Atul

I used to get stuck with Git almost every time there was a production deployment. If you’re a developer, keep this list handy. You’ll probably use these commands more often than you think. 🟢 Daily Git Commands • git status → Check changes • git pull origin main → Get latest code • git checkout -b feature-name → Create new branch • git checkout main → Switch branch • git add . → Stage all changes • git commit -m "message" → Save changes • git push origin feature-name → Push code 🔀 Branch Management • git merge branch-name → Merge branch • git rebase main → Reapply commits • git branch -d branch-name → Delete branch 🚀 Before Production • git fetch --all → Fetch updates • git pull --rebase origin main → Sync cleanly • git diff → Compare changes • git log --oneline → View history • git stash → Save work • git stash pop → Restore work • git tag v1.0.0 → Create release tag 🚑 Recovery Commands • git reset --soft HEAD~1 → Undo commit • git reset --hard HEAD~1 → Discard changes • git revert → Reverse commit • git reflog → Recover lost commits • git cherry-pick → Copy commit #Git #Programming #SoftwareEngineering #DevOps #Developer #Java #Backend #Tech

@SaiyamPathak @elonmusk Genius recognises genius

wow, He has rhe X app and used X for the mass reach! kudos to @elonmusk

@jain_harshit Next week will be a defining week in Ai history

Meta joins the party. Better late than never?

The evolution of programming languages 💻 ⚙️ 1972 → C 🗄️ 1974 → SQL ❤️ 1983 → C++ 🐍 1991 → Python ☕ 1995 → Java 🌐 1995 → JavaScript 🐘 1995 → PHP 🔷 2000 → C# 🚀 2009 → Go 🦀 2010 → Rust 🤖 2011 → Kotlin 🍎 2014 → Swift #Programming #Java #Python #CPP #JavaScript #SoftwareEngineering #Coding #Tech

@TheGBreaker Nope

Be honest… would you quit your job if you could earn $5,000/month on 𝕏?

@themishra4402 Claude fable

Everyone says Claude Fable is insane. What's ONE thing it can do that ChatGPT 5.6 still can't?

@shriyya_06 Backend developer

Backend or frontend, which one are you? 🔥

@ash_twtz True

Only the top 1% of developers know the real difference between Stack and Heap. Do you?

@Automateby_Priy 2-4

How many hours do you spend on X every day? - Less than 1 - 1–2 - 2–4 - 4+ Be honest 😂

@Taniyatweets_ Java will always be here trust me

Be honest… which programming language is the most future proof in 2026?

@CodeWithAmann You are already on last step everything is over for you mate 😅

I just deleted Claude and installed Meta AI Now tell me the next steps.

@_avichawla Thats for sharing Avi Chawla , The InsForge integration for reliable backend handling is a clever fix for context exhaustion issues.

I just built a 4-agent software team. Everything runs from Telegram and is managed on a Kanban board. - A project manager who plans the work - A backend developer - A frontend developer - And a tester The PM reads a goal, breaks it into linked tasks, and assigns each to the right agent. The thing that makes them a team instead of four strangers is a shared kanban board. Every task is a row, and when an agent finishes, it writes a summary of what it built and what the next agent needs to know. The next agent reads that summary before it starts. So the frontend developer never has to guess the API shape, and the tester knows exactly what to verify. The hardest part I faced when setting this up was building an agent that could actually act like a backend engineer. A backend engineer has to stand up a database, wire auth, manage storage, deploy functions, and keep all of it consistent while the rest of the team builds on top. An agent doing this from scratch failed almost every time in my run. It burned its context window, remembering which tables existed and which endpoint it created. Due to this, the work context exhausted quickly. I solved this by adding InsForge as the backend context engineering layer. It is an open-source, agent-native backend, and I added it to our backend developer agent as a skill. With InsForge installed, the agent stopped improvising infrastructure and followed a reliable path to create the project, define the database, set up auth, and deploy functions. To test the whole team, I had them build a working Google Docs clone, AI features included. The backend agent spun up the full service on its own, like database tables, user auth, document handling, and edge functions running real TypeScript, all in one dashboard. The frontend agent read that summary and built the UI on top of it, and the tester closed the loop. InsForge GitHub: github.com/InsForge/InsFo… (don't forget to star 🌟) To dive deeper into the full setup guide, Akshay wrote an article on Hermes Kanban, which acts as a mission control for Agents. Read it below.

@arpit_bhayani Thanks Arpit, great breakdown on Meerkat and QuePaxa ,The leader-optional design for handling flaky networks is super insightful.

Cloudflare has been building Meerkat, their new global consensus service, built on a protocol called QuePaxa instead of the usual Raft or Paxos. To be honest, I did not know about QuePaxa before this. I learned about it from the post itself, and it is genuinely interesting. Most consensus systems, like Raft, rely on timeouts to detect a dead leader and trigger a new election. That works fine until your network latency fluctuates a lot, which is exactly what Cloudflare deals with every day. Too short a timeout, and replicas panic and block writes. Too long, and the system just sits there while something is actually broken. So instead of Raft, Meerkat runs on QuePaxa. Here is how QuePaxa avoids the leader problem. A client does not need to go through a leader at all; it can contact any replica, and that replica can drive consensus for the current slot on its own. A leader still exists in the system, and it has one advantage: if it is the one proposing, it takes just one round trip to reach a decision. A non-leader replica needs three or more round-trip to do the same thing. So the leader speeds things up, but it is not a requirement for progress. If the leader goes down or slows down, any other replica simply picks up the work, and writing keeps flowing. Also, concurrent proposals do not conflict destructively. The replicas coordinate and converge on a single agreed value regardless. Interestingly, Cloudflare is planning to build a full key-value store and a leasing system on top of it. I have started reading up on QuePaxa after this post, and wanted to share what I found first. Hope this helps.

@akshay_pachaar Great article Akshay , LMcache insight was amazing , thanks for sharing

14x faster and 90% cheaper LLM inference. (100% open-source, KV cache management) your LLM does the same expensive work over and over. every request, it re-reads the same system prompts and the same documents from scratch, even if it processed them one second ago. token prices keep falling, but agent workloads re-send so much repeated context that the bill climbs anyway. LMCache fixes this. it's an open-source KV cache management layer that plugs into vLLM, SGLang, and TensorRT-LLM. here's how it works: LLMs recompute their understanding of the same content on every request. the same system prompts, the same documents, processed from scratch every time, and a single GPU throws away roughly 15 TB of this reusable cache per day. LMCache stores that cache and serves it back on repeat requests, running as a separate process completely outside the inference engine. the engine just asks for the cache blocks it needs. LMCache handles all the heavy data movement across GPU, CPU, disk, and remote storage in parallel, so cache work never steals compute from inference. it also reuses cache beyond exact prefixes. their CacheBlend technique (EuroSys 2025 best paper) keeps RAG documents cached no matter what order they appear in. on H200s with a 235B model, that adds up to 14x faster time-to-first-token and 4x faster decoding. and since reuse skips the compute entirely (the same reason providers discount cached tokens by 90%), the cost savings follow directly. GitHub repo: github.com/LMCache/LMCache (don't forget to star 🌟) i wrote a full breakdown of KV cache management that walks through why 𝗽𝗿𝗲𝗳𝗶𝘅 𝗰𝗮𝗰𝗵𝗶𝗻𝗴 silently breaks in three common cases, the 𝗱𝗶𝘀𝗮𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗲𝗱 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 behind the 14x speedup, 𝗖𝗮𝗰𝗵𝗲𝗕𝗹𝗲𝗻𝗱, and how to turn every document in your knowledge base into a reusable cached asset. the article is quoted below.

@nishithX26 Ruby

Name one I'll wait

@codewith55 No I don’t think so , in depth knowledge will always be in need.

these books are useless in this AI era

@AKirtesh Thanks Kirtesh

@DevWith_Atul impressive

My coding journey: 📍 2016 → 2020 | C++ ❤️ The language that taught me programming, DSA, and problem-solving. 📍 2020 → 2021 | Python 🐍 Explored automation, scripting, and backend development. 📍 2021 → Present | Java ☕ Building backend systems, APIs, and scalable applications. 🤝 SQL has been the constant companion throughout the journey. Every language I learned shaped the way I think as a developer. What’s your programming language timeline? #Java #CPP #Python #SQL #Programming #SoftwareEngineering #Developer #Coding #Tech

@vicky_grok Really a fantastic course , great insights ,thank you for sharing Vikas

🚨 Anthropic just showed a 27-minute workshop on how to actually do prompts for Claude. Taught by the people who built it. Free. No registration. No paywall. I've seen $300 courses that don't cover what they teach in the first 8 minutes. Watch the session, then read the guide on building loops below.

@omarvvvr Cpp is best

Can you name a programming language better than C++ or no ?

@AKirtesh I am a full stack developer but primary focused on backend developement

Devs, Backend or frontend, which one are you? 🔥