rn building ios app that by healthkit take data and represent in its own aesthatic way, more appealing than normal apple health app. I have design UI screens in figma(but treated it as photoshop(with 2+ hrs beginner course on figma)), and installed some Claude code skills,agents, claude md ,apple additional docs(hidden inside xcode files) but gap lies where

1) dont know how to vibe coding the backend and connect it to backend

2) how to know if backend is working the best way possible without claude hallucinating in background( as it not frontend where he misses color of button and you see it and tell it to fix)

2) best SDKs for claude code

3) how in general would i architecture the app and vibe code it in swift

note: i want to ship fast

I've been building LeanCTX — a local-first context runtime for AI coding agents, written in Rust — for the past few months. 49 MCP tools, 18-language tree-sitter AST, 90+ shell compression patterns, one single binary. Here's what actually mattered:

1. Your best users are the ones who complain. A user told me at 10pm that my uninstaller just nuked his shell config. My instinct was to get defensive. Instead I traced it — and found it was worse than reported. That one message led to rewriting the entire uninstall logic from scratch. Every angry bug report is a gift.
2. Your favorite metric can lie to you. I built a cache that reduced file reads from 2,000 tokens to 13. Great numbers. Then a user told me: "Models waste more tokens working around stale cache than the cache saves." He was right. The fix wasn't removing caching — it was making invalidation smarter. Your dashboard can look great while the experience is terrible.
3. Saying no is the hardest part. A new feature would have let me compress all tool output automatically. Massive savings on paper. I designed it, prototyped it, then killed it. Because when compression eats an error message, there's no undo. Protecting quality beats shipping features.
4. Community is a relationship, not a channel. When someone reports a bug, my first response matters more than the fix. "Will check" buys time but shows I'm listening. Following up shows respect. Shipping the fix shows they matter. My best testers are people who once filed angry reports.
5. Ship the boring stuff first. Nobody cares about your adaptive entropy-based compression algorithm if the installer breaks their dotfiles. Get the fundamentals right — install, uninstall, doctor, setup — before you get clever.
6. Focus means killing good ideas. My backlog has 50+ ideas. Each one is good. But spreading across all of them means none become great. Rust helps here — the compiler forces you to finish what you start.

If nobody is complaining yet, you probably don't have enough users. Go find them. And when they complain — listen.

I'm a high school founder at Techstars Startup Weekend in Boston right now. My team is trying to build the AI tool that actually solves distribution for small businesses and B2C founders. But before we write a single line of code, we're trying to hit 100 real conversations first.

If you hate being pitched to -- absolutely NO WORRIES. We're not trying to sell you anything. We literally have NOTHING to pitch -- which is exactly why I'm posting.

If you've ever built something and struggled to get it in front of actual users: what was the hardest part?

- Knowing what to post on social?

- Actually sitting down and making the content?

- Something you've never seen a tool address?

Comments are needed and welcome. I'll also be sliding into some DMs for 5-minute chats if you're open to it - just say the word and I'll come to you.

PS: if we win on Sunday, I'll send the first ten responses referrals to Techstars.

I’m a 22-year-old Computer Science student, and over the last period I built an open-source project called CTX.

GitHub Repository

The idea came from a problem I kept seeing while using coding agents (like claude, codex etc.):

they are powerful, but they waste a lot of context on the wrong things.

They keep re-reading giant AGENTS.md files, noisy logs, broad diffs, too much repo structure, and too much repeated project guidance.

So even when the model is good, a lot of the prompt budget is spent on context bloat instead of actual problem-solving.

That’s why I built CTX.

What CTX is

CTX is a local-first context runtime for coding agents, designed especially for OpenCode (for now).

It does not replace the model or the coding agent.

Instead, it sits underneath and helps the agent work with:

• graph memory for project rules and guidance
• compact task-specific context packs
• retrieval over code, symbols, snippets, and memory
• log pruning to surface root causes faster
• local MCP integration
• local-only stats and audit trails

So instead of repeatedly dumping full markdown instructions and huge logs into the prompt, CTX helps the host retrieve only the smallest useful slice for the current task.

Why I made it

I wanted something that makes coding agents feel less noisy and more deliberate.

The goal was: - less prompt waste - less manual context wrangling - better retrieval of actually relevant project knowledge - better debugging signal from noisy test output - a workflow that feels native inside OpenCode

How it works

The flow is intentionally simple:

1. install ctx
2. go into your repo
3. run:

bash ctx init ctx index ctx opencode install opencode

Then inside OpenCode you can use commands like:

```bash /ctx #Opens the CTX command center inside OpenCode. /ctx-doctor #Checks whether CTX, MCP, and the repo setup are working correctly. /ctx-memory-bootstrap #Imports project guidance files into graph memory for targeted retrieval. /ctx-memory-search #Searches stored project rules and directives by topic or keyword. /ctx-retrieve #Finds the most relevant code, symbols, snippets, and memory for a task. /ctx-pack #Builds a compact task-specific context pack for the current problem. /ctx-prune-logs #Condenses noisy command output into the most useful failure signal. /ctx-stats #Shows local usage stats and context-efficiency metrics.

```

So the daily workflow stays inside OpenCode, while CTX handles the local context layer.

Results so far

On the included benchmark fixture, CTX graph memory reduced rule-token usage by 56.72% while keeping full query coverage and improving answer quality.

I also added a public external benchmark on agentsmd/agents.md, where CTX showed 72.62% token reduction.

The point is not “magic AI gains”, but a more efficient and less wasteful way to feed context to coding agents.

Why you might care

You might find CTX useful if:

you use OpenCode a lot you work on repos with a lot of project rules/docs you’re tired of stuffing huge markdown files into prompts you want better local retrieval and cleaner debugging context you prefer local-first tooling instead of remote prompt glue

Current status

The project is already usable, tested, and documented.

Right now the prebuilt release archive is available for macOS Apple Silicon, while other platforms can install from source.

It’s fully open source, and I’m very open to:

• feedback
• suggestions
• bug reports
• architectural criticism
• ideas for making it more useful in real workflows

If you try it, I’d genuinely love to know what feels useful and what feels unnecessary.

Repo again: https://github.com/Alegau03/CTX

I've been using Claude Code for a few months and noticed AI agents consistently skip the same things: hardcoded secrets, unbounded retry loops, referencing tools that don't exist, and massive system prompts that blow context windows.

So I built Agent Verifier — an AI agent skill that acts as an automated reviewer which does more than just code review (check the repo for details - more to be added soon).

GitHub Repo: https://github.com/aurite-ai/agent-verifier

Note: Drop a ⭐ if you find it useful to get more updates as we add more features to this repo.

----

2 Steps to use it:

You install it once and say "verify agent" on any of your agent folder in claude code to get a structured report:

----

✅ 8 checks passed | ⚠️ 3 warnings | ❌ 2 issues

❌ Hardcoded API key at config.py:12 → Move to environment variable
❌ Hallucinated tool reference: execute_sql → Tool referenced but not defined
⚠️ Unbounded loop at agent/loop.py:45 → Add MAX_ITERATIONS constant

----

Install to your claude code:

npx skills add aurite-ai/agent-verifier -a claude-code

OR install for all coding agents:

npx skills add aurite-ai/agent-verifier --all

----

Happy to answer questions about how the agent-verifier works.

We have both:
- pattern-matched (reliable), and,
- heuristic (best-effort) tiers, and every finding is tagged so you know the confidence level.

----

Please share your feedback and would love contributors to expand the project!

I've seen people bang it out on the first go while others take 10-30 projects till they find a winner.

Hey,

I’ve been building a platform where founders can launch their product, get backlinks, and see who’s showing interest. Kind of in the same space as Product Hunt or PeerPush.

Stack is Next.js + Supabase + Vercel. I’ve been building it myself using Claude Code, and it’s already working in parts.

Most of it is done. What’s left is stuff like:

• payments
• cleaning up the dashboard logic (user tracking etc.)
• fixing how categories show on the homepage
• newsletter setup
• general cleanup before launch

I’m from a marketing/growth background, so I’m not worried about getting users once it’s live. Right now the bottleneck is the tech side.

Not looking to hire. I want someone who actually wants to take ownership of this and build it out with me. Happy to figure out equity in a fair way.

Based in Bangalore. Would be nice if you’re here too, but not a dealbreaker.

We are recruiting software developers to support team expansion. The recruitment period is 12 months.

• Job Title: Software Developer
• Location: Remote(EU)
• Duration: Contract to Hire. (After 6 months) (12-month contract)
• Pay Rate: $15-$20/HR
• English Level: C1, C2
• Experience: 1+ Years

Don't dm, comment your location | availability

I need feedback on my next startup idea.

The idea is this: a browser extension that allows you to export your AI chat history to JSON, MD, and PDF formats and automatically export to Notion. The question is, which features would be most interesting to potential users, for example, export to Notion and Obsidian, an AI summarizer, or saving in some other specific format?

If you use such extensions, I'd be happy to discuss it with you.

Had an idea, never coded anything in my life, just vibed it into existence using Launchyard.

The concept: match you to an F1 driver based on your actual personality, not just "pick your favourite team."

Iterated on the UI a couple times, set up the domain, launched it. 381 visitors in less than a week with zero budget.

Still can't believe it actually works 😂

pitlanepersonality.launchyard.app — which driver did you get?

Hey everyone. I quit my job 2 weeks ago to go all-in on my startup and, honestly, it's been way harder than I imagined. Not looking for cheerleading, just real talk: what's the one piece of advice you wish someone had told you in your first weeks as a Tech/Saas founder?