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Show HN: Dlog – Journaling and AI coach that learns what drives wellbeing (Mac)

Hi HN! I’m Johan. I built Dlog, a journaling app with an AI coach that tracks how your personality, daily experiences, and well-being connect over time. It’s based on my PhD research in entrepreneurial well-being.<p>Edit: here's a video demo so you can see it before downloading: <a href="https://www.youtube.com/watch?v=74C4P8I164M" rel="nofollow">https://www.youtube.com/watch?v=74C4P8I164M</a> - it's unvarnished but I'm told that's how people like it here :)<p>How Dlog works<p>- Journal and set goals/projects; Dlog scores entries on-device (sentiment + narrative signals) and updates your personal model.<p>- A built-in structural equation model (SEM) estimates which factors actually move your well-being week to week.<p>- The Coach turns those findings into specific guidance (e.g., “protect 90 minutes after client calls; that’s when energy dips for you”).<p>- No account; your journals live locally (in your calendar). You decide what, if anything, leaves the device.<p>The problem<p>- Generic AI coaches give advice without understanding your personality or context.<p>- Traditional journaling is reflective but doesn’t surface causal patterns.<p>- Well-being apps rarely account for individual differences or test what works for you over time.<p>What my research found (plain English)<p>In my PhD I modeled how Personality, Character, Resources, and Well-Being interact over time. The key is latent relationships: for example, Autonomy can buffer the impact of low Extraversion on social drain, while time/energy constraints mediate whether “good advice” is actionable. These effects are person-specific and evolve—so you need a model that learns you, not averages.<p>The solution<p>Dlog pairs on-device journaling analytics with an SEM that updates weekly. You get a running estimate of “what moves the needle for me,” and the Coach translates that into concrete suggestions aligned with your goals and constraints.<p>Early stories (anonymized from pilot users)<p>- A founder saw energy dips clustered after external calls; moving deep work to mornings reduced “bad days” and improved weekly mood stability.<p>- A solo designer’s autonomy scores predicted well-being more than raw hours worked; small boundary changes (client comms windows) helped more than time-tracking tweaks.<p>Tech & security<p>- Platform: macOS (Swift/SwiftUI). Data: local storage + EventKit calendar for entries/timestamps.<p>- Analytics: on-device sentiment + narrative features; SEM computed locally; weekly updates compare to your baseline.<p>- AI Coach: uses an enterprise LLM API for reasoning on derived features/summaries. By default, raw journal text does not leave the device; you can opt-in per prompt if you want the Coach to read a specific passage.<p>- Why 61 baseline variables? The SEM needs multiple indicators per construct (Personality, Character, Resources, Well-Being) to estimate stable latent factors without overfitting; weekly check-ins refresh those signals.<p>What I’ve learned building this<p>- Users value clarity with depth: concise recommendations paired with focused dashboards, often 5–10 charts, to explain the “why” and trade-offs.<p>- Cold start matters: a solid baseline makes the first week of insights credibly useful.<p>- Privacy UX needs to be explicit: users want granular control over what the Coach can read, per request.<p>I’m looking for feedback on:<p>- Onboarding (baseline survey and first-week experience)<p>- Coach guidance clarity and usefulness<p>- Analytics accuracy vs. your lived experience<p>- Edge cases, bugs, and performance<p>Download: <a href="https://dlog.pro" rel="nofollow">https://dlog.pro</a><p>If you hit token limits while testing, email me at johan@dlog.pro<p>Background<p>PhD (Hunter Center for Entrepreneurship, Strathclyde), MBA (Babson), BComm (UCD). I study solo self-employment and well-being, and built Dlog to bring that research into a tool practitioners can use.<p>Note: The Coach activates after your first scored entry. If you haven’t written one yet, you’ll see a hold state—add a quick journal entry and it unlocks.<p>Appearance: On a few Macs the initial theme can render darker than intended. If you see this, switch to Light Mode as a temporary workaround; a fix is incoming.<p>Edit: For general users it's free for 14 days with 10K free tokens; then its 1.99 per month at the moment. However, for HN readers that DM me or email me with the email they register with, I'll give a free perpetual license so there's no monthly fee; and add 1 million tokens.

Show HN: Apache Fory Rust – 10-20x faster serialization than JSON/Protobuf

Serialization framework with some interesting numbers: 10-20x faster on nested objects than json/protobuf.<p><pre><code> Technical approach: compile-time codegen (no reflection), compact binary protocol with meta-packing, little-endian layout optimized for modern CPUs. Unique features that other fast serializers don't have: - Cross-language without IDL files (Rust ↔ Python/Java/Go) - Trait object serialization (Box<dyn Trait>) - Automatic circular reference handling - Schema evolution without coordination Happy to discuss design trade-offs. Benchmarks: https://fory.apache.org/docs/benchmarks/rust</code></pre>

Show HN: Apache Fory Rust – 10-20x faster serialization than JSON/Protobuf

Serialization framework with some interesting numbers: 10-20x faster on nested objects than json/protobuf.<p><pre><code> Technical approach: compile-time codegen (no reflection), compact binary protocol with meta-packing, little-endian layout optimized for modern CPUs. Unique features that other fast serializers don't have: - Cross-language without IDL files (Rust ↔ Python/Java/Go) - Trait object serialization (Box<dyn Trait>) - Automatic circular reference handling - Schema evolution without coordination Happy to discuss design trade-offs. Benchmarks: https://fory.apache.org/docs/benchmarks/rust</code></pre>

Show HN: ISS in Real Time – 25 Years Aboard the International Space Station

Today my collaborator and I are releasing issinrealtime.org, a multimedia project that plays back every day onboard the ISS. Feedback welcomed.<p>Here's an article that was just released about it: <a href="https://www.collectspace.com/news/news-102725a-iss-in-real-time-25-years-continuous-human-occupancy-space-station.html" rel="nofollow">https://www.collectspace.com/news/news-102725a-iss-in-real-t...</a><p>I also wrote a "making of" post about it here: <a href="https://benfeist.com/posts/iss-in-real-time/" rel="nofollow">https://benfeist.com/posts/iss-in-real-time/</a>

Show HN: ISS in Real Time – 25 Years Aboard the International Space Station

Today my collaborator and I are releasing issinrealtime.org, a multimedia project that plays back every day onboard the ISS. Feedback welcomed.<p>Here's an article that was just released about it: <a href="https://www.collectspace.com/news/news-102725a-iss-in-real-time-25-years-continuous-human-occupancy-space-station.html" rel="nofollow">https://www.collectspace.com/news/news-102725a-iss-in-real-t...</a><p>I also wrote a "making of" post about it here: <a href="https://benfeist.com/posts/iss-in-real-time/" rel="nofollow">https://benfeist.com/posts/iss-in-real-time/</a>

Show HN: ISS in Real Time – 25 Years Aboard the International Space Station

Today my collaborator and I are releasing issinrealtime.org, a multimedia project that plays back every day onboard the ISS. Feedback welcomed.<p>Here's an article that was just released about it: <a href="https://www.collectspace.com/news/news-102725a-iss-in-real-time-25-years-continuous-human-occupancy-space-station.html" rel="nofollow">https://www.collectspace.com/news/news-102725a-iss-in-real-t...</a><p>I also wrote a "making of" post about it here: <a href="https://benfeist.com/posts/iss-in-real-time/" rel="nofollow">https://benfeist.com/posts/iss-in-real-time/</a>

Show HN: Bash Screensavers

A github project to collect a bunch of bash-based screensavers/visualizations.

Show HN: Bash Screensavers

A github project to collect a bunch of bash-based screensavers/visualizations.

Show HN: Bash Screensavers

A github project to collect a bunch of bash-based screensavers/visualizations.

Show HN: Git Auto Commit (GAC) – LLM-powered Git commit command line tool

GAC is a tool I built to help users spend less time summing up what was done and more time building. It uses LLMs to generate contextual git commit messages from your code changes. And it can be a drop-in replacement for `git commit -m "..."`.<p>Example:<p><pre><code> feat(auth): add OAuth2 integration with GitHub and Google - Implement OAuth2 authentication flow - Add provider configuration for GitHub and Google - Create callback handler for token exchange - Update login UI with social auth buttons </code></pre> Don't like it? Reroll with 'r', or type `r "focus on xyz"` and it rerolls the commit with your feedback.<p>You can try it out with uvx (no install):<p><pre><code> uvx gac init # config wizard uvx gac </code></pre> <i>Note: `gac init` creates a .gac.env file in your home directory with your chosen provider, model, and API key.</i><p>Tech details:<p><i>14 providers</i> - Supports local (Ollama & LM Studio) and cloud (OpenAI, Anthropic, Gemini, OpenRouter, Groq, Cerebras, Chutes, Fireworks, StreamLake, Synthetic, Together AI, & Z.ai (including their extremely cheap coding plans!)).<p><i>Three verbosity modes</i> - Standard with bullets (default), one-liners (`-o`), or verbose (`-v`) with detailed Motivation/Architecture/Impact sections.<p><i>Secret detection</i> - Scans for API keys, tokens, and credentials before committing. Has caught my API keys on a new project when I hadn't yet gitignored .env.<p><i>Flags</i> - Automate common workflows:<p><pre><code> `gac -h "bug fix"` - pass hints to guide intent `gac -yo` - auto-accept the commit message in one-liner mode `gac -ayp` - stage all files, auto-accept the commit message, and push (yolo mode) </code></pre> Would love to hear your feedback! Give it a try and let me know what you think! <3<p>GitHub: <a href="https://github.com/cellwebb/gac" rel="nofollow">https://github.com/cellwebb/gac</a>

Show HN: Git Auto Commit (GAC) – LLM-powered Git commit command line tool

GAC is a tool I built to help users spend less time summing up what was done and more time building. It uses LLMs to generate contextual git commit messages from your code changes. And it can be a drop-in replacement for `git commit -m "..."`.<p>Example:<p><pre><code> feat(auth): add OAuth2 integration with GitHub and Google - Implement OAuth2 authentication flow - Add provider configuration for GitHub and Google - Create callback handler for token exchange - Update login UI with social auth buttons </code></pre> Don't like it? Reroll with 'r', or type `r "focus on xyz"` and it rerolls the commit with your feedback.<p>You can try it out with uvx (no install):<p><pre><code> uvx gac init # config wizard uvx gac </code></pre> <i>Note: `gac init` creates a .gac.env file in your home directory with your chosen provider, model, and API key.</i><p>Tech details:<p><i>14 providers</i> - Supports local (Ollama & LM Studio) and cloud (OpenAI, Anthropic, Gemini, OpenRouter, Groq, Cerebras, Chutes, Fireworks, StreamLake, Synthetic, Together AI, & Z.ai (including their extremely cheap coding plans!)).<p><i>Three verbosity modes</i> - Standard with bullets (default), one-liners (`-o`), or verbose (`-v`) with detailed Motivation/Architecture/Impact sections.<p><i>Secret detection</i> - Scans for API keys, tokens, and credentials before committing. Has caught my API keys on a new project when I hadn't yet gitignored .env.<p><i>Flags</i> - Automate common workflows:<p><pre><code> `gac -h "bug fix"` - pass hints to guide intent `gac -yo` - auto-accept the commit message in one-liner mode `gac -ayp` - stage all files, auto-accept the commit message, and push (yolo mode) </code></pre> Would love to hear your feedback! Give it a try and let me know what you think! <3<p>GitHub: <a href="https://github.com/cellwebb/gac" rel="nofollow">https://github.com/cellwebb/gac</a>

Show HN: Helium Browser for Android with extensions support, based on Vanadium

Been working on an experimental Chromium-based browser that brings 2 major features to your phone/tablet:<p>1. desktop-style extensions: natively install any extensions (like uBO) from the chrome web store, just toggle "desktop site" in the menu first.<p>2. privacy/security hardening: applies the full patch sets from Vanadium (with Helium's currently wip).<p>Means you get both browsers' excellent privacy features, like Vanadium's webrtc IP policy option that protects your real IP by default, and security improvements such as JIT being disabled by default, all while being a reasonably efficient FOSS app that can be installed on any (modern) android.<p>It's still in beta, and as I note in the README, it's not a replacement for the full OS-level security model you'd get from running the GrapheneOS Vanadium combo. However, goal was to combine privacy of Vanadium with the power of desktop extensions and Helium features, and make it accessible to a wider audience. (Passkeys from Bitwarden Mobile should also work straight away once merged in the list of FIDO2 privileged browsers)<p>Build scripts are in the repo if you want to compile it yourself. You can find pre-built releases there too.<p>Would love any feedback/support!

Show HN: Helium Browser for Android with extensions support, based on Vanadium

Been working on an experimental Chromium-based browser that brings 2 major features to your phone/tablet:<p>1. desktop-style extensions: natively install any extensions (like uBO) from the chrome web store, just toggle "desktop site" in the menu first.<p>2. privacy/security hardening: applies the full patch sets from Vanadium (with Helium's currently wip).<p>Means you get both browsers' excellent privacy features, like Vanadium's webrtc IP policy option that protects your real IP by default, and security improvements such as JIT being disabled by default, all while being a reasonably efficient FOSS app that can be installed on any (modern) android.<p>It's still in beta, and as I note in the README, it's not a replacement for the full OS-level security model you'd get from running the GrapheneOS Vanadium combo. However, goal was to combine privacy of Vanadium with the power of desktop extensions and Helium features, and make it accessible to a wider audience. (Passkeys from Bitwarden Mobile should also work straight away once merged in the list of FIDO2 privileged browsers)<p>Build scripts are in the repo if you want to compile it yourself. You can find pre-built releases there too.<p>Would love any feedback/support!

Show HN: Erdos – open-source, AI data science IDE

Hey HN! We’re Jorge and Will from Lotas (<a href="https://www.lotas.ai/">https://www.lotas.ai/</a>), and we’ve built Erdos, a secure AI-powered data science IDE that’s fully open source (<a href="https://www.lotas.ai/erdos">https://www.lotas.ai/erdos</a>).<p>A few months ago, we shared Rao, an AI coding assistant for RStudio (<a href="https://news.ycombinator.com/item?id=44638510">https://news.ycombinator.com/item?id=44638510</a>). We built Rao to bring the Cursor-like experience to RStudio users. Now we want to take the next step and deliver a tool for the entire data science community that handles Python, R, SQL, and Julia workflows.<p>Erdos is a fork of VS Code designed for data science. It includes:<p>- An AI that can search, read, and write across all file types for Python, R, SQL, and Julia. Also, for Jupyter notebooks, we’ve optimized a jupytext system to allow the AI to make faster edits.<p>- Built-in Python, R, and Julia consoles accessible to both the user and AI<p>- Plot pane that tracks and organizes plots by file and time<p>- Database pane for connecting to and manipulating SQL or FTP data sources<p>- Environment pane for viewing variables, packages, and environments<p>- Help pane for Python, R, and Julia documentation<p>- Remote development via SSH or containers<p>- AI assistant available through a single-click sign-in to our zero data retention backend, bring your own key, or a local model<p>- Open source AGPLv3 license<p>We built Erdos because data scientists are often second-class citizens in modern IDEs. Tools like VS Code, Cursor, and Claude Code are made for software developers, not for people working across Jupyter notebooks, scripts, and SQL. We wanted an IDE that feels native to data scientists, while offering the same AI productivity boosts.<p>You can try Erdos at <a href="https://www.lotas.ai/erdos">https://www.lotas.ai/erdos</a>, check out our source code on our GitHub (<a href="https://github.com/lotas-ai/erdos" rel="nofollow">https://github.com/lotas-ai/erdos</a>), and let us know what features would make it more useful for your work. We’d love your feedback below!

Show HN: Erdos – open-source, AI data science IDE

Hey HN! We’re Jorge and Will from Lotas (<a href="https://www.lotas.ai/">https://www.lotas.ai/</a>), and we’ve built Erdos, a secure AI-powered data science IDE that’s fully open source (<a href="https://www.lotas.ai/erdos">https://www.lotas.ai/erdos</a>).<p>A few months ago, we shared Rao, an AI coding assistant for RStudio (<a href="https://news.ycombinator.com/item?id=44638510">https://news.ycombinator.com/item?id=44638510</a>). We built Rao to bring the Cursor-like experience to RStudio users. Now we want to take the next step and deliver a tool for the entire data science community that handles Python, R, SQL, and Julia workflows.<p>Erdos is a fork of VS Code designed for data science. It includes:<p>- An AI that can search, read, and write across all file types for Python, R, SQL, and Julia. Also, for Jupyter notebooks, we’ve optimized a jupytext system to allow the AI to make faster edits.<p>- Built-in Python, R, and Julia consoles accessible to both the user and AI<p>- Plot pane that tracks and organizes plots by file and time<p>- Database pane for connecting to and manipulating SQL or FTP data sources<p>- Environment pane for viewing variables, packages, and environments<p>- Help pane for Python, R, and Julia documentation<p>- Remote development via SSH or containers<p>- AI assistant available through a single-click sign-in to our zero data retention backend, bring your own key, or a local model<p>- Open source AGPLv3 license<p>We built Erdos because data scientists are often second-class citizens in modern IDEs. Tools like VS Code, Cursor, and Claude Code are made for software developers, not for people working across Jupyter notebooks, scripts, and SQL. We wanted an IDE that feels native to data scientists, while offering the same AI productivity boosts.<p>You can try Erdos at <a href="https://www.lotas.ai/erdos">https://www.lotas.ai/erdos</a>, check out our source code on our GitHub (<a href="https://github.com/lotas-ai/erdos" rel="nofollow">https://github.com/lotas-ai/erdos</a>), and let us know what features would make it more useful for your work. We’d love your feedback below!

Show HN: Erdos – open-source, AI data science IDE

Hey HN! We’re Jorge and Will from Lotas (<a href="https://www.lotas.ai/">https://www.lotas.ai/</a>), and we’ve built Erdos, a secure AI-powered data science IDE that’s fully open source (<a href="https://www.lotas.ai/erdos">https://www.lotas.ai/erdos</a>).<p>A few months ago, we shared Rao, an AI coding assistant for RStudio (<a href="https://news.ycombinator.com/item?id=44638510">https://news.ycombinator.com/item?id=44638510</a>). We built Rao to bring the Cursor-like experience to RStudio users. Now we want to take the next step and deliver a tool for the entire data science community that handles Python, R, SQL, and Julia workflows.<p>Erdos is a fork of VS Code designed for data science. It includes:<p>- An AI that can search, read, and write across all file types for Python, R, SQL, and Julia. Also, for Jupyter notebooks, we’ve optimized a jupytext system to allow the AI to make faster edits.<p>- Built-in Python, R, and Julia consoles accessible to both the user and AI<p>- Plot pane that tracks and organizes plots by file and time<p>- Database pane for connecting to and manipulating SQL or FTP data sources<p>- Environment pane for viewing variables, packages, and environments<p>- Help pane for Python, R, and Julia documentation<p>- Remote development via SSH or containers<p>- AI assistant available through a single-click sign-in to our zero data retention backend, bring your own key, or a local model<p>- Open source AGPLv3 license<p>We built Erdos because data scientists are often second-class citizens in modern IDEs. Tools like VS Code, Cursor, and Claude Code are made for software developers, not for people working across Jupyter notebooks, scripts, and SQL. We wanted an IDE that feels native to data scientists, while offering the same AI productivity boosts.<p>You can try Erdos at <a href="https://www.lotas.ai/erdos">https://www.lotas.ai/erdos</a>, check out our source code on our GitHub (<a href="https://github.com/lotas-ai/erdos" rel="nofollow">https://github.com/lotas-ai/erdos</a>), and let us know what features would make it more useful for your work. We’d love your feedback below!

Show HN: Write Go code in JavaScript files

I built a Vite plugin that lets you write Go code directly in .js files using a "use golang" directive. It compiles to WebAssembly automatically.

Show HN: Write Go code in JavaScript files

I built a Vite plugin that lets you write Go code directly in .js files using a "use golang" directive. It compiles to WebAssembly automatically.

Show HN: Write Go code in JavaScript files

I built a Vite plugin that lets you write Go code directly in .js files using a "use golang" directive. It compiles to WebAssembly automatically.

Show HN: JSON Query

I'm working on a tool that will probably involve querying JSON documents and I'm asking myself how to expose that functionality to my users.<p>I like the power of `jq` and the fact that LLMs are proficient at it, but I find it right out impossible to come up with the right `jq` incantations myself. Has anyone here been in a similar situation? Which tool / language did you end up exposing to your users?