MuhammadIrfan Khalid @Muhammadir69003

if you build this business I will pay you a $5k bounty and be your first recurring customer The problem One recurring need across our client work is reliable creator and influencer outreach on Instagram: send personalized first-touch DMs to a vetted list of Instagram profiles, track outcomes, and integrate the workflow into our agent infrastructure. We are looking for a vendor or builder who already has — or can quickly ship — a HeyReach-style product for Instagram DMs: something we can use programmatically without operating the underlying browser automation, sender account management, infrastructure, or maintenance ourselves. The Solution We want to provide: - A list of Instagram profiles to contact - A message or message template - Campaign-level settings, limits, and metadata - Optional follow-up logic - A callback, webhook, or API response with delivery and reply status And we want the product to handle: - Sender account setup and management - Safe sending limits and throttling - Campaign execution - Duplicate prevention - Reporting - Maintenance when Instagram changes platform behavior - Ongoing reliability full spec notion doc below

build this and dm me and/or @maxchehab notion.so/graphed/Reques…

اب انتہائی خطرناک اور تشویشناک حقائق سامنے آ رہے ہیں۔ کچھ جاننے والوں کے مطابق حافظ سعد ریاض کو ایک ایس ایچ او نے ذاتی رنجش کی بنا پر اتنے سنگین الزام میں نامزد کر کے ایف آئی آر دی کہ اس کا القاعدہ سے تعلق ہے۔ یہ ایک ایسا الزام ہے جس کے بعد انسان ساری زندگی مشکوک ہو جاتا ہے۔ جبکہ اطلاعات کے مطابق اس اس کیس میں اصل وجہ ایک سی ٹی ڈی افسر کی @hafizsaadriaz سے اس لئے ذاتی رنجش تھی کیونکہ سعد ایرانی پراکسیز کیخلاف لکھتا تھا۔ اداروں سے اور حکومت سے درخواست ہے کہ ان معاملات کا سختی سے نوٹس لیں اور اگر کوئی سرکاری افسر اس طرح کی حرکات کہ ذاتی رنجش پر لوگوں پر دہشتگردی کے الزام لگا کر اپنے اختیار کا غلط استعمال کر رہا اس کو عبرت کا نشان بنائیں۔ خدارا عام عوام کو پڑھے لکھے لوگوں کو آزاد معاشرے میں آزاد سوچ کے ساتھ جینے دیں سعد کو جینے دو #ReleaseHafizSaadRiaz

Evil websites like Libgen, Z-library, and Sci-Hub had pirated millions of academic books and papers. They've been shut down, and rightly so. We shouldn't use them anyway. We should make billion-dollar academic publishers richer. Anyway, here's how to access these libraries: 🚨DO NOT DO THIS!

If I had to master API design, I’d learn these concepts: 1. What is an API 2. API Architecture Styles 3. REST Principles 4. RESTful Design 5. GraphQL 6. gRPC 7. SOAP 8. Resource Modeling 9. URI Design 10. HTTP Methods (GET, POST, PUT, PATCH, DELETE) 11. Status Codes 12. Request & Response Structure 13. JSON 14. XML 15. Serialization 16. Deserialization 17. Idempotency 18. Statelessness 19. Versioning Strategies 20. URI Versioning 21. Header Versioning 22. Content Negotiation 23. Pagination 24. Filtering 25. Sorting 26. Searching 27. Rate Limiting 28. Throttling 29. API Gateway 30. Load Balancing 31. Caching Strategies 32. Cache-Control Headers 33. ETags 34. Conditional Requests 35. Authentication 36. Authorization 37. API Keys 38. JWT 39. OAuth 2.0 40. OpenID Connect 41. CORS 42. CSRF Protection 43. Input Validation 44. Data Sanitization 45. Error Handling 46. Error Codes & Messages 47. Logging 48. Monitoring 49. Observability 50. Metrics 51. Tracing 52. Documentation 53. OpenAPI Specification 54. Swagger 55. API Contracts 56. Contract Testing 57. Mock Servers 58. API Testing 59. Postman 60. Load Testing 61. Security Best Practices 62. Encryption (HTTPS/TLS) 63. Secrets Management 64. Rate Limit Headers 65. Webhooks 66. Event-Driven APIs 67. Async APIs 68. Streaming APIs 69. WebSockets 70. Server-Sent Events 71. API Lifecycle Management 72. Deprecation Strategies 73. Backward Compatibility 74. Breaking Changes 75. API Governance 76. Naming Conventions 77. Consistency Rules 78. SDK Generation 79. Developer Experience (DX) 80. API Analytics 81. Usage Tracking 82. Monetization 83. API Marketplace 84. Multi-Tenancy 85. Scalability 86. High Availability 87. Fault Tolerance 88. Circuit Breaker 89. Retry Logic 90. Timeout Handling 91. Service Discovery 92. Microservices Integration 93. BFF (Backend for Frontend) 94. Edge APIs 95. CDN Integration 96. Data Transformation 97. Aggregation Layer 98. Orchestration vs Choreography (...and more concepts) === 👋 PS - Want a detailed breakdown of API design best practices? Read right now: → API Design Ebook: codewithdhanian.gumroad.com/l/nbfkk === 💾 Save this for later & RT to help others learn API design. 👤 Follow @e_opore + turn on notifications.

Technical interview question: You need to process a 10GB JSON file. Extract specific fields and transform them. Memory is limited. What’s your approach?

Introducing Pods Hyperspace Pods lets a small group of people - a family, a startup, a few friends, to pool their laptops and desktops into one AI cluster. Everyone installs the CLI, someone creates a pod, shares an invite link, and the machines form a mesh. Models like Qwen 3.5 32B or GLM-5 Turbo that need more memory than any single laptop has get automatically sharded across the group's devices - layers split proportionally, inference pipelined through the ring. From the outside it looks like one OpenAI-compatible API endpoint with a pk_* key that drops straight into your AI tools and products. No configuration beyond pasting the key and changing the base URL. A team of five paying for cloud AI burns $500–2,000 a month on API calls. The same team's existing machines can serve Qwen 3.5 (competitive on SWE-bench) and GLM-5 Turbo (#1 on BrowseComp for tool-calling and web research) for free - the hardware is already on their desks. When a query genuinely needs a frontier model nobody has locally, the pod falls back to cloud at wholesale rates from a shared treasury. But for the daily work - code reviews, refactors, research, drafting - local models handle it and nobody gets billed. And when it is idle, you can rent out your pod on the compute marketplace, with fine-grained permissions for access management. There's no central server involved in inference. Prompts go from your machine to your pod members' machines and back: all of this enabled by the fully peer-to-peer Hyperspace network. Pod state - who's a member, which API keys are valid, how much treasury is left - is replicated across members with consensus, so the whole thing works on a local network. Members behind home routers don't need port forwarding either. The practical setup for most pods is three models covering different jobs: Qwen 3.5 32B for code and reasoning, GLM-5 Turbo for browsing and research, Gemma 4 for fast lightweight tasks. All running on hardware you already own. Pods ship today in Hyperspace v5.19. Model sharding, API keys, treasury, and Raft coordinator are all live. What Makes This Different - No middleman. Your prompts travel from your IDE to your pod members' hardware and back. There is no server in between reading your data. - No vendor lock-in. Pod membership, API keys, and treasury are replicated across your own machines using Raft consensus. If the internet goes down, your local network keeps working. There is no database in someone else's cloud that your pod depends on. - Automatic sharding. You don't configure layer ranges or calculate VRAM budgets. Tell the pod which model you want. It figures out how to split it across whatever hardware is online. - Real NAT traversal. Your friend behind a home router with a dynamic IP? Works. No VPN, no Tailscale, no port forwarding. The nodes handle it. - Free when local. This is the part that matters most. Cloud AI bills scale with usage. Pod inference on local hardware scales with nothing. The marginal cost of your 10,000th prompt is the electricity your laptop was already using. Coming soon: - Pod federation: pods form alliances with other pods. - Marketplace: pods with spare capacity can sell inference to other pods.

New course: Spec-Driven Development with Coding Agents, built in partnership with @jetbrains, and taught by @paulweveritt. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track! deeplearning.ai/short-courses/…

Mr Sharad Agarwal of Air India Engineering Service Limited - a PSU operating under the Ministry of Civil Aviation is harassing its employees and forcing them to work even after resignation and notice period. My relative, an aircraft engineer resigned from the Hyderabad office on 13th January, 2026. He completely served the notice period of 90 days till 12th April, 2026 The resignation was accepted by Hyderabad office HR & GM. And has been pending with Mr. Sharad who is not willing to approve his resignation. And is adamant despite approaching him multiple times. He has to join the other company and is left hanging in a limbo. These are the kind of labour laws in India where employees have no rights and ppl in power play with their careers. @RamMNK & @MoCA_GoI , does civial aviation ministry support this harrassment of employees ?? @LabourMinistry @LabourAP please take action here. Requesting everyone to share this widely to help the guy who is stuck. Any media house that can help cover this story, please reach out in comments or DM.

🚀 I'm starting #50DaysOfAzure! For the next 50 days, I'll break down ONE Azure service daily: ☁️ What it does 🔧 Real-world use cases 💡 Key features 📊 Pricing insights 🏗️ Architecture tips From VMs to Quantum Computing — we're covering it ALL. Follow along & RT to help others learn! 🧵👇 #Azure #Cloud

Most remote job boards show you the same 500 listings everyone else sees. Fortunately, Reddit has thousands of unadvertised roles if you know how to look. Here's how to find them:

عروج بھی اللہ نے دیا اور زوال میں بھی اسکی مرضی تھی : جس حال میں رکھے شکر ہے اس ذات عظیم کا ۔۔۔۔۔ کبھی سینکڑوں لوگ انکے ماتحت کام کرتے تھے اور آج سڑکوں سے لوہا چننے پر مجبور ۔۔ لاکھوں روپے تنخواہ پانے والے ایک انجینئر کی سچی کہانی : 27 سال تک اسٹیل انڈسٹری میں کام کیا ۔ ایک نام تھا اور رتبہ تھا ۔ انکی مرضی کے بغیر فیکٹری میں پتہ نہیں ہلتا تھا لیکن پھر ایک غلطی ہوئی اور سب کچھ ختم ہو گیا ، بیوی بچوں کا پیٹ پالنے کے لیےگزشتہ 3 سال سے اپنی بائیک پر گھر سے نکلتے ہیں ، سڑک پر مقناطیس کے ذریعے لوہے کے چھوٹے چھوٹے ٹکڑے نٹ بولٹ وغیرہ اکٹھا کرتے ہیں ۔ شام تک 10، 12 کلو اکٹھا ہو جائے تو اسے بیچ کر روزی رزق کا بندوبست کر لیتے ہیں ۔۔۔ جب انجینئرنگ میں نوکری کررہے تھے تو بچوں کو اعلیٰ تعلیمی اداروں میں پڑھا رہے تھے لیکن نوکری سے محروم ہو کر بھی بچوں کی تعلیم کا سلسلہ نہیں روکا ، آج 2 بچے چارٹر اکاؤنٹنٹ اور بیٹی ایم بی بی ایس کے فائنل میں ہے ۔ اللہ پر یقین ہے اس نے جو عروج پہلے دیا اس سے بھی بڑھ کر اچھے دن دوبارہ دکھائے گا ۔۔۔ دعا ہے اللہ کریم اس بھائی کی مشکلات آسان فرمائے آمین

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If you want clients without using Upwork, you just need to know where funded startups announce themselves. Here are the platforms you should be checking every single day:

Apply for joinstellar .ai micro1 .ai telusinternational .ai mercor .com crowdgen .com alignerr .com abaka .ai mindrift .com remoexperts / rex .zone welocalize .com terac .com superannotate .com lxt .ai

I was paying for Higgsfield AI. Then I found this repo and cancelled my subscription the same day. Open Higgsfield AI is a self-hosted, MIT licensed cinema studio with 200+ AI models Flux, Midjourney, Sora, Kling, Veo, GPT-4o, SDXL all in one interface that runs on your machine for free. Text to image. Image to image. Text to video. Image to video. Cinema mode with pro camera controls. No subscription. No vendor lock-in. Your data stays local. 2.5K stars. MIT License. 100% Open Source. github.com/Anil-matcha/Op…

If you’re hunting for a remote job, you just need to figure out how Reddit works, and you’ll never be unemployed for a long time. Here’s a list of subreddits you should bookmark right now:

🚨 BREAKING: NVIDIA just removed the biggest friction point in Voice AI They open-sourced PersonaPlex 7B, a real-time conversational model. It listens and speaks simultaneously to handle natural interruptions and overlaps. 100% Open Source.

Meet a game-changing AI that understands both text AND financial data. This multimodal model can analyze documents, charts, and numbers together. It's like giving financial analysts superhuman comprehension abilities.

R.I.P. LinkedIn in 2026. R.I.P. Upwork in 2026. R.I.P. Indeed in 2026. I spent 6 years applying. Just 1 interview. My friend spent 2 hours on niche platforms. He got 4 remote job offers instantly. Here are 30 platforms that actually help you get hired (with details) 🧵👇

AI users often focus on the wrong thing. The goal isn’t to reach a solution as fast as possible. It’s to arrive at the *best* solution. What AI does well is help you experiment faster, explore more possibilities, and refine the problem and solution space. A lot of AI use goes wrong when people optimize for speed or quantity. Optimize for quality instead, and AI becomes an incredible tool.