NestJS Best Practices (Yet another Claude skill)

DayTradingCentral – Free Trading Journal (Next.js, NestJS, Postgres)

NestJS is a bad TypeScript framework

I’m a Computer Engineering student from Brazil. I built this to showcase backend patterns that go beyond simple CRUDs: row-level multi-tenancy (Prisma), async processing (BullMQ&#x2F;Redis), and observability (OpenTelemetry). Looking for feedback on the architecture!

Show HN: Production-Ready NestJS Back End (Multi-Tenancy, Event-Driven)

Osprey API Tester – API testing inside VS Code for NestJS projects.It reads NestJS controllers and DTO classes to:list available routesparse route params, query params, and headersgenerate request URLs from decoratorsgenerate JSON bodies from DTOsallow sending requests directly from VS CodeNo runtime dependency on the server.
Uses TypeScript AST (ts-morph).
Limitations: NestJS + TypeScript only.

Show HN: Osprey API Tester – VS Code API Testing from NestJS Controllers/DTOs

I recently ran an audit on our latest full-stack repo to figure out why &quot;spinning up a new project&quot; felt like such a heavy lift. I counted every file required just to reach a &quot;production-ready&quot; baseline—before writing a single line of unique feature code.The count was roughly 600 files.To be clear, I&#x27;m not talking about a `create-react-app` sandbox. I mean a compliant, scalable SaaS foundation: Next.js frontend, Node.js&#x2F;NestJS backend, mobile wrapper, CI&#x2F;CD pipelines, and enough security config to pass a SOC2 audit.It sounds ridiculous (and honestly, it feels ridiculous), but when I broke it down, I couldn&#x27;t find many files I was willing to delete.Here is where the bloat comes from:First, the &quot;Configuration Hell&quot; accounts for about 40-50 files alone. We aren&#x27;t just dealing with `package.json` anymore. It&#x27;s `tsconfig.json` (base), `tsconfig.build.json`, `tsconfig.spec.json`... multiplied across frontend, backend, and shared libraries. Then add `.eslintrc.js`, `.prettierrc`, `jest.config.js`, `vitest.config.ts`, `nodemon.json`, and the Docker-compose variants for dev, test, and prod.Then there’s the DevOps and Quality layer. We have roughly 20-30 files for GitHub Actions workflows (lint, test, build, deploy, semantic release), Husky hooks (pre-commit, commit-msg), and pull request templates.But the real multiplier is the separation of concerns. In a modern monorepo, a &quot;Hello World&quot; isn&#x27;t just `console.log`. It’s:
- A NestJS module (Controller, Service, Module, DTO, Entity, Unit Test, E2E Test).
- A Next.js slice (Page, Component, Type definition, API client wrapper).
- A shared library entry.We found that adding a single &quot;minimal&quot; API endpoint usually touches 5-7 files just to maintain architectural standards.The trade-off is painful. On one hand, this setup handles the things we used to forget: security headers, proper logging, consistent error handling, and type safety across boundaries. It prevents the &quot;spaghetti code&quot; distinct to startups that scale too fast.On the other hand, the cognitive load of managing a 600-file &quot;empty&quot; project is massive. Updating dependencies becomes a chore because a major version bump in one tool (like ESLint) cascades through forty config files.I’m curious how others are handling this &quot;starting line&quot; complexity.Are you accepting the boilerplate as the cost of doing business? Or have you found a way to strip this down without sacrificing the compliance&#x2F;safety guardrails that enterprise clients demand?It feels like we&#x27;ve over-engineered the entry point of software development, but I’m not sure what the alternative is for a serious project. We tried going &quot;lean&quot; initially, but spent weeks retrofitting auth and testing harnesses later—which was worse.Is there a middle ground I&#x27;m missing, or is ~600 files just the new normal?

Tell HN: A production-ready "Hello World" is now ~600 files

I built Easemonitor to keep track of service uptime, response times, SEO, vulnerability scans, etc.
It&#x27;s 100 % open‑source (GPL‑3), runs in Docker on a cheap VPS and includes:NestJS API + worker with BullMQ queues
NextJS frontend with SSR caching &amp; image optimization
Prometheus metrics, Loki logs, Grafana dashboards, Jaeger tracing
JWT rotation, WAF rules, CSP&#x2F;HSTS, CVE audit scripts
Webhook DLQ, queue dashboard, healthchecks, maintenance mode
You can try it on my demo <a href="https:&#x2F;&#x2F;easemonitor.com" rel="nofollow">https:&#x2F;&#x2F;easemonitor.com</a>Would love feedback, contributions, or ideas for features.

Show HN: Easemonitor – self‑hosted uptime and performance monitoring

California&#x27;s AB 1043 takes effect January 2027. If your app serves California users, you&#x27;ll need to request OS-level age signals from Apple&#x2F;Google and treat them as &quot;actual knowledge&quot; of a user&#x27;s age. Penalties are $7,500 per affected child for intentional violations.We started building A3 (<a href="https:&#x2F;&#x2F;www.a3api.io" rel="nofollow">https:&#x2F;&#x2F;www.a3api.io</a>) after realizing the law has a gap nobody was talking about: browsers have no OS age signal. If you have a web app, the law creates compliance obligations but the platform provides no mechanism. And on native, you&#x27;re left stitching together Apple&#x27;s Declared Age Range API and Google&#x27;s Play Age Signals yourself — two different APIs, two different response formats, two different integration paths.The standard industry answer is ID uploads and selfie scans. We didn&#x27;t want to build that. Those approaches tank conversion rates, create PII liability, and feel disproportionate to the problem. So we went a different direction: passive behavioral signal fusion.The idea is that children and adults interact with devices differently in measurable ways — motor control, scroll patterns, typing rhythm, form completion speed. Our browser SDK (&lt;5 KB) collects these signals from standard DOM events, computes aggregate scores on-device, and sends only anonymized ratios and averages. No raw coordinates, no keystroke logs, no text content ever leaves the browser. The API processes everything in memory and discards it immediately.On native, we normalize the Apple&#x2F;Google OS signals into a single response. On the web, the behavioral signals become the primary assessment. Either way you get the same response format: a verdict, age bracket, confidence score, evidence tags, and an HMAC-SHA256 signed receipt for your audit trail.To be upfront about limitations: behavioral signals are probabilistic, not deterministic. A confident 12-year-old and a hasty adult can look similar in a short session. We mitigate this with five signal categories (behavioral metrics, input complexity, device context, contextual signals, account longevity) that are weighted and cross-validated, and we apply coverage penalties when fewer categories are present. But this is age estimation, not identity verification — it&#x27;s designed for the &quot;commercially reasonable&quot; standard the statute actually requires, not the false certainty that ID checks imply.The stack is NestJS on AWS Lambda, with client SDKs for React&#x2F;Vue&#x2F;vanilla JS, SwiftUI, and Jetpack Compose. There&#x27;s a free tier (100 checks&#x2F;month) if you want to kick the tires, and a playground at <a href="https:&#x2F;&#x2F;www.a3api.io&#x2F;playground" rel="nofollow">https:&#x2F;&#x2F;www.a3api.io&#x2F;playground</a>.If you maintain an open source project, we have a program that gives you Pro-tier access (50k checks&#x2F;month) for free — the only requirement is a &quot;Powered by A3&quot; in your age gate UI or README. Details at <a href="https:&#x2F;&#x2F;www.a3api.io&#x2F;open-source" rel="nofollow">https:&#x2F;&#x2F;www.a3api.io&#x2F;open-source</a>.Docs: <a href="https:&#x2F;&#x2F;www.a3api.io&#x2F;docs" rel="nofollow">https:&#x2F;&#x2F;www.a3api.io&#x2F;docs</a>Happy to answer questions about the signal fusion approach, the legal nuances, or where we think this falls short.

Show HN: Complying with California's AB 1043 via signal fusion, not ID uploads

Hi HN,I kept finding myself writing scripts or manually running prompts to do things like PR reviews, documentation generation, or issue triage on my GitHub repositories.After doing this enough times, I decided to build a small platform to automate these workflows.I recently open sourced it:<a href="https:&#x2F;&#x2F;github.com&#x2F;Njuelle&#x2F;Codaholiq" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;Njuelle&#x2F;Codaholiq</a>Codaholiq lets you run AI-powered workflows triggered by GitHub events.You connect a repository and define automations that run when certain events occur, such as:- pull request opened
- push to a branch
- issue created
- cron schedule
- manual triggerEach automation defines:- a trigger
- an AI provider or model (Claude Code, Codex, Gemini, etc.)
- a prompt template
- optional conditions on the GitHub event payloadWhen the event happens, Codaholiq renders the prompt using variables from the event context and dispatches a GitHub Actions workflow that runs the AI task.The platform also tracks executions with:- real-time log streaming
- token usage and cost tracking
- execution historyOne design goal was self-hosting, so the entire platform can run locally or on your own infrastructure.The architecture is intentionally simple:- GitHub webhooks trigger automations
- jobs are queued using Redis and BullMQ
- the NestJS backend processes the queue and dispatches workflows to GitHub Actions
- AI models are called through providers
- logs and token usage are streamed back to the UIThe full platform can run with Docker using Postgres and Redis.Example automation:An automation could trigger when a pull request is opened. 
It sends the PR diff to an AI model asking for a code review, then runs the task through a GitHub Actions workflow.Some possible use cases:- automated PR reviews
- generating documentation from diffs
- code refactoring suggestions
- issue triage
- automatic changelog generationIt&#x27;s still early, but the core pieces are working.One thing I&#x27;m unsure about is whether this project makes more sense as:- a self-hosted automation tool
- or a hosted version that simplifies setup and managementI&#x27;m curious how teams here would prefer to run something like this.Any feedback is very welcome.

Show HN: Codaholiq, AI automations for GitHub repositories

After my annual checkup showed LDL 4.4 mmol&#x2F;L (170 mg&#x2F;dL) and triglycerides 
2.0 mmol&#x2F;L at 33, I tried tracking with ChatGPT (lost data when context got 
too big), then spreadsheets (too tedious).Built a simple tracker focused on cholesterol. Log meals, see lipid breakdown, 
track trends. I believe snacks and sugar were my main issue.Stack: Angular 17 + NestJS + SupabaseStarted January 1st, already lost 3kg. Same breakfast daily (psyllium, oats, 
chia, skyr, whey, berries), cut sugar from daily to once per week.Free during beta. Looking for feedback on whether strict diet cutting or 80&#x2F;20 
approach is more sustainable long-term.

Show HN: Cholesterol Tracker – Built after high cholesterol diagnosis at 33

Focido is now live on App Store and Google Play after months of beta testing and weekly updates.What is it?
A social to-do app where your goals live in a feed, and real humans (not AI) send nudges to help you follow through. We built it because solo trackers have ~20% completion rates, while social accountability apps like Strava get people moving consistently.Key features:Post tasks, get matched with motivatorsReal-time nudges, replies, and task visibilityNudge limits, cooldowns, anonymous tasks for privacyLeagues, leaderboards, and motivator ratingsCustom reminder windows so it fits your scheduleTech:
Flutter (iOS&#x2F;Android), NestJS&#x2F;Supabase backend, RevenueCat for IAP. Real-time with Supabase. MVP in ~4 months.Why we built it:
Most productivity apps fail at completion. Humans are better at creating the right kind of pressure (guilt + reciprocity). Early data shows 3x completion uplift vs solo apps.Links:
iOS: <a href="https:&#x2F;&#x2F;apps.apple.com&#x2F;us&#x2F;app&#x2F;focido&#x2F;id6757135734">https:&#x2F;&#x2F;apps.apple.com&#x2F;us&#x2F;app&#x2F;focido&#x2F;id6757135734</a>
Android: <a href="https:&#x2F;&#x2F;play.google.com&#x2F;store&#x2F;apps&#x2F;details?id=com.focido.app.focido">https:&#x2F;&#x2F;play.google.com&#x2F;store&#x2F;apps&#x2F;details?id=com.focido.app...</a>
Website: 
<a href="https:&#x2F;&#x2F;focido.com" rel="nofollow">https:&#x2F;&#x2F;focido.com</a>Open to questions about retention, matching, or the economics of human motivators. Curious what HN thinks of social accountability vs gamification.

Show HN: Focido – social to-do where real people nudge you to finish tasks

Anthropic just launched Remote Control for Claude Code. It lets you control a coding session from your phone or browser. Cool idea, except it requires a $200&#x2F;mo Max plan, supports one session at a time, has no auto-approve rules or hook management, and kills your session if the terminal closes or you lose network for 10 minutes.I built ForkOff because I kept coming back from skiing and biking to find my Claude Code sessions dead. I wanted to approve tool calls from my phone while I was out, not babysit a terminal.ForkOff is the open-source alternative:- Free (MIT licensed)
- E2E encrypted — the relay server sees only opaque blobs
- Auto-approve rules — configure which tools are safe, which need manual approval
- Proper diff rendering on mobile, not raw terminal text
- Sessions survive terminal close
- Self-hostable relay, or --local flag for direct P2P (zero internet)
- Multi-session supportStack: React Native + Expo (mobile), NestJS (relay), Node.js CLI that hooks into Claude Code&#x27;s PreToolUse&#x2F;PostToolUse lifecycle via the SDK. X25519 key exchange, XSalsa20-Poly1305 encryption.iOS beta is live on TestFlight. Android coming soon.We are looking forward to feedback, code contributions, and more!TestFlight: <a href="https:&#x2F;&#x2F;testflight.apple.com&#x2F;join&#x2F;dhh5FrN7" rel="nofollow">https:&#x2F;&#x2F;testflight.apple.com&#x2F;join&#x2F;dhh5FrN7</a>
(Note: We are currently pending apple&#x27;s review on the open-source version of the app expect the release on the above link within 24 hours till then the app config will show that you require an update)GitHub (CLI): <a href="https:&#x2F;&#x2F;github.com&#x2F;Forkoff-app&#x2F;forkoff-cli" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;Forkoff-app&#x2F;forkoff-cli</a>
GitHub (Mobile): <a href="https:&#x2F;&#x2F;github.com&#x2F;Forkoff-app&#x2F;forkoff-react-native" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;Forkoff-app&#x2F;forkoff-react-native</a>
Website: <a href="https:&#x2F;&#x2F;forkoff.app" rel="nofollow">https:&#x2F;&#x2F;forkoff.app</a>

Show HN: ForkOff – Orchestrate Your Claude Agents, Anytime, Anywhere

Hi HN, I&#x27;m the author.I&#x27;ve spent years building Node.js backends (mostly Express and NestJS) and I’ve consistently found traditional ORMs like TypeORM too heavy, while Prisma’s subscription models didn&#x27;t quite fit my need for lightweight CDC (Change Data Capture). I wanted something universal that felt closer to the metal but still handled real-time events seamlessly.Over the past couple of days, I built Kinetic SQL. It&#x27;s a thin, highly flexible SQL wrapper for Node.js (supporting Postgres, MySQL, and SQLite).The CORE focus:
Framework Agnostic: Works beautifully with Express, Fastify, or Vanilla Node, with a dedicated seamless-integration module for NestJS included as a bonus.Real-time Subscriptions: Listen to table changes (INSERT&#x2F;UPDATE&#x2F;DELETE) natively and push to clients (perfect for live dashboards).Zero-Touch Interfaces: The CLI (npx k-sql gen) reads your schema and auto-generates absolute type safety. No more writing interfaces by hand.Native DB Functions: Call your database procedures directly as native JavaScript methods.To stress-test the real-time engine, I built a high-frequency stock market simulator (running on a free Vercel&#x2F;Render stack with a 0-second cold start):Live Demo: <a href="https:&#x2F;&#x2F;live-stock-simulator.vercel.app&#x2F;" rel="nofollow">https:&#x2F;&#x2F;live-stock-simulator.vercel.app&#x2F;</a>
NPM: <a href="https:&#x2F;&#x2F;www.npmjs.com&#x2F;package&#x2F;kinetic-sql" rel="nofollow">https:&#x2F;&#x2F;www.npmjs.com&#x2F;package&#x2F;kinetic-sql</a>I&#x27;d love to hear your thoughts on the API design. 
(P.S. MSSQL support is coming soon!)

Show HN: Kinetic SQL – A lightweight, real-time SQL Engine for Node.js

I spent 4 years trying to build this OAuth server but never finished it.Then I discovered agentic coding and shipped it in 3 weeks.What makes it different:• Dual AI agents analyze every login in &lt;300ms
 - Security Signals Agent: risk scoring (device, IP, geo, velocity)
 - Policy Compliance Agent: business rules (MFA policies, role enforcement)
 - Combined decision: allow&#x2F;log&#x2F;step-up&#x2F;lock&#x2F;deny• Production-ready security
 - PKCE (RFC 7636), DPoP (RFC 9449)
 - MFA (TOTP + WebAuthn&#x2F;Passkeys)
 - IP restrictions, rate limiting, audit trail• EU digital sovereignty
 - GDPR native (data export, legal holds, retention policies)
 - EU hosting, no US Cloud Act exposure
 - Full audit trail (PostgreSQL + Redis Streams)• Zero AI dependency
 - Deterministic fallback if AI timeouts
 - Conservative MEDIUM risk returned (safe default)
 - System keeps running without external LLM calls• Modern stack
 - Backend: NestJS + TypeScript, LangChain&#x2F;LangGraph
 - Frontend: React 19, hexagonal architecture, 91% test coverage
 - Deterministic fallback if AI timeouts (zero dependency)Built as an alternative to Firebase Auth &#x2F; AWS Cognito &#x2F; Auth0 for companies that want control over their authentication infrastructure.Architecture diagrams and screenshots in the repo.Open to feedback and questions.

Show HN: OAuth 2.0 server with AI security agents (EU sovereign alternative)

Hello Hacker News — greetings from South Korea 
I’m a backend engineer working primarily with Go, and I’d like to share a framework I’ve been building to solve a problem I’ve repeatedly encountered in production systems.In my day-to-day work, our backend is built on top of Echo. Echo is fast and reliable as an HTTP transport, but its high level of freedom leaves architectural decisions almost entirely to individual developers. Over time, this led to a system where execution flow and responsibility boundaries varied depending on who last touched a feature. Maintenance became difficult not because the code was incorrect, but because how requests actually executed was no longer obvious.I looked for a Go framework that could provide a clear execution model and structural constraints, similar to what Spring or NestJS offer. I couldn’t find one that fit. Moving to Spring or NestJS would also mean giving up some of Go’s strengths—simplicity, performance, and explicit control—so I decided to build one instead.Spine is an execution-centric backend framework for Go.
It aims to provide enterprise-grade structure while deliberately avoiding hidden magic.What Spine provides
 • An IoC container with explicit, constructor-based dependency injection
 • Interceptors with well-defined execution phases (before, after, completion)
 • First-class support for both HTTP requests and event-driven execution
 • No annotations, no implicit behavior, no convention-driven wiringThe core idea: execution firstThe key difference is Spine’s execution model.Every request—HTTP or event—flows through a single, explicit Pipeline.
The Pipeline is the only component that determines execution order.
Actual method calls are handled by a separate Invoker, keeping execution control and invocation strictly separated.Because of this structure:
 • Execution order is explainable by reading the code
 • Cross-cutting concerns live in the execution flow, not inside controllers
 • Controllers express use cases only, not orchestration logic
 • You can understand request handling by looking at main.goThis design trades some convenience for clarity. In return, it offers stronger control as the system grows in size and complexity.My goal with Spine isn’t just to add another framework to the Go ecosystem, but to start a conversation:
How much execution flow do modern web frameworks hide, and when does that become a maintenance cost?The framework itself is currently written in Korean.
If English support or internationalization is important to you, feel free to open an issue—I plan to prioritize it based on community interest.You can find more details, a basic HTTP example, and a simple Kafka-based MSA demo here:
Repository: <a href="https:&#x2F;&#x2F;github.com&#x2F;NARUBROWN&#x2F;spine" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;NARUBROWN&#x2F;spine</a>Thanks for reading. I’d really appreciate your feedback.

Show HN: Spine – an execution-centric backend framework for Go

LeetCode wasn&#x27;t actually preparing me or anyone else for the pressure of a real technical interview.Most platforms just give you a text box and a compiler. I wanted something that actually simulates the back-and-forth of an interviewer pushing you on time complexity, asking follow-up questions, and pointing out edge cases you missed.&gt; The Stack:
I built the backend with nestjs, prisma, postgresql, Webrtc for real time back and forth conv and [socket.io](<a href="http:&#x2F;&#x2F;socket.io" rel="nofollow">http:&#x2F;&#x2F;socket.io</a>) events in panel like code run etc…. claude-haiku-4-5 for conv and anthropic.claude-sonnet-4-6 for interview scoring.&gt; Where it still falls short:
It’s not perfect. Sometimes the AI gets overly pedantic about syntax instead of focusing on the core algorithmic logic. I’m still tuning the prompts to make it behave more like a senior engineer and less like a strict compiler.I&#x27;m currently trying to stress-test the system. I’d love for you to try breaking the AI interviewer or tell me why this approach is flawed. Happy to answer any questions about the stack or the prompt engineering.

Show HN: I built an AI-powered technical interview prep tool

Hi HN,We built Supercheck – an open source platform that combines test automation and uptime monitoring in one self-hosted solution.*The Problem:*
Most monitoring tools are expensive SaaS products that charge per check. Test automation and monitoring are often separate concerns, using different tools and workflows. We wanted a unified platform where you can write a Playwright test once and use it for both CI&#x2F;CD testing and production monitoring and use same tool for k6 performance tests too.*What Supercheck Does:*Testing:
- Playwright browser tests (UI&#x2F;E2E) with screenshots, traces, videos
- API tests (HTTP&#x2F;GraphQL)
- Database tests (PostgreSQL, MySQL)
- k6 performance tests
- Schedule tests via cron or trigger from CI&#x2F;CDMonitoring:
- HTTP, Website, Ping, Port monitors
- Synthetic monitors (run full Playwright tests on a schedule)
- Multi-region: US East, EU Central, Asia Pacific
- Threshold-based alerting (consecutive failures before alerting)Extras:
- AI Create: Generate tests from plain English
- AI Fix: Automatically analyze failures and suggest fixes
- Public status pages with incident management
- Alerts: Slack, Discord, Telegram, Email, Teams, webhooks
- RBAC with 6 permission levels
- Browser extensions: Chrome + Edge*Architecture:*
Next.js frontend, NestJS workers, PostgreSQL, Redis + BullMQ for job queuing, MinIO for artifacts. Each browser test runs in an isolated Playwright context. Workers are stateless – scale horizontally by adding more containers.*Deploy:*
```bash
git clone <a href="https:&#x2F;&#x2F;github.com&#x2F;supercheck-io&#x2F;supercheck" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;supercheck-io&#x2F;supercheck</a>
cd supercheck&#x2F;deploy&#x2F;docker
.&#x2F;init-secrets.sh
docker compose -f docker-compose.yml up -d
```One-click deployment with Coolify.*Links:*
- GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;supercheck-io&#x2F;supercheck" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;supercheck-io&#x2F;supercheck</a>
- Docs: <a href="https:&#x2F;&#x2F;supercheck.io&#x2F;docs" rel="nofollow">https:&#x2F;&#x2F;supercheck.io&#x2F;docs</a>Happy to answer any questions about the architecture, design decisions, or roadmap.

Show HN: Supercheck.io – Open-Source AI-Powered Test Automation and Monitoring

Hey HN,In 2024 my son was born, and during the long nights of frequent wake-ups, I started (and never finished...) building an Electron app. I very quickly found that the boilerplate required to wire up the main and renderer processes to be very cumbersome, and I&#x27;m sure like many others, started to build abstractions around it to make life easier.Having been heavily indoctrinated in the NestJS ecosystem through my workplace, I started to grow fond of DI, decorators, and the declarative style of working.My first attempt at abstraction was fairly mediocre, but I recently decided to have a second crack. I leaned more heavily into decorators so that I could give the library a clean syntax that was simple to use. I then packaged it up so that others can use it too.Electron IPC Bridge allows you to decorate your classes in the main process, and automatically configures the contracts in the preload. The accompanying vite plugin generates types from those contracts and ensures type-safety in the renderer. Change your contracts? The types update too. Easy!Before:<pre><code> &#x2F;&#x2F; Main
 ipcMain.handle(&quot;users.get_profile&quot;, async (_event, userId: string) =&gt; {
 return userService.getProfile(userId);
 });

 &#x2F;&#x2F; Preload
 &#x2F;&#x2F; Easy to make a mistake with the channel, or forget to register 
 contextBridge.exposeInMainWorld(&quot;api&quot;, {
 getProfile: (id: string) =&gt; ipcRenderer.invoke(&quot;users.get_profile&quot;, id),
 });

 &#x2F;&#x2F; Renderer 
 &#x2F;&#x2F; No type-safety 
 const profile = await window.api.getProfile(userId); 

</code></pre>
After:<pre><code> &#x2F;&#x2F; Main
 @IpcController()
 class UsersController {
 @IpcHandle()
 async getProfile(userId: string) {
 return userService.getProfile(userId);
 }
 }

 &#x2F;&#x2F; Preload
 setupPreload();

 &#x2F;&#x2F; Renderer
 &#x2F;&#x2F; 100% Type-safe, auto-generated contracts with IDE autocomplete
 const profile = await window.api.users.getProfile(userId);
</code></pre>
I&#x27;ve also tried to supply a few different DI library examples too to help people get started. I took my original unfinished app and managed to migrate it fairly painlessly! It&#x27;s also using Nest now instead of typedi.AI Disclosure:Core: About ~90% handwritten with some assistance and refactoring in placesVite plugin: Around 50&#x2F;50, leaning towards AI leading where my experience with Vite is lackingDocs: Mostly written by me, but AI planned site structure, and reviewed and edited what I wrote. It also wrote the troubleshooting page and generated some diagrams for me.This post was all me!

Show HN: Electron IPC Bridge- Auto-generated type-safety without the boilerplate

Hi HN,I built Locus, an open-source project management platform designed for engineering teams that want to use AI coding agents.The core idea: plan sprints and manage tasks in a cloud dashboard, but all code execution happens locally on your infrastructure. Your source code never leaves your machine.How it works:- locus plan: AI generates a sprint plan by analyzing your codebase. It uses multi-agent roles to break down directives into structured tasks with complexity estimates and risk assessments. You can reject and iterate on plans before approving.- locus run: An agent picks up tasks from the sprint, executes them sequentially on a single branch, auto-commits after each task, and opens a PR when the sprint is done. Supports both Claude and Codex as backends.- locus review: Review that understands your full codebase, not just diffs. Detects bugs, security issues, and performance problems. Posts review comments directly to GitHub PRs.- locus discuss: Have architectural discussions with AI that has full project context. Insights and decisions are automatically extracted and saved.- Telegram bot: Manage your agent remotely from your phone.- VSCode extension: Chat with AI in your editor with full repo context.The whole system is free, self-hostable, and works with your existing GitHub workflow. There&#x27;s a one-command installation script for Ubuntu&#x2F;Debian&#x2F;macOS.Tech stack: TypeScript monorepo with NestJS API, Next.js dashboard, and a Bun-bundled CLI.I&#x27;m a solo developer building this because I was frustrated with the disconnect between planning tools and actual code execution.Would love feedback on the approach and any features you&#x27;d want to see.

Show HN: Locus – AI agents that ship your code

Transcriptum is an audio and video transcription service powered by WhisperX: speaker diarization, word-level timestamps, 50+ languages, and optional AI analysis (summaries, Q&amp;A, topics, sentiment, action items, fact-checking) via multiple LLM providers (OpenAI, Gemini, DeepSeek).You can upload files or paste a YouTube URL; we download and transcribe. Export as TXT, SRT, VTT, DOCX. Built with NestJS, Next.js, Prisma&#x2F;PostgreSQL; subscriptions are handled with Polar.I built this to have accurate, private transcription without locking into a single vendor, and to combine transcription with analysis in one place. Would love feedback from anyone who transcribes meetings, podcasts, or long-form content.

Show HN: Transcriptum – fast video transcription with speaker labels and summary


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  [![Sponsors on Open Collective](https://opencollective.com/nest/sponsors/badge.svg)](https://opencollective.com/nest#sponsor)

## Description

Nest is a framework for building efficient, scalable [Node.js](http://nodejs.org) server-side applications. It uses modern JavaScript, is built with  [TypeScript](http://www.typescriptlang.org) preserves compatibility with pure JavaScript and combines elements of OOP (Object Oriented Programming), FP (Functional Programming), and FRP (Functional Reactive Programming).

Under the hood, Nest makes use of [Express](https://expressjs.com/), but also, provides compatibility with a wide range of other libraries, like e.g. [Fastify](https://github.com/fastify/fastify), allowing for easy use of the myriad third-party plugins which are available.

## Installation

```js
$ npm install
```

## Getting Started

Setting up a new project is quite simple. With npm installed, you can create a new Nest project with the following commands in your OS terminal:

```js
$ npm i -g @nestjs/cli
$ nest new project-name
```

## Running the app

```js
# development
$ npm run start

# watch mode
$ npm run start:dev

# production mode
$ npm run start:prod
```

## Test

```js
# unit tests
$ npm run test

# e2e tests
$ npm run test:e2e

# test coverage
$ npm run test:cov
```

## Support

Nest is an MIT-licensed open source project. It can grow thanks to the sponsors and support by the amazing backers. If you'd like to join them, please [read more here](https://opencollective.com/nest).

## Stay in touch

- Website - [https://nestjs.com](https://nestjs.com/)
- Twitter - [@nestframework](https://twitter.com/nestframework)

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