPC instead of silently failing. Meanwhile, your main session stays le
Show HN: OnGarde – Runtime content security proxy for self-hosted AI agents
Built this because I had heard some horror stories about companies leaking PII from high compliance environments to ChatGPT. I wanted something that would auto-filter any dangerous traffic between my AI agent and the LLM API without requiring code changes in the agent itself.The filtering list has expanded a bit to include PII, secret keys and I've started a prompt injection library thats being filtered on as well.The problem: self-hosted agent platforms (OpenClaw, Agent Zero, CrewAI) have
Show HN: StageWright – A performance-focused Playwright reporter with AI
Hi HN,I’m the creator of StageWright (and the open-source playwright-smart-reporter).I’ve been frustrated by the "black box" nature of E2E test failures. Standard reporters tell you that a test failed, but they don't help you understand why it’s failing across 50 different runs or whether its execution time is trending toward a regression.I built StageWright to treat test results as a performance and stability dataset.Key Technical Features:Historical Flakiness Detection: Unlike P
Show HN: How AI Content Automation Is Reshaping SaaS Marketing in 2025
Show HN: How AI Content Automation is Reshaping SaaS Marketing in 2025I've spent 5 years building SaaS and tracking how AI revolutionizes marketing. Here's what the data shows:KEY FINDINGS:- AI-integrated SaaS products grew 40% YoY (GitNux, 2026)
- Companies using AI publish 3.2x more content than human-only teams
- Cost per article dropped from $157 to $12-18 (AI-assisted)
- Top-quartile SaaS allocate 65% of marketing budget to automation (up from 23% in 2022)WHERE AI WORKS BEST:High-
ChatGPT's Writing Style
We can all detect that particular style. I've just thought about what may define it.It writes in such a way that the human reading it assigns meaning to it. We're accustomed to reading the words of others and being generous with our interpretation. I think GPT takes advantage of this. What it says can be interpreted as correct and incisive, but if one were to be very strict and uncharitable then what it says can usually be interpreted as meaningless and vague.Considering it was trained
Show HN: Caddy plugin that charges AI crawlers real USDC to access your site
Hello,
I built a Caddy middleware that implements the x402 protocol (by Coinbase) to charge AI crawlers real money for content access.When GPTBot, ClaudeBot, or any known AI crawler hits your site, it gets an HTTP 402 with payment
requirements. If it pays (USDC on Base), it gets the content. If not, it gets nothing.Normal users are never affected.How it works:
- Crawler detected by User-Agent → 402 response with price and wallet address- Crawler signs a USDC payment (EIP-3009) and retries wi
Show HN: Handoff-md – One command to generate portable AI context from any repo
Every time you switch AI models mid-project, the new model starts from zero. It doesn't know your stack, your conventions, or what you were working on five minutes ago.I built handoff-md to fix this. It's a CLI tool that analyzes your git repo and generates a single HANDOFF.md file. Paste it into any AI model and it instantly understands your project.What it does:- Parses git history (last 20 commits, branches, uncommitted changes)
- Detects your stack (framework, ORM, DB, auth, deploy
Show HN: Market Digest: Self-hosted market analysis and Telegram
Hi HN, I built this because my pre-market routine was eating 45+ minutes every morning — checking TradingView, Finviz, economic calendars, news sites, fear/greed indexes, all before market open.*What it does:* Market Digest pulls data from 6 free sources (yfinance, TwelveData, Finnhub, FRED, NewsAPI, Fear & Greed), runs multi-timeframe technical analysis (daily/weekly/monthly RSI, pivot points, trend detection), scores every instrument from 0-100, and sends you a formatted dig
Show HN: GameScout AI – AI-powered game recommender
I built GameScout AI because I never really liked the recommendations sites like Steam propose. It uses natural language to find games based on specific mechanics or moods, like "cozy farming sims with a bit of action" or "something like Dark Souls but funnier".The Stack:- Next.js & Tailwind: For a responsive, gaming-focused UI.- Groq (Llama 3): I’m using Groq for inference because sub-second latency makes semantic search feel like a local DB query.- Prompt Engineering: O
Ask HN: Why do AI coding agents refuse to save their own observations?
I've spent months building tooling for AI coding agents and hit something I can't fully explain.If you give an agent (Claude Code, Cursor, Codex) a tool to save observations — "save_observation: persist this insight for future sessions" — and explicitly instruct it to use the tool in system prompts, config files, everywhere you can, it calls it maybe 30% of the time.The agent will happily use tools that help it complete the current task. But a tool that only benefits future s
Show HN: Simple Viewers – Tiny native macOS file viewers
Hi HN,Around summer/fall of 2025, I started using 'plan mode' quite a bit more. When I would cmd+click into a newly created markdown plan, macOS would open Xcode. This was slow, didn't have native rendered viewing, the list goes on. I started working on a markdown viewer to easily open, review plans before I sent Claude on their way. The Markdown Viewer was born! It came from inspiration from the great Preview Mac app.For Christmas our family got a Bambu A1 3D printer (fantas
Show HN: Phone a Friend for Claude Code – GPT, Gemini, DeepSeek via MCP
I built an MCP server that gives Claude Code a "phone a friend" lifeline. Instead of relying on one model's perspective, Claude can pull in GPT, Gemini, DeepSeek, or any OpenAI-compatible model for a structured multi-round debate — and participate as an active debater itself.How it works:You ask Claude to brainstorm a topic
All configured models respond in parallel (Round 1)
Claude reads their responses and pushes back with its own take
Models see each other's responses and r
