The best code creates impact only when it reaches users 😵‍💫 If you want to understand what happens after the code is written this session is for you! Learn how modern engineering teams build deploy monitor and scale applications using DevOps and Kubernetes. Featuring Manish Kumar 📅 11 June 2026 ⏰ 7 PM IST Register NOW👇 __geeksforgeeks.org/meet/ship-… . . . . . #DevOps #GitPush #Kubernetes #docker #placements

Current structure for my VPS and summarized below This has helped immensely with a variety of projects. Would explore it with either codex or claude code. Then install either on your VPS. I have both. Which can work on your phone, desktop, laptop etc. and means you have access to the same virtual machine wherever. Every project is now connected to my overall knowledge source that constantly grows and improves. With research that can be done overnight if you set it up correctly. This is the ingest process. It also include my AI council which I've posted about before as I have my openclaw also on it that is connected to Codex. Sky's the limit I've been using @Vultr . Will include a link that will will get you $250 in credits vultr.com/?ref=9905573-9J AI VPS Knowledge System Blueprint This VPS is set up so AI coding agents do not rely on chat history as memory. Instead, they use a Git-backed knowledge wiki plus small agent-specific memory files. Core Idea There are two memory layers: 1. Agent instructions and session memory - Global behavior rules for each AI agent. - A current handoff file for “resume here” context. - A small persistent memory index for durable gotchas. 2. Knowledge wiki - A private Git repo that stores project facts, hypotheses, rules, decisions, raw research, changelogs, and wiki articles. - This is the source of truth. Recommended Folder Layout ~/knowledge/ CLAUDE.md # operating manual for agents using the wiki INDEX.md # list of domains/projects CHANGELOG.md # append-only activity log decisions/ # dated decision journal quality/ # quality gates/checklists syntheses/ # larger cross-topic analyses tools/ # docs for local tools/scripts meta/ sources-of-truth.md # which file wins when facts conflict project-a/ knowledge.md # confirmed durable facts hypotheses.md # unconfirmed patterns to test rules.md # proven default rules articles/ # wiki-style explanations raw/ # immutable source material project-b/ knowledge.md hypotheses.md rules.md articles/ raw/ Agent Startup Routine At the start of meaningful work, the agent reads: ~/knowledge/CLAUDE.md ~/knowledge/INDEX.md ~/knowledge/CHANGELOG.md ~/knowledge/{project}/rules.md ~/knowledge/{project}/knowledge.md ~/knowledge/{project}/hypotheses.md If resuming prior work, it also reads: ~/.agent/HANDOFF.md Knowledge Rules Use these rules to prevent drift: - raw/ is the immutable source layer. - knowledge.md stores confirmed facts. - hypotheses.md stores plausible but unconfirmed patterns. - rules.md stores things agents should do by default. - decisions/ stores choices that affect future work. - CHANGELOG.md records what happened. - Existing knowledge files should be append-only unless a specific section is being updated. - If two files conflict, the source-of-truth map decides which one wins. Ingest Flow External info should not go straight into rules. It should move through this pipeline: source document / research / transcript -> project/raw/ -> compile/extract -> knowledge.md or hypotheses.md -> rules.md only after repeated confirmation Sync Flow The wiki should be a private Git repo: ~/knowledge/ -> commit -> push to private GitHub/GitLab repo -> other machines pull from that repo Optional compatibility mirror: canonical knowledge repo -> mirror repo -> desktop/laptop/sandbox pulls mirror Automation To Add Useful scripts/hooks: session-end hook # auto-commit and push knowledge changes daily compile cron # compile new raw files sync health check # alerts if pushes or pulls are stale backup script # encrypted offsite backups secret guard # blocks agents from reading credentials Security Rules Never put these in the knowledge repo: .env files SSH keys API keys OAuth tokens cloud credentials database passwords backup passphrases private auth JSON files Use placeholders in docs: <server-user> <your-domain> <github-user> <project-name> <service-name> <backup-bucket> <secret-store> Shareable Diagram flowchart TD User[User] --> Agent[AI Agent Session] subgraph AgentMemory[Agent Memory Layer] GlobalRules[Global Instructions] Handoff[Current Handoff] SmallMemory[Persistent Agent Memory] end Agent --> GlobalRules Agent --> Handoff Agent --> SmallMemory subgraph KnowledgeWiki[Private Git-Backed Knowledge Wiki] Manual[CLAUDE.md / Operating Manual] Index[INDEX.md] Changelog[CHANGELOG.md] Rules[project/rules.md] Facts[project/knowledge.md] Hypotheses[project/hypotheses.md] Articles[project/articles/] Raw[project/raw/] Decisions[decisions/] Quality[quality/] end Agent --> Manual Agent --> Index Agent --> Changelog Agent --> Rules Agent --> Facts Agent --> Hypotheses Agent --> Quality Agent --> Work[Code / Research / Operations Work] Work --> NewLearning[New Facts, Decisions, or Patterns] NewLearning --> Changelog NewLearning --> Facts NewLearning --> Hypotheses NewLearning --> Articles NewLearning --> Decisions subgraph IngestPipeline[Ingest Pipeline] Source[External Source] Ingest[Ingest Script] Compile[Compile / Extract Script] end Source --> Ingest Ingest --> Raw Raw --> Compile Compile --> Facts Compile --> Hypotheses subgraph Automation[Automation Layer] StopHook[Session-End Hook] AutoCompile[Daily Auto-Compile] GitPush[Verified Git Push] Backups[Encrypted Offsite Backup] HealthChecks[Sync / Cron Health Checks] end Agent --> StopHook StopHook --> GitPush AutoCompile --> Compile KnowledgeWiki --> GitPush KnowledgeWiki --> Backups GitPush --> RemoteRepo[(Private Git Repo)] subgraph OtherMachines[Other Machines / Sandboxed Agents] Laptop[Laptop / Desktop Clone] Sandbox[Sandboxed Agent] SyncScript[Sync Script] IngestEndpoint[Private Ingest Endpoint] end Sandbox --> SyncScript SyncScript --> IngestEndpoint IngestEndpoint --> Raw Short Version The system is a private wiki for AI agents. Agents read it before work, update it after work, file raw sources into raw/, compile them into facts or hypotheses, and promote only proven patterns into rules. Git, hooks, cron jobs, and backups keep the whole thing synced and durable

Day 52 & 53 of code till internship: > clg assignments >Build a CLI called gitpush that lets you add, commit, and push your code with a single command instead of manually running multiple Git commands every time. try it : npmjs.com/package/gitpushx

Reached out to authorities and some dm’ed me. No one is paying for your ideation stage without you shipping anything. Your investors wants to see the stage you’re in before they commit to your gitPush. Build and start scaling and see more users afterwards.

me when i notice claude code is running a rm -rf on sum random files: cd..gitadd.gitcommit-m"latest"gitpush

Two devs, one GitHub account, both hitting git push 😅 Chaos ensues: overwritten code, merge conflicts, broken builds. Branch. Pull. Review. Don’t repaint the same wall. 🚀 #GitHub #GitPush #MergeConflict #DevLife #PitrixTechnologies

Gitpush gitpull 😮‍💨

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GitPush中に何も操作出来なくなった完全フリーズWindowsくん。ブチ切れ強制シャットダウン。

yes, should be posted with our gitpush but we made one for speeding up our testing

わしもやることをやる(ง ˙-˙ )ง とりあえず今日のデイリーをこなしてgitの構成組んで設計書テンプレート配置してgitpushまでが今日の目標(ง ˙-˙ )ง

Day21 11/24 バージョン管理について① git　変更履歴（箇所、作業者）を記録すること ●Githubに保存する手順 1 Githubに新しいリポジトリを作る 2 エクスプローラーで作成したファイルの保存フォルダを開き、Githubにコピーするファイルを選択 3 GithubのAddfile－Uploadfilesにドラッグ＆ドロップで完了 ●Githubから戻す手順　*1 1 GithubのCode－DownloadZIPからZipフォルダをダウンロード ●GithubDesktop 1 Github上に空のリポジトリを作る　←gitclone 2 空のリポジトリをＰＣにダウンロードする　*1 3 空のリポジトリにHTMLやCSSのファイルを保存する 4 保存したファイルはGithubに連携できる　commitしてpush 5 GithubからＰＣに戻せる　pull　＊複数台での作業時の差分確認等 (git)commit　変更記録の保存　必要な記録を残す GitPush　Githubに戻すこと GitAdd　どのファイル、変更履歴を保存するか選ぶ #sunabaco　#すなばこ2025冬

Just fixed the biggest pain in the ass, guys. Finally I can sleep peacefully. My overlay app was freezing all the time—now it's responsive for life! Phew... #buildinpublic @auratext #gitpush #commit #overlaydontfreezeanymore #goodsleep

最近、GitPushもAIに頼むほどだらけてまして。。。。 考えてみたら『GitPushお願い』って頼むよりGitPushって打ったほうが文字数短いし早いじゃん!って 今更気づくもうボケジジイです

🚀 New: We’ve just launched Shuttle’s @github Integration Code where you always do. Deploy where it’s fastest. ✅ Connect your repo ✅ Deploy instantly from a Shuttle-ready repo or template ✅ Or auto-deploy on #GitPush when you update your code Shuttle turns your GitHub repo into a deployment pipeline. Connect. Push. Deploy. ⚡ 👉 Link below P.S. We’d love to see what you build - tag us with your first deploy 👇

your wall tile's gitpush map is lovely

Sunucu paneli önerisi istemiştim geçen haftalarda ve Dokploy ile Coolify arasında kalmıştım. Vercel CEO'su da ağır saçmalayınca alternatif arayanlar için naçizane deneyimlerimi uzunca yazayım. Bir Türk girişimcinin harika panelinden de bahsedeceğim. Özetle: Cloudpanel kullanıyordum ama docker destekli ve hızlı deploy yapabileceğim panel arayışım vardı. ✅Dokploy: Tercihim Dokploy'dan yana oldu. - Arayüzü harika ve insanı yormuyor. - Şablon galerisi çok zengin. - Çoklu proje ve çoklu ekip için çok iyi kurgulanmış. Coolify da bu yönüyle gayet iyi ama Dokploy'da kullanıcı ve organizasyon bazlı yetkilendirme çok daha çeşitli kombinleyebiliyorsunuz. - Projelerimde yer alacak yazılımcı arkadaşlarım da CI/CD entegrasyonu ve gitpush ile otomatik deploy tarafını çok sevdiler. - Aslında iki yıldır hobi olarak Docker ile uğraşıyorum :) ve iş bireysel birden fazla sunucum vardı. Olur da ilerde lazım olur, node yönetimi için swarm desteği olması harika. - Küçük çaplı bir stres testi yaptık, Coolify'dan daha verimli kaynak yönetimi var. Boştayken iki panel de aynı yüzdelikte kaynak kullanıyor ama birkaç deploy test sonunda Dokploy çok daha iyi bu konuda. ❌Eksileri: - Dökümantasyon zayıf, bazı şeyleri araştırmak ve çözüm bulmak size düşüyor. - Topluluk tarafı Coolify kadar güçlü değil ama iş görüyor. - Ücretsiz ve açık kaynak olmasına rağmen lisans konusunda çeşitli çekinceler var. - Uzak sunucu izleme için ücretli paket almanız lazım. Eksi midir tartışılır. ✅ Coolify: - Bence yeni başlayacaklar için Dokploy'a nazaran daha kolay kullanımı var. - Özellikle WordPress'in çeşitli varyantlarını kuracaksanız hali hazırda hepsi var diyebilirim (WordPress Mariadb Redis gibi) Dokploy'da compose kodlarını modifiye etmeniz gerekiyor. - Çoklu sunucu desteği gayet güzel ve problemsiz çalışıyor fakat swarm desteği yok. Swarm da lazım olur mu? Olursa zaten milyonluk iş yapıyorsunuzdur :) size kalmış bu kriter. - Topluluk çılgın. Gayet hızlı çözüm buluyorsunuz. Dökümantasyon çok iyi. Kaynak çok fazla var. Kaynak bolluğuna bağlı AI araçları da Coolify ile ilgili sorularınıza çözüm sunabiliyor. Dokploy'da bu imkan zayıf şu an. ❌ Eksileri: - Dokploy'dan sonra arayüzü beni yordu. - Proje ve client arttıkça kaynak tüketimi Dokploy'a göre -18 arası fazla oluyor. Başlarda çok problem değil bana göre ama stres testinde gözüme çarptı. ✅ Stormkit: Türk yazılımcı ve girişimci Savaş Vedova tarafından geliştirilmiş bir panel. Öncelikle muhteşem bir ürün ve kesinlikle desteklenmesi gerekiyor. Kurulumu diğer paneller kadar basit ve test için 16 saat denemem oldu. Lakin bana göre fazla üst seviye bir panel. Teknik bilgi gerekiyor. Enterprise projelerde düşünülebilir.