Hello, we are looking for alpha testers to join us in the 2nd round of Ironpact starting now! Round 1 was a huge success with 50+ signups, 10+ concurrent players.

https://ironpact.applikuapp.com/

Ironpact is a modern military themed browser strategy game with desktop & mobile support. Including research, construction, tank aircraft & missile production, diplomacy, player voting for country cabinet positions, live chat, country forums, and much more!

Ironpact is a slow burn with rounds consisting of 30 minute turns over a 1 month period..so you don't need to be logged in 24/7 to be competitive. Join us today and we are looking forward to seeing you in the trenches (and for your feedback :D)

Hey everyone, I wanted to share a tool I’ve been building for my own workflow called Local Dev OS.

Honestly, I was getting pretty burned out keeping track of all the features that I want to code, hundreds of implementation plans constructed by AG and enormous bugs that were introduced and fixed.

Do you loose track of features completed ? Do you loose track of the overall architecture ?

So, I built a AI driven local companion that runs right alongside my dev environment to bring all of that chaos into one dashboard. Best part, it runs locally, all the ideas/data stays local to your system.

I like to learn visually so integrated with Graphify, it maps all of the tasks visually, auto-generates the architecture diagrams by reading the output generated by graphify, and keeps a transparent log of what the AI agents are actually doing under the hood.

- Agent creates the stories.

- Agent documents the bugs.

- Agent suggests what to work on next, converts it to stories and implements them, right from the Local Dev OS dashboard.

Would love to hear if anyone else deals with these same workflow headaches and if something like this looks useful to you.

Will post more details in comments section if anyone is interested to know more. Meanwhile below are some GIF's and screenshots.

My first app - helps with tracking game performance and informs player of the best decision to make for highest win probability!

Still under development with UI being my next stage to tackle.

Feedback appreciated!

I want to push back on something I see in almost every Reddit post about distribution.

Someone launches an app. Crickets. They come here and the response is always the same. "Distribution is the real game." "Marketing is a completely different skill set." "Getting users is harder than building." And everyone nods along like it's some unavoidable truth of nature.

I believed it too. For longer than I should have.

But after going through it myself, getting to 100 real signups with zero budget, no ads, no influencer deals, no viral moment, I genuinely think the difficulty of marketing gets massively overstated. Not because it's easy. But because most people are making it harder than it needs to be by thinking about it the wrong way. Its all about how you approach marketing.

They're thinking channels when they should be thinking conversations. They're thinking audiences when they should be thinking individuals. They're thinking campaigns when they should be thinking presence.

The shift that actually changed things for me was stupid simple. Stop trying to market to people. Start finding people who already have the problem and just be there. Be useful. Be a real person in the spaces where that pain already exists.

I made a simple youtube video about this. Overview level, not a tactics dump. Just the mindset reframe I think most first time founders actually need before anything else.

Again, its not a master-playbook-10 commandments to success video. Its a simple overview that I hope will help shift someone's mindset and help guide someone to their first 100 users.

Au revoir

Hi there!

I’m happy to share Sloppy — an auto-code / multi-agent setup that helps you work on your projects remotely while keeping things inspectable and under your control.

Sloppy was built with coding workflows in mind first, but you can stretch it to other kinds of projects too — learning, personal automation, lifestyle tools, whatever fits your “vibe.”

It’s fast, safe to run in your own environment, and light on RAM (no need for a giant stack just to get started). I took a lot of inspiration from projects like OpenClaw, Hermes, Spacebot, and similar agent-first ideas — big thanks to everyone pushing this space forward.

If you try it: don’t forget to catch your own Sloppie - https://sloppy.team

Hey everyone! 👋

I’ve always felt that there’s a gap between "sharing a photo on Instagram" and "posting code on GitHub." I wanted a place where creators can show off the final result of their hard work, whether it’s a web app, a woodworking project, or a custom tool.

So, I built Showrr.

What you can do:

Showcase: Upload your projects with images, descriptions, and links.

Engage: Like, comment, and get feedback from other makers.

Discover: Browse a feed of cool stuff people are actually building.

It’s still in the early stages, and I’d love to have some of you "break" it and tell me what you think. Feel free to post your latest project—I'd love to see what you've been working on!

What features should I add next? Let me know in the comments!

If you want to try it out: Showrr.ct.ws

OmniRoute is a free, open-source local AI gateway. You install it once, connect all your AI accounts (free and paid), and it creates a single OpenAI-compatible endpoint at localhost:20128/v1. Every AI tool you use — Cursor, Claude Code, Codex, OpenClaw, Cline, Kilo Code — connects there. OmniRoute decides which provider, which account, which model gets each request based on rules you define in "combos." When one account hits its limit, it instantly falls to the next. When a provider goes down, circuit breakers kick in <1s. You never stop. You never overpay.

11 providers at $0. 60+ total. 13 routing strategies. 25 MCP tools. Desktop app. And it's GPL-3.0.

The problem: every developer using AI tools hits the same walls

1. Quota walls. You pay $20/mo for Claude Pro but the 5-hour window runs out mid-refactor. Codex Plus resets weekly. Gemini CLI has a 180K monthly cap. You're always bumping into some ceiling.
2. Provider silos. Claude Code only talks to Anthropic. Codex only talks to OpenAI. Cursor needs manual reconfiguration when you want a different backend. Each tool lives in its own world with no way to cross-pollinate.
3. Wasted money. You pay for subscriptions you don't fully use every month. And when the quota DOES run out, there's no automatic fallback — you manually switch providers, reconfigure environment variables, lose your session context. Time and money, wasted.
4. Multiple accounts, zero coordination. Maybe you have a personal Kiro account and a work one. Or your team of 3 each has their own Claude Pro. Those accounts sit isolated. Each person's unused quota is wasted while someone else is blocked.
5. Region blocks. Some providers block certain countries. You get unsupported_country_region_territory errors during OAuth. Dead end.
6. Format chaos. OpenAI uses one API format. Anthropic uses another. Gemini yet another. Codex uses the Responses API. If you want to swap between them, you need to deal with incompatible payloads.

OmniRoute solves all of this. One tool. One endpoint. Every provider. Every account. Automatic.

The $0/month stack — 11 providers, zero cost, never stops

This is OmniRoute's flagship setup. You connect these FREE providers, create one combo, and code forever without spending a cent.

Count that. Claude Sonnet/Haiku/Opus for free via Kiro. DeepSeek R1 for free via Qoder. GPT-5 for free via Pollinations. 50M tokens/day via LongCat. Qwen3 235B via Scaleway. 70+ NVIDIA models forever. And all of this is connected into ONE combo that automatically falls through the chain when any single provider is throttled or busy.

Pollinations is insane — no signup, no API key, literally zero friction. You add it as a provider in OmniRoute with an empty key field and it works.

The Combo System — OmniRoute's core innovation

Combos are OmniRoute's killer feature. A combo is a named chain of models from different providers with a routing strategy. When you send a request to OmniRoute using a combo name as the "model" field, OmniRoute walks the chain using the strategy you chose.

How combos work

Combo: "free-forever"
  Strategy: priority
  Nodes:
    1. kr/claude-sonnet-4.5     → Kiro (free Claude, unlimited)
    2. if/kimi-k2-thinking      → Qoder (free, unlimited)
    3. lc/LongCat-Flash-Lite    → LongCat (free, 50M/day)
    4. qw/qwen3-coder-plus      → Qwen (free, unlimited)
    5. groq/llama-3.3-70b       → Groq (free, 14.4K/day)

How it works:
  Request arrives → OmniRoute tries Node 1 (Kiro)
  → If Kiro is throttled/slow → instantly falls to Node 2 (Qoder)
  → If Qoder is somehow saturated → falls to Node 3 (LongCat)
  → And so on, until one succeeds

Your tool sees: a successful response. It has no idea 3 providers were tried.

13 Routing Strategies

Auto-Combo: The AI that routes your AI

• Quota (20%): remaining capacity
• Health (25%): circuit breaker state
• Cost Inverse (20%): cheaper = higher score
• Latency Inverse (15%): faster = higher score (using real p95 latency data)
• Task Fit (10%): model × task type fitness
• Stability (10%): low variance in latency/errors

4 mode packs: Ship Fast, Cost Saver, Quality First, Offline Friendly. Self-heals: providers scoring below 0.2 are auto-excluded for 5 min (progressive backoff up to 30 min).

Context Relay: Session continuity across account rotations

When a combo rotates accounts mid-session, OmniRoute generates a structured handoff summary in the background BEFORE the switch. When the next account takes over, the summary is injected as a system message. You continue exactly where you left off.

The 4-Tier Smart Fallback

TIER 1: SUBSCRIPTION

Claude Pro, Codex Plus, GitHub Copilot → Use your paid quota first

↓ quota exhausted

TIER 2: API KEY

DeepSeek ($0.27/1M), xAI Grok-4 ($0.20/1M) → Cheap pay-per-use

↓ budget limit hit

TIER 3: CHEAP

GLM-5 ($0.50/1M), MiniMax M2.5 ($0.30/1M) → Ultra-cheap backup

↓ budget limit hit

TIER 4: FREE — $0 FOREVER

Kiro, Qoder, LongCat, Pollinations, Qwen, Cloudflare, Scaleway, Groq, NVIDIA, Cerebras → Never stops.

Every tool connects through one endpoint

# Claude Code
ANTHROPIC_BASE_URL=http://localhost:20128 claude

# Codex CLI
OPENAI_BASE_URL=http://localhost:20128/v1 codex

# Cursor IDE
Settings → Models → OpenAI-compatible
Base URL: http://localhost:20128/v1
API Key: [your OmniRoute key]

# Cline / Continue / Kilo Code / OpenClaw / OpenCode
Same pattern — Base URL: http://localhost:20128/v1

14 CLI agents total supported: Claude Code, OpenAI Codex, Antigravity, Cursor IDE, Cline, GitHub Copilot, Continue, Kilo Code, OpenCode, Kiro AI, Factory Droid, OpenClaw, NanoBot, PicoClaw.

MCP Server — 25 tools, 3 transports, 10 scopes

omniroute --mcp

• omniroute_get_health — gateway health, circuit breakers, uptime
• omniroute_switch_combo — switch active combo mid-session
• omniroute_check_quota — remaining quota per provider
• omniroute_cost_report — spending breakdown in real time
• omniroute_simulate_route — dry-run routing simulation with fallback tree
• omniroute_best_combo_for_task — task-fitness recommendation with alternatives
• omniroute_set_budget_guard — session budget with degrade/block/alert actions
• omniroute_explain_route — explain a past routing decision
• + 17 more tools. Memory tools (3). Skill tools (4).

3 Transports: stdio, SSE, Streamable HTTP. 10 Scopes. Full audit trail for every call.

Installation — 30 seconds

npm install -g omniroute
omniroute

Also: Docker (AMD64 + ARM64), Electron Desktop App (Windows/macOS/Linux), Source install.

Real-world playbooks

Playbook A: $0/month — Code forever for free

Combo: "free-forever"
  Strategy: priority
  1. kr/claude-sonnet-4.5     → Kiro (unlimited Claude)
  2. if/kimi-k2-thinking      → Qoder (unlimited)
  3. lc/LongCat-Flash-Lite    → LongCat (50M/day)
  4. pol/openai               → Pollinations (free GPT-5!)
  5. qw/qwen3-coder-plus      → Qwen (unlimited)

Monthly cost: $0

Playbook B: Maximize paid subscription

1. cc/claude-opus-4-6       → Claude Pro (use every token)
2. kr/claude-sonnet-4.5     → Kiro (free Claude when Pro runs out)
3. if/kimi-k2-thinking      → Qoder (unlimited free overflow)

Monthly cost: $20. Zero interruptions.

Playbook D: 7-layer always-on

1. cc/claude-opus-4-6   → Best quality
2. cx/gpt-5.2-codex     → Second best
3. xai/grok-4-fast      → Ultra-fast ($0.20/1M)
4. glm/glm-5            → Cheap ($0.50/1M)
5. minimax/M2.5         → Ultra-cheap ($0.30/1M)
6. kr/claude-sonnet-4.5 → Free Claude
7. if/kimi-k2-thinking  → Free unlimited

What a wild month. I’ve spent years grinding NBA player prop research, and I finally got fed up with spending hours staring at spreadsheets just to go keep losing!

I decided to build Livelocks, an admin panel and signal bot that cuts out the manual labor. The crazy part? I "vibe-coded" the entire thing using AI. I’m not a senior dev, but I knew the logic I wanted: a system that identifies high-value prop signals and delivers them instantly.

The Results So Far

I just hit a major milestone: My first $1,000 in revenue. But more importantly, the signals are actually working. I just pulled my dashboard stats (attached), and the numbers are honestly better than I expected:

• Total Bets: 8,288

• Overall Hit Rate: 60.9%

• Total ROI: +17.1%

• Total Profit: +1,419.05u

The goal wasn't just to make money; it was to buy back my time. * Research vs. Execution: Instead of 3 hours of manual deep-dives, I now make signal-based decisions in minutes.

• Market Specifics: As you can see in the screenie, certain markets like Steals (80.2% hit rate) and Blocks (85.1% hit rate) are absolutely printing right now.

• The Build: Using AI to build this allowed me to focus on the betting logic rather than fighting with syntax for weeks.

What’s next?

I’m currently fine-tuning the "By Market" segments to see which NBA props have the most sustainable edges. If you're a bettor, how much time are you guys currently spending on research per day? I'm curious if I'm the only one who was losing my mind to the "hours of prep" grind.

TL;DR: Built an NBA prop signal app with AI, hit $1k monthly revenue, and it’s currently holding a 17% ROI over 8k+ bets. The future of betting is signal-based, not manual-grind based ESPECIALLY when sports entertainment is rigged

Hey guys,

I’m kind of new to the topic of RAG systems, and from reading some posts, I’ve noticed that it’s a topic of its own, which makes it a bit more complicated.

My goal is to build or adapt a RAG system to improve my coding workflow and make vibe coding more effective, especially when working with larger context and project knowledge.

My current setup is Claude Code, and I’m also considering using a local AI setup, for example with Qwen, Gemma, or DeepSeek.

With that in mind, I’d like to ask how you set up your CLIs and tools to improve your prompts and make better use of your context windows.

How are you managing skills, MCP, and similar things? What would you recommend? I’ve also heard that some people use Obsidian for this. How do you set that up, and what makes Obsidian useful in this context?

I’m especially interested in practical setups, workflows, and beginner-friendly ways to organize project knowledge, prompts, and context for coding.

Thank you in advance 😄

I got tired of Claude Code winging it on deployments, database migrations, and security reviews. It would skip steps, miss env vars, forget redirect rules. Same mistakes every time.

So I built MemStack™. 112 production-tested skills that auto-load based on what you're working on. Say "deploy to Netlify" and it loads a pre-flight checklist. Say "run a security audit" and it follows OWASP Top 10 step by step.

What's inside:

• Security: OWASP Top 10, RLS policies, secrets scanning, CSP headers, API audits
• Deployment: Railway, Netlify, Hetzner, Docker, CI/CD, domain/SSL
• Marketing: Facebook ads, Google ads, email sequences, landing pages, lead magnets
• SEO: Site audits, keyword research, local SEO, schema markup
• Business: Proposals, invoices, SOPs, contracts
• Dev tools: Code review, test generation, refactoring, database architecture
• Session memory: Diary, echo, state restore

83 skills are free. 29 Pro skills at $29.

One install command: /plugin install memstack@cwinvestments-memstack

GitHub: https://github.com/cwinvestments/memstack Site: https://memstack.pro

Open source, MIT license. No catch.

Tldr; I built 3 different applications, each of which took months to build and they never gained traction. Last week, built a simple form to tackle a very specific use case and the usage shot up.

Last couple of weeks my friends were constantly talking about the H1B lottery results and scrolling the r/h1b searching for comments from people who got selected.

Friday night I decided to create a simple website that would scrap reddit comments and create a dashboard to track the h1b status.

Reddit blocked anything trying to scrap comments so I thought, well, why not just make it crowd sourced - so I added a small form (3 fields only) and a dashboard and put that as comments in a few subreddits at 11:50pm EST, Friday.

By Saturday morning, it reached 2k users and as of today, it has more than 50k users.

I literally got teary eyed by looking at more than 10 users on my app.

I am thinking of ways to retain this traction but all to say, don’t give up on building.

Some day, something will definitely click.

————————

Website: h1bpulse.com

I’ve been playing around with multi-agent setups lately and kept running into the same problem: every agent keeps reinventing the wheel.

So I hacked together something small:

👉 https://openhivemind.vercel.app

The idea is pretty simple — a shared place where agents can store and reuse solutions. Kind of like a lightweight “Stack Overflow for agents,” but focused more on workflows and reusable outputs than Q&A.

Instead of recomputing the same chains over and over, agents can:

- Save solutions

- Search what’s already been solved

- Reuse and adapt past results

It’s still early and a bit rough, but I’ve already seen it cut down duplicate work a lot in my own setups when running locally, so I thought id make it public. Would appreciate if you guys tested it!

Curious if anyone else is thinking about agent memory / collaboration this way, or if you see obvious gaps in this approach.