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Show HN: Bunqueue – Job queue for Bun using SQLite instead of Redis

Show HN: Micropolis/SimCity Clone in Emacs Lisp

This is a little game implemented over a week of tinkering and targeting Emacs.<p>The point is both to have fun with this kind of simulations, and also explore the "functional core / imperative shell" approach to architecture. I also developed a tile and tile effect definition DSL, which makes this even easier to extend. From this point of view it's a success: easy testing, easy extension,<p>Gameplay-wise the simulation is too simplistic, and needs input from people interested in this kind of toys. The original Micropolis/SimSity is the last time I built a virtual city.

Show HN: Micropolis/SimCity Clone in Emacs Lisp

This is a little game implemented over a week of tinkering and targeting Emacs.<p>The point is both to have fun with this kind of simulations, and also explore the "functional core / imperative shell" approach to architecture. I also developed a tile and tile effect definition DSL, which makes this even easier to extend. From this point of view it's a success: easy testing, easy extension,<p>Gameplay-wise the simulation is too simplistic, and needs input from people interested in this kind of toys. The original Micropolis/SimSity is the last time I built a virtual city.

Show HN: Interactive California Budget (By Claude Code)

There's been a lot of discussion around the california budget and some proposed tax policies, so I asked claude code to research the budget and turn it into an interactive dashboard.<p>Using async subagents claude was able to research ~a dozen budget line items at once across multiple years, adding lots of helpful context and graphs to someone like me who was starting with little familiarity.<p>It still struggles with frontend changes, but for research this probably 20-40x's my throughput.<p>Let me know any additional data or visualizations that would be interesting to add!

Show HN: Interactive California Budget (By Claude Code)

There's been a lot of discussion around the california budget and some proposed tax policies, so I asked claude code to research the budget and turn it into an interactive dashboard.<p>Using async subagents claude was able to research ~a dozen budget line items at once across multiple years, adding lots of helpful context and graphs to someone like me who was starting with little familiarity.<p>It still struggles with frontend changes, but for research this probably 20-40x's my throughput.<p>Let me know any additional data or visualizations that would be interesting to add!

Show HN: I built "AI Wattpad" to eval LLMs on fiction

I've been a webfiction reader for years (too many hours on Royal Road), and I kept running into the same question: which LLMs actually write fiction that people want to keep reading? That's why I built Narrator (<a href="https://narrator.sh/llm-leaderboard" rel="nofollow">https://narrator.sh/llm-leaderboard</a>) – a platform where LLMs generate serialized fiction and get ranked by real reader engagement.<p>Turns out this is surprisingly hard to answer. Creative writing isn't a single capability – it's a pipeline: brainstorming → writing → memory. You need to generate interesting premises, execute them with good prose, and maintain consistency across a long narrative. Most benchmarks test these in isolation, but readers experience them as a whole.<p>The current evaluation landscape is fragmented: Memory benchmarks like FictionLive's tests use MCQs to check if models remember plot details across long contexts. Useful, but memory is necessary for good fiction, not sufficient. A model can ace recall and still write boring stories.<p>Author-side usage data from tools like Novelcrafter shows which models writers prefer as copilots. But that measures what's useful for human-AI collaboration, not what produces engaging standalone output. Authors and readers have different needs.<p>LLM-as-a-judge is the most common approach for prose quality, but it's notoriously unreliable for creative work. Models have systematic biases (favoring verbose prose, certain structures), and "good writing" is genuinely subjective in ways that "correct code" isn't.<p>What's missing is a reader-side quantitative benchmark – something that measures whether real humans actually enjoy reading what these models produce. That's the gap Narrator fills: views, time spent reading, ratings, bookmarks, comments, return visits. Think of it as an "AI Wattpad" where the models are the authors.<p>I shared an early DSPy-based version here 5 months ago (<a href="https://news.ycombinator.com/item?id=44903265">https://news.ycombinator.com/item?id=44903265</a>). The big lesson: one-shot generation doesn't work for long-form fiction. Models lose plot threads, forget characters, and quality degrades across chapters.<p>The rewrite: from one-shot to a persistent agent loop<p>The current version runs each model through a writing harness that maintains state across chapters. Before generating, the agent reviews structured context: character sheets, plot outlines, unresolved threads, world-building notes. After generating, it updates these artifacts for the next chapter. Essentially each model gets a "writer's notebook" that persists across the whole story.<p>This made a measurable difference – models that struggled with consistency in the one-shot version improved significantly with access to their own notes.<p>Granular filtering instead of a single score:<p>We classify stories upfront by language, genre, tags, and content rating. Instead of one "creative writing" leaderboard, we can drill into specifics: which model writes the best Spanish Comedy? Which handles LitRPG stories with Male Leads the best? Which does well with romance versus horror?<p>The answers aren't always what you'd expect from general benchmarks. Some models that rank mid-tier overall dominate specific niches.<p>A few features I'm proud of:<p>Story forking lets readers branch stories CYOA-style – if you don't like where the plot went, fork it and see how the same model handles the divergence. Creates natural A/B comparisons.<p>Visual LitRPG was a personal itch to scratch. Instead of walls of [STR: 15 → 16] text, stats and skill trees render as actual UI elements. Example: <a href="https://narrator.sh/novel/beware-the-starter-pet/chapter/1" rel="nofollow">https://narrator.sh/novel/beware-the-starter-pet/chapter/1</a><p>What I'm looking for:<p>More readers to build out the engagement data. Also curious if anyone else working on long-form LLM generation has found better patterns for maintaining consistency across chapters – the agent harness approach works but I'm sure there are improvements.

Show HN: C discrete event SIM w stackful coroutines runs 45x faster than SimPy

Hi all,<p>I have built <i>Cimba</i>, a multithreaded discrete event simulation library in C.<p>Cimba uses POSIX pthread multithreading for parallel execution of multiple simulation trials, while coroutines provide concurrency inside each simulated trial universe. The simulated processes are based on asymmetric stackful coroutines with the context switching hand-coded in assembly.<p>The stackful coroutines make it natural to express agentic behavior by conceptually placing oneself "inside" that process and describing what it does. A process can run in an infinite loop or just act as a one-shot customer passing through the system, yielding and resuming execution from any level of its call stack, acting both as an active agent and a passive object as needed. This is inspired by my own experience programming in Simula67, many moons ago, where I found the coroutines more important than the deservedly famous object-orientation.<p>Cimba turned out to run <i>really</i> fast. In a simple benchmark, 100 trials of an M/M/1 queue run for one million time units each, it ran <i>45 times faster</i> than an equivalent model built in SimPy + Python multiprocessing. The running time was <i>reduced by 97.8 %</i> vs the SimPy model. Cimba even processed more simulated events per second <i>on a single CPU core</i> than SimPy could do on all 64 cores.<p>The speed is not only due to the efficient coroutines. Other parts are also designed for speed, such as a hash-heap event queue (binary heap plus Fibonacci hash map), fast random number generators and distributions, memory pools for frequently used object types, and so on.<p>The initial implementation supports the AMD64/x86-64 architecture for Linux and Windows. I plan to target Apple Silicon next, then probably ARM.<p>I believe this may interest the HN community. I would appreciate your views on both the API and the code. Any thoughts on future target architectures to consider?<p>Docs: <a href="https://cimba.readthedocs.io/en/latest/" rel="nofollow">https://cimba.readthedocs.io/en/latest/</a><p>Repo: <a href="https://github.com/ambonvik/cimba" rel="nofollow">https://github.com/ambonvik/cimba</a>

Show HN: EpsteIn – Search the Epstein files for your LinkedIn connections

Show HN: EpsteIn – Search the Epstein files for your LinkedIn connections

Show HN: GitHub Browser Plugin for AI Contribution Blame in Pull Requests

Show HN: GitHub Browser Plugin for AI Contribution Blame in Pull Requests

Show HN: Ghidra MCP Server – 110 tools for AI-assisted reverse engineering

Show HN: Ghidra MCP Server – 110 tools for AI-assisted reverse engineering

Show HN: Ghidra MCP Server – 110 tools for AI-assisted reverse engineering

Show HN: Craftplan – I built my wife a production management tool for her bakery

My wife was planning to open a micro-bakery. We looked at production management software and it was all either expensive or way too generic. The actual workflows for a small-batch manufacturer aren't that complex, so I built one and open-sourced it.<p>Craftplan handles recipes (versioned BOMs with cost rollups), inventory (lot traceability, demand forecasting, allergen tracking), orders, production batch planning, and purchasing. Built with Elixir, Ash Framework, Phoenix LiveView, and PostgreSQL.<p>Live demo: <a href="https://craftplan.fly.dev" rel="nofollow">https://craftplan.fly.dev</a> (test@test.com / Aa123123123123)<p>GitHub: <a href="https://github.com/puemos/craftplan" rel="nofollow">https://github.com/puemos/craftplan</a>

Show HN: Craftplan – I built my wife a production management tool for her bakery

My wife was planning to open a micro-bakery. We looked at production management software and it was all either expensive or way too generic. The actual workflows for a small-batch manufacturer aren't that complex, so I built one and open-sourced it.<p>Craftplan handles recipes (versioned BOMs with cost rollups), inventory (lot traceability, demand forecasting, allergen tracking), orders, production batch planning, and purchasing. Built with Elixir, Ash Framework, Phoenix LiveView, and PostgreSQL.<p>Live demo: <a href="https://craftplan.fly.dev" rel="nofollow">https://craftplan.fly.dev</a> (test@test.com / Aa123123123123)<p>GitHub: <a href="https://github.com/puemos/craftplan" rel="nofollow">https://github.com/puemos/craftplan</a>

Show HN: Craftplan – I built my wife a production management tool for her bakery

My wife was planning to open a micro-bakery. We looked at production management software and it was all either expensive or way too generic. The actual workflows for a small-batch manufacturer aren't that complex, so I built one and open-sourced it.<p>Craftplan handles recipes (versioned BOMs with cost rollups), inventory (lot traceability, demand forecasting, allergen tracking), orders, production batch planning, and purchasing. Built with Elixir, Ash Framework, Phoenix LiveView, and PostgreSQL.<p>Live demo: <a href="https://craftplan.fly.dev" rel="nofollow">https://craftplan.fly.dev</a> (test@test.com / Aa123123123123)<p>GitHub: <a href="https://github.com/puemos/craftplan" rel="nofollow">https://github.com/puemos/craftplan</a>

Show HN: Octosphere, a tool to decentralise scientific publishing

Hey HN! I went to an ATProto meetup last week, and as a burnt-out semi-academic who hates academic publishing, I thought there might be a cool opportunity to build on Octopus (<a href="https://www.octopus.ac/" rel="nofollow">https://www.octopus.ac/</a>), so I got a bit excited over the weekend and built Octosphere.<p>Hopefully some of you find it interesting! Blog post here: <a href="https://andreasthinks.me/posts/octosphere/octosphere.html" rel="nofollow">https://andreasthinks.me/posts/octosphere/octosphere.html</a>

Show HN: Octosphere, a tool to decentralise scientific publishing

Hey HN! I went to an ATProto meetup last week, and as a burnt-out semi-academic who hates academic publishing, I thought there might be a cool opportunity to build on Octopus (<a href="https://www.octopus.ac/" rel="nofollow">https://www.octopus.ac/</a>), so I got a bit excited over the weekend and built Octosphere.<p>Hopefully some of you find it interesting! Blog post here: <a href="https://andreasthinks.me/posts/octosphere/octosphere.html" rel="nofollow">https://andreasthinks.me/posts/octosphere/octosphere.html</a>

Show HN: difi – A Git diff TUI with Neovim integration (written in Go)