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Show HN: TRiP – a complete transformer engine in C built from scratch just by me

Show HN: I wrote a DOOM clone in my own programming language

Show HN: My retired dad and I made a daily, somewhat difficult, quiz

My dad makes the questions, I made the site.<p>I think the genre and the level of difficulty is suited for HN. Hope you enjoy.<p>(I promise no AI-generated questions, they are all hand made!).

Show HN: Pu.sh – a full coding-agent harness in 400 lines of shell

I originally was just messing with pi-autoresearch. Gave it a sample task to build the most portable coding agent.<p>First cut was 6 KB of shell. Great for one-shots, unusable interactively. I was shocked it actually worked.<p>Started building up -- adding features — but with a self-imposed rule: no new dependencies, and sub 500 LOC. This thing had to be truly portable. Just sh, curl, awk. System primitives only.<p>Which means I did some genuinely disgusting things in awk, including JSON parsing and the OpenAI Responses tool loop with reasoning items carried across turns.<p>It's now ~400 lines. In the box: Anthropic + OpenAI, 7 tools (bash, read, write, edit, grep, find, ls), REPL, auto-compaction, checkpoint/resume, pipe mode, 90 no-API tests. Not in the box: TUI, streaming, images, OAuth, Windows, dignity.<p>Two honest things:<p>1. I stole/modified the system prompt and the architecture. Pi/Claude/Codex wrote the awk. I cannot read most of this code. This wasn't possible for me a year ago.<p>2. Heavily inspired by Pi (pi.dev) — same 7-tool surface, same exact-text edit model. Credit where it's due. Pi is awesome -- you should probably use them.<p>The agent loop itself is tiny. Almost everything else in a "real" agent CLI is DX and hardening. You can probably build your own harness exactly how you like it. Mario Zechner's AI Engineer talk on taking back control of your tools nudged me here.<p>The name is because it's a .sh file. The other thing it sounds like is, regrettably, also accurate.

Show HN: A new benchmark for testing LLMs for deterministic outputs

When building workflows that rely on LLMs, we commonly use structured output for programmatic use cases like converting an invoice into rows or meeting transcripts into tickets or even complex PDFs into database entries.<p>The model may return the schema you want, but with hallucinated values like `invoice_date` being off by 2 months or the transcript array ordered wrongly. The JSON is valid, but the values are not.<p>Structured output today is a big part of using LLMs, especially when building deterministic workflows.<p>Current structured output benchmarks (e.g., JSONSchemaBench) only validate the pass rate for JSON schema and types, and not the actual values within the produced JSON.<p>So we designed the Structured Output Benchmark (SOB) that fixes this by measuring both the JSON schema pass rate, types, and the value accuracy across all three modalities, text, image, and audio.<p>For our test set, every record is paired with a JSON Schema and a ground-truth answer that was verified against the source context manually by a human and an LLM cross-check, so a missing or hallucinated value will be considered to be wrong.<p>Open source is doing pretty well with GLM 4.7 coming in number 2 right after GPT 5.4.<p>We noticed the rankings shift across modalities: GLM-4.7 leads text, Gemma-4-31B leads images, Gemini-2.5-Flash leads audio.<p>For example, GPT-5.4 ranks 3rd on text but 9th on images.<p>Model size is not a predictor, either: Qwen3.5-35B and GLM-4.7 beat GPT-5 and Claude-Sonnet-4.6 on Value Accuracy. Phi-4 (14B) beats GPT-5 and GPT-5-mini on text.<p>Structured hallucinations are the hardest bug. Such values are type-correct, schema-valid, and plausible, so they slip through most guardrails. For example, in one audio record, the ground truth is "target_market_age": "15 to 35 years", and a model returns "25 to 35". This is invisible without field-level checks.<p>Our goal is to be the best general model for deterministic tasks, and a key aspect of determinism is a controllable and consistent output structure. The first step to making structured output better is to measure it and hold ourselves against the best.

Show HN: A new benchmark for testing LLMs for deterministic outputs

When building workflows that rely on LLMs, we commonly use structured output for programmatic use cases like converting an invoice into rows or meeting transcripts into tickets or even complex PDFs into database entries.<p>The model may return the schema you want, but with hallucinated values like `invoice_date` being off by 2 months or the transcript array ordered wrongly. The JSON is valid, but the values are not.<p>Structured output today is a big part of using LLMs, especially when building deterministic workflows.<p>Current structured output benchmarks (e.g., JSONSchemaBench) only validate the pass rate for JSON schema and types, and not the actual values within the produced JSON.<p>So we designed the Structured Output Benchmark (SOB) that fixes this by measuring both the JSON schema pass rate, types, and the value accuracy across all three modalities, text, image, and audio.<p>For our test set, every record is paired with a JSON Schema and a ground-truth answer that was verified against the source context manually by a human and an LLM cross-check, so a missing or hallucinated value will be considered to be wrong.<p>Open source is doing pretty well with GLM 4.7 coming in number 2 right after GPT 5.4.<p>We noticed the rankings shift across modalities: GLM-4.7 leads text, Gemma-4-31B leads images, Gemini-2.5-Flash leads audio.<p>For example, GPT-5.4 ranks 3rd on text but 9th on images.<p>Model size is not a predictor, either: Qwen3.5-35B and GLM-4.7 beat GPT-5 and Claude-Sonnet-4.6 on Value Accuracy. Phi-4 (14B) beats GPT-5 and GPT-5-mini on text.<p>Structured hallucinations are the hardest bug. Such values are type-correct, schema-valid, and plausible, so they slip through most guardrails. For example, in one audio record, the ground truth is "target_market_age": "15 to 35 years", and a model returns "25 to 35". This is invisible without field-level checks.<p>Our goal is to be the best general model for deterministic tasks, and a key aspect of determinism is a controllable and consistent output structure. The first step to making structured output better is to measure it and hold ourselves against the best.

Show HN: Adblock-rust Manager – Firefox extension to enable the Brave ad blocker

Firefox 149 ships adblock-rust (Brave's Rust engine, MPL-2.0) completely disabled with no UI. It's controlled by two about:config prefs with no WebExtension API, so you can't touch them programmatically from a standard extension.<p>This extension gives it a UI: ETP toggle (via browser.privacy API, instant), filter list manager with clipboard helpers for the manual about:config steps, and 8 preset lists. You can also add your own if you so desire.

Show HN: Adblock-rust Manager – Firefox extension to enable the Brave ad blocker

Firefox 149 ships adblock-rust (Brave's Rust engine, MPL-2.0) completely disabled with no UI. It's controlled by two about:config prefs with no WebExtension API, so you can't touch them programmatically from a standard extension.<p>This extension gives it a UI: ETP toggle (via browser.privacy API, instant), filter list manager with clipboard helpers for the manual about:config steps, and 8 preset lists. You can also add your own if you so desire.

Show HN: Rocky – Rust SQL engine with branches, replay, column lineage

Hi HN, I'm Hugo. I've been building Rocky over the past month, shipping fast in the open. The binary is on GitHub Releases, `dagster-rocky` on PyPI, and the VS Code extension on the Marketplace. I held off on a broader announcement until the trust-system surface was coherent enough to talk about as one thing. The governance waveplan — column classification, per-env masking, 8-field audit trail on every run, `rocky compliance` rollup, role-graph reconciliation, retention policies — landed end-to-end last week in engine-v1.16.0 and rounded out in v1.17.4 (tagged 2026-04-26). That's the milestone I'd been waiting for.<p>The pitch: keep Databricks or Snowflake. Bring Rocky for the DAG. Rocky is a Rust-based control plane for warehouse pipelines. Storage and compute stay with your warehouse. Rocky owns the graph — dependencies, compile-time types, drift, incremental logic, cost, lineage, governance. The things your current stack can't give you because it doesn't own the DAG.<p>A few things I think are interesting:<p>- Branches + replay. `rocky branch create stg` gives you a logical copy of a pipeline's tables (schema-prefix today; native Delta SHALLOW CLONE and Snowflake zero-copy are next). `rocky replay <run_id>` reconstructs which SQL ran against which inputs. Git-grade workflow on a warehouse.<p>- Column-level lineage from the compiler, not a post-hoc graph crawl. The type checker traces columns through joins, CTEs, and windows. VS Code surfaces it inline via LSP.<p>- Governance as a first-class surface. Column classification tags plus per-env masking policies, applied to the warehouse via Unity Catalog (Databricks) or masking policies (Snowflake). 8-field audit trail on every run. `rocky compliance` rollup that CI can gate on. Role-graph reconciliation via SCIM + per-catalog GRANT. Retention policies with a warehouse-side drift probe.<p>- Cost attribution. Every run produces per-model cost (bytes, duration). `[budget]` blocks in `rocky.toml`; breaches fire a `budget_breach` hook event.<p>- Compile-time portability + blast radius. Dialect-divergence lint across Databricks / Snowflake / BigQuery / DuckDB (12 constructs). `SELECT *` downstream-impact lint.<p>- Schema-grounded AI. Generated SQL goes through the compiler — AI suggestions type-check before they can land.<p>What Rocky isn't:<p>- Not a warehouse — it's the control plane on top.<p>- Not a Fivetran replacement. `rocky load` handles files (CSV/Parquet/JSONL); for SaaS sources use Fivetran, Airbyte, or warehouse-native CDC.<p>- Not dbt Cloud — no hosted UI, no managed scheduler. First-class Dagster integration if you need orchestration.<p>Adapters: Databricks (GA), Snowflake (Beta), BigQuery (Beta), DuckDB (local dev / playground). Apache 2.0.<p>I'd love feedback on the trust-system framing, the governance surface (particularly classification-to-masking resolution in `rocky compile` and the `rocky compliance` CI gate), the branches/replay design, the cost-attribution primitives, or anything else that catches your eye. Happy to go deep in the thread.

Show HN: Rocky – Rust SQL engine with branches, replay, column lineage

Hi HN, I'm Hugo. I've been building Rocky over the past month, shipping fast in the open. The binary is on GitHub Releases, `dagster-rocky` on PyPI, and the VS Code extension on the Marketplace. I held off on a broader announcement until the trust-system surface was coherent enough to talk about as one thing. The governance waveplan — column classification, per-env masking, 8-field audit trail on every run, `rocky compliance` rollup, role-graph reconciliation, retention policies — landed end-to-end last week in engine-v1.16.0 and rounded out in v1.17.4 (tagged 2026-04-26). That's the milestone I'd been waiting for.<p>The pitch: keep Databricks or Snowflake. Bring Rocky for the DAG. Rocky is a Rust-based control plane for warehouse pipelines. Storage and compute stay with your warehouse. Rocky owns the graph — dependencies, compile-time types, drift, incremental logic, cost, lineage, governance. The things your current stack can't give you because it doesn't own the DAG.<p>A few things I think are interesting:<p>- Branches + replay. `rocky branch create stg` gives you a logical copy of a pipeline's tables (schema-prefix today; native Delta SHALLOW CLONE and Snowflake zero-copy are next). `rocky replay <run_id>` reconstructs which SQL ran against which inputs. Git-grade workflow on a warehouse.<p>- Column-level lineage from the compiler, not a post-hoc graph crawl. The type checker traces columns through joins, CTEs, and windows. VS Code surfaces it inline via LSP.<p>- Governance as a first-class surface. Column classification tags plus per-env masking policies, applied to the warehouse via Unity Catalog (Databricks) or masking policies (Snowflake). 8-field audit trail on every run. `rocky compliance` rollup that CI can gate on. Role-graph reconciliation via SCIM + per-catalog GRANT. Retention policies with a warehouse-side drift probe.<p>- Cost attribution. Every run produces per-model cost (bytes, duration). `[budget]` blocks in `rocky.toml`; breaches fire a `budget_breach` hook event.<p>- Compile-time portability + blast radius. Dialect-divergence lint across Databricks / Snowflake / BigQuery / DuckDB (12 constructs). `SELECT *` downstream-impact lint.<p>- Schema-grounded AI. Generated SQL goes through the compiler — AI suggestions type-check before they can land.<p>What Rocky isn't:<p>- Not a warehouse — it's the control plane on top.<p>- Not a Fivetran replacement. `rocky load` handles files (CSV/Parquet/JSONL); for SaaS sources use Fivetran, Airbyte, or warehouse-native CDC.<p>- Not dbt Cloud — no hosted UI, no managed scheduler. First-class Dagster integration if you need orchestration.<p>Adapters: Databricks (GA), Snowflake (Beta), BigQuery (Beta), DuckDB (local dev / playground). Apache 2.0.<p>I'd love feedback on the trust-system framing, the governance surface (particularly classification-to-masking resolution in `rocky compile` and the `rocky compliance` CI gate), the branches/replay design, the cost-attribution primitives, or anything else that catches your eye. Happy to go deep in the thread.

Show HN: Rip.so – a graveyard for dead internet things

Show HN: Rip.so – a graveyard for dead internet things

Show HN: Auto-Architecture: Karpathy's Loop, pointed at a CPU

Show HN: AgentSwift – Open-source iOS builder agent

I'm working on a coding agent for building iOS apps. It's built on openspec and xcodebuildmcp. It's free and open source.

Show HN: Drive any macOS app in the background without stealing the cursor

Hi HN, Francesco from Cua here. I hacked this project together last weekend, inspired by the Codex Computer-Use release and lessons learned from deploying GUI-operating agents for our customers.<p>The main problem: when a UI automation process controls a desktop app today, it usually takes over the human’s session. Your cursor moves, keyboard focus gets stolen, windows jump to the front, and you have to stop working until the agent is done. That is why we have historically avoided encouraging users to run these processes directly on their host machine, instead relying on VMs or GUI containers for concurrency and background execution.<p>But computer-use - the tools we give agents to operate computers like humans - does not scale cleanly that way. As models get smarter, agents need to share hosts safely, run in the background, and avoid collisions with the human or other agents using the same machine.<p>We realized macOS has no first-class API for "drive this app without touching the cursor". CGEventPost routes through the hardware input stream, so it moves your cursor. CGEvent.postToPid avoids the cursor warp, but Chromium treats those events as untrusted and silently drops clicks at the renderer boundary. Activating the target app first raises the window and pulls focus, defeating the point of background execution.<p>Cua Driver is our attempt at a real fix: a background computer-use driver for macOS that lets an agent click, type, scroll, and read native apps while your cursor, frontmost app, and Space stay where they are. The default interface is a CLI, so it is easy to script or call from any coding agent shell.<p>Try it on macOS 14+:<p>/bin/bash -c "$(curl -fsSL <a href="https://raw.githubusercontent.com/trycua/cua/main/libs/cua-driver/scripts/install.sh" rel="nofollow">https://raw.githubusercontent.com/trycua/cua/main/libs/cua-d...</a>)"<p>The first internal use case was delegated demo recording. We ask Claude Code to drive an app while 'cua-driver recording start' captures the trajectory, screenshots, actions, and click markers. The result is an agent-generated product demo, Screen Studio inspired.<p>Other things we have used it for:<p>- Replacing Vercel’s agent-browser and other browser-use CLIs. With Claude Code and Cua Driver, you do not need Chrome DevTools Protocol at all.<p>- A dev-loop QA agent that reproduces a visual bug, edits code, rebuilds, and verifies the UI while my editor stays frontmost.<p>- Personal-assistant flows that use iMessage from Claude Code, Hermes, or other general-purpose agent CLIs.<p>- Pulling visual context from Chrome, Figma, Preview, or YouTube windows I am not looking at, without relying on their APIs.<p>What made this harder than expected:<p>- CGEventPost warps the cursor because it goes through the HID stream.<p>- CGEvent.postToPid does not warp the cursor, but Chromium drops it at the renderer IPC boundary.<p>- Activating the target first raises the window and can drag you across Spaces.<p>- Electron apps stop keeping useful AX trees alive when windows are occluded without a private remote-aware SPI.<p>The unlock was SkyLight. SLEventPostToPid is a sibling of the public per-PID call, but it travels through a WindowServer channel Chromium accepts as trusted. Pair it with yabai’s focus-without-raise pattern, plus an off-screen primer click at (-1, -1), and the click lands without the window ever raising.<p>One thing we learned: the right addressing mode depends on the app. Native macOS apps usually have rich AX trees, Chromium-family apps often need a hybrid of AX and screenshots, and apps like Blender or CAD tools may expose almost no useful AX surface. The mistake is defaulting to pixels everywhere - or defaulting to AX everywhere.<p>Long technical writeup: <a href="https://github.com/trycua/cua/blob/main/blog/inside-macos-window-internals.md" rel="nofollow">https://github.com/trycua/cua/blob/main/blog/inside-macos-wi...</a><p>I would like feedback from people building Mac automation, agent harnesses, or accessibility tooling. If it breaks on an macOS app you care about, that is useful data for us.

Show HN: Drive any macOS app in the background without stealing the cursor

Hi HN, Francesco from Cua here. I hacked this project together last weekend, inspired by the Codex Computer-Use release and lessons learned from deploying GUI-operating agents for our customers.<p>The main problem: when a UI automation process controls a desktop app today, it usually takes over the human’s session. Your cursor moves, keyboard focus gets stolen, windows jump to the front, and you have to stop working until the agent is done. That is why we have historically avoided encouraging users to run these processes directly on their host machine, instead relying on VMs or GUI containers for concurrency and background execution.<p>But computer-use - the tools we give agents to operate computers like humans - does not scale cleanly that way. As models get smarter, agents need to share hosts safely, run in the background, and avoid collisions with the human or other agents using the same machine.<p>We realized macOS has no first-class API for "drive this app without touching the cursor". CGEventPost routes through the hardware input stream, so it moves your cursor. CGEvent.postToPid avoids the cursor warp, but Chromium treats those events as untrusted and silently drops clicks at the renderer boundary. Activating the target app first raises the window and pulls focus, defeating the point of background execution.<p>Cua Driver is our attempt at a real fix: a background computer-use driver for macOS that lets an agent click, type, scroll, and read native apps while your cursor, frontmost app, and Space stay where they are. The default interface is a CLI, so it is easy to script or call from any coding agent shell.<p>Try it on macOS 14+:<p>/bin/bash -c "$(curl -fsSL <a href="https://raw.githubusercontent.com/trycua/cua/main/libs/cua-driver/scripts/install.sh" rel="nofollow">https://raw.githubusercontent.com/trycua/cua/main/libs/cua-d...</a>)"<p>The first internal use case was delegated demo recording. We ask Claude Code to drive an app while 'cua-driver recording start' captures the trajectory, screenshots, actions, and click markers. The result is an agent-generated product demo, Screen Studio inspired.<p>Other things we have used it for:<p>- Replacing Vercel’s agent-browser and other browser-use CLIs. With Claude Code and Cua Driver, you do not need Chrome DevTools Protocol at all.<p>- A dev-loop QA agent that reproduces a visual bug, edits code, rebuilds, and verifies the UI while my editor stays frontmost.<p>- Personal-assistant flows that use iMessage from Claude Code, Hermes, or other general-purpose agent CLIs.<p>- Pulling visual context from Chrome, Figma, Preview, or YouTube windows I am not looking at, without relying on their APIs.<p>What made this harder than expected:<p>- CGEventPost warps the cursor because it goes through the HID stream.<p>- CGEvent.postToPid does not warp the cursor, but Chromium drops it at the renderer IPC boundary.<p>- Activating the target first raises the window and can drag you across Spaces.<p>- Electron apps stop keeping useful AX trees alive when windows are occluded without a private remote-aware SPI.<p>The unlock was SkyLight. SLEventPostToPid is a sibling of the public per-PID call, but it travels through a WindowServer channel Chromium accepts as trusted. Pair it with yabai’s focus-without-raise pattern, plus an off-screen primer click at (-1, -1), and the click lands without the window ever raising.<p>One thing we learned: the right addressing mode depends on the app. Native macOS apps usually have rich AX trees, Chromium-family apps often need a hybrid of AX and screenshots, and apps like Blender or CAD tools may expose almost no useful AX surface. The mistake is defaulting to pixels everywhere - or defaulting to AX everywhere.<p>Long technical writeup: <a href="https://github.com/trycua/cua/blob/main/blog/inside-macos-window-internals.md" rel="nofollow">https://github.com/trycua/cua/blob/main/blog/inside-macos-wi...</a><p>I would like feedback from people building Mac automation, agent harnesses, or accessibility tooling. If it breaks on an macOS app you care about, that is useful data for us.

Show HN: Drive any macOS app in the background without stealing the cursor

Hi HN, Francesco from Cua here. I hacked this project together last weekend, inspired by the Codex Computer-Use release and lessons learned from deploying GUI-operating agents for our customers.<p>The main problem: when a UI automation process controls a desktop app today, it usually takes over the human’s session. Your cursor moves, keyboard focus gets stolen, windows jump to the front, and you have to stop working until the agent is done. That is why we have historically avoided encouraging users to run these processes directly on their host machine, instead relying on VMs or GUI containers for concurrency and background execution.<p>But computer-use - the tools we give agents to operate computers like humans - does not scale cleanly that way. As models get smarter, agents need to share hosts safely, run in the background, and avoid collisions with the human or other agents using the same machine.<p>We realized macOS has no first-class API for "drive this app without touching the cursor". CGEventPost routes through the hardware input stream, so it moves your cursor. CGEvent.postToPid avoids the cursor warp, but Chromium treats those events as untrusted and silently drops clicks at the renderer boundary. Activating the target app first raises the window and pulls focus, defeating the point of background execution.<p>Cua Driver is our attempt at a real fix: a background computer-use driver for macOS that lets an agent click, type, scroll, and read native apps while your cursor, frontmost app, and Space stay where they are. The default interface is a CLI, so it is easy to script or call from any coding agent shell.<p>Try it on macOS 14+:<p>/bin/bash -c "$(curl -fsSL <a href="https://raw.githubusercontent.com/trycua/cua/main/libs/cua-driver/scripts/install.sh" rel="nofollow">https://raw.githubusercontent.com/trycua/cua/main/libs/cua-d...</a>)"<p>The first internal use case was delegated demo recording. We ask Claude Code to drive an app while 'cua-driver recording start' captures the trajectory, screenshots, actions, and click markers. The result is an agent-generated product demo, Screen Studio inspired.<p>Other things we have used it for:<p>- Replacing Vercel’s agent-browser and other browser-use CLIs. With Claude Code and Cua Driver, you do not need Chrome DevTools Protocol at all.<p>- A dev-loop QA agent that reproduces a visual bug, edits code, rebuilds, and verifies the UI while my editor stays frontmost.<p>- Personal-assistant flows that use iMessage from Claude Code, Hermes, or other general-purpose agent CLIs.<p>- Pulling visual context from Chrome, Figma, Preview, or YouTube windows I am not looking at, without relying on their APIs.<p>What made this harder than expected:<p>- CGEventPost warps the cursor because it goes through the HID stream.<p>- CGEvent.postToPid does not warp the cursor, but Chromium drops it at the renderer IPC boundary.<p>- Activating the target first raises the window and can drag you across Spaces.<p>- Electron apps stop keeping useful AX trees alive when windows are occluded without a private remote-aware SPI.<p>The unlock was SkyLight. SLEventPostToPid is a sibling of the public per-PID call, but it travels through a WindowServer channel Chromium accepts as trusted. Pair it with yabai’s focus-without-raise pattern, plus an off-screen primer click at (-1, -1), and the click lands without the window ever raising.<p>One thing we learned: the right addressing mode depends on the app. Native macOS apps usually have rich AX trees, Chromium-family apps often need a hybrid of AX and screenshots, and apps like Blender or CAD tools may expose almost no useful AX surface. The mistake is defaulting to pixels everywhere - or defaulting to AX everywhere.<p>Long technical writeup: <a href="https://github.com/trycua/cua/blob/main/blog/inside-macos-window-internals.md" rel="nofollow">https://github.com/trycua/cua/blob/main/blog/inside-macos-wi...</a><p>I would like feedback from people building Mac automation, agent harnesses, or accessibility tooling. If it breaks on an macOS app you care about, that is useful data for us.

Show HN: Live Sun and Moon Dashboard with NASA Footage

Show HN: Live Sun and Moon Dashboard with NASA Footage

Show HN: Live Sun and Moon Dashboard with NASA Footage