One Engineer + AI Agents Replace Seven-Person Teams
Sid Sijbrandij, the co-founder of GitLab, just said: "One developer with parallel AI agents will outproduce an entire team of seven." And at his new company Kilo, that's already the standard. He has 20 engineers. Each one manages multiple AI agents across parallel work streams. • One builds • One reviews • One deploys All simultaneously while the human keeps the system moving. He said it himself: "It used to be that you needed a team of seven people to do something. Now you have one person and a whole team of agents working on something." He calls 2026 the year this goes mainstream. Kilo is already shipping orchestration features that split tasks across multiple agents with smaller context windows so they run faster, cheaper, and don't lose half their context. They're even building runoffs where two different models tackle the same task so you can compare outputs and ship the stronger one. Every engineering org will have to restructure around this. The question is whether you'll be orchestrating the agents or getting replaced by someone who is. PS. Sid Sijbrandij (@sytses), co-founder at GitLab (@gitlab)and Kilo Code (@kilocode) is doing a keynote on May 7th at SynBioBeta this year. If biotech, open source, or the future of AI-driven science is your world, the founders, investors, and researchers shaping it will be in the room. Link for tickets below.
DevTools Warns URL Not for Production Use
I am looking at messages in Google Developer tools and it is saying https://t.co/GlZADMaCAQ should not be used in production so if you are…. https://t.co/im7RGR0fNq
AWS Engineers Deliver Invisible, Game‑Changing Infrastructure Advances
“The best engineering is invisible. You never notice. And for twenty years, this is exactly what our engineers have done day in and day out”, says AWS @Werner as AWS enters 21st year. “The hypervisor overhead that disappeared. The cold...
Scion Runs Agents in Isolated Containers, Not Scripts
"Most agent frameworks treat AI as a library or prompt-chaining script that runs directly in your environment. Scion takes a different approach — it treats agents as system processes, wrapping each one in a dedicated container and tmux session." https://t.co/Pjc4O6WUpi
Model Armor Adds Gatekeeper for Secure AI Inference on GKE
Guardrails at the gateway: Securing AI inference on GKE with Model Armor https://t.co/9JExlcrCJd < you're running an open model on Kubernetes, but want a gatekeeper to inspect traffic before and after the model gets called. This architecture shows how to...
AI Coding Boosts Enterprise Productivity—But How Much?
What is the actual impact of AI assisted coding in large enterprises? I am personally pretty blown away by what I can build with it but at scale I rarely hear specifics on the impact. Are large teams actually 10% faster...
Build a HIPAA‑Ready Health Data Platform on AWS
https://leketecy.hashnode.dev/building-a-hipaa-ready-health-data-platform-on-aws If you are a DevOps engineer, platform engineer or SRE go through my blog and read on this topic #Devops #platform #sre
LLMs Now Callable Directly From Pub/Sub Pipelines
At some point, it'll be possible to call an LLM from ANY piece of your architecture. Should you? We just added the ability to call LLMs (managed ones, or custom ones) from @googlecloud's messaging service Pub/Sub. I ask the question, and tried...
Docker Sandboxes Isolate AI Agents with Safe MicroVMs
Want to let AI agents go full YOLO mode without risking your host? 🚀 See how Docker solves the isolation problem with Docker Sandboxes. Lightweight microVMs keep your system completely safe.🛡️ Watch here (and see who chewed my hat 🐶): https://youtu.be/PVjuMgjr0CU #AI #docker
Essential Redshift‑Azure AD Federation Guide for SSO Errors
I wrote the guide I wish I had: Redshift + Azure AD federation what works what breaks what makes zero sense in the docs if you’ve hit token errors or SSO issues, this is for you ⤵️ ✨
AI Can Run Workflows, but Accountability Remains Unclear
RT Anthropic reports that AI can now handle "entire implementation workflows." Impressive,but who is accountable for #observability, nonfunctional requirements, #DevSecOps guardrails, and #FinOps #AI @Star_CIO https://t.co/p18hdtdbZn
One File Guardrails Tame AI Code Overreach
How to stop AI agents from ruining your codebase (with one 18K+ star file) 🤯 @Karpathy recently ranted about how LLMs code: They assume too much, overcomplicate simple tasks, and refactor things that aren't broken. To fix this, a dev turned those observations...
Clarifying DevOps vs SRE: Key Differences Explained
I found this video super helpful for understanding the difference between DevOps vs SRE 👇 If you’ve been confused about the two — this one’s for you 🙌🏾
Force OpenClaw to Generate Tests, Even if It Doesn't
Just because OpenClaw doesn't write tests on its own when it's creating software for you doesn't mean you shouldn't make it make tests for you... https://t.co/TqrgnU71SH
Seeking AI Agents for Deterministic DevOps Collaboration
Dear algo: please connect me with people interested in AI agent harnesses for deterministic software engineering, CI/CD, operations, observability, and reliability. No Grok
QA Bot Integration Boosts AI-Driven Customer Support
Discover how the integration of a question-answer bot can enhance AI-powered quality assurance, optimizing customer interactions and support processes. https://t.co/ossWoHHtjy
GBrain Adds Clickable Private Supabase File Redirects
Day 2 of Agentic Engineering GBrain from the poolside of the Rosewood Kona Village Hawai’i Right now added improved GBrain file storage so that private Supabase Files linked from markdown can be clicked through via Supabase Edge Function temp redirects All...
Reduced to One Worker, Now Runs Overnight
Scaled infra down to a single worker. Last run was burning tokens way too fast. Now it’s crawling… so this one runs overnight.
Shared Observability Unites SOCs and DevOps
RT SOCs and DevOps will need shared observability for agents: data access, tool calls, MCP interactions, and risk levels in one view. #Security #DevOps @Star_CIO https://t.co/tRGwCPc4Mb
Scale Gradually: Start Simple, Add Complexity When Needed
Step-1: Use a static web framework to save costs Step-2: Run entire website on a single virtual machine for simplicity Step-3: Split backend & database into separate virtual machines Step-4: Add more availability zones to improve resilience Step-5: Use serverless for infrequent workloads Step-6: Keep...
AI Agent Automates Dev Issue Resolution on AWS
AI Agent passing development issues, online. Join the Thread 🍿 AWS infra. ClaudeCode. Pilot. Hit the star: https://github.com/qf-studio/pilot
AI Bug‑Fix Pipeline Nears Launch, Integrates Top Tools
🤏 We're this close to launching our AI bug fixing pipeline It gracefully connects @linear @jamdotdev @claudeai @sentry and @greptile https://t.co/RGEJWqunwR
AI Code Reviewers Catch Bugs, Boost Speed
I use Claude and Codex to review my code before pushing. Catches: - Edge cases I missed - Security issues - Performance problems They also work together to identify issues Takes 30 seconds. Saves hours of back-and-forth. LLMs are great copilots.
A Proxy Without SLOs Is a Liability
Your proxy is either a guardian or a liability. There’s no in-between. If it doesn’t have its own SLOs, timeouts, and runbook — it’s not a safe proxy. It’s a false sense of security with a load balancer in front. 🫥 What’s yours running...
Replit Deploys to Databricks, Boosting Enterprise BI Speed
Replit now deploys directly to Databricks. Your apps run inside your Databricks environment while inheriting its security, governance, and data access. Beta is live. Enterprises are already building with it and seeing massive acceleration in BI and internal tools. https://t.co/O33uJHohgo
Claude Code Automates Browser Testing Directly From Terminal
Claude Code can control your browser. I asked it to test a form on localhost. It opened Chrome, typed in the fields, submitted bad data, and caught a validation error. All from my terminal. No Selenium. No Playwright.
Docker Simplifies: Build Once, Run Anywhere
Docker made simple: build once, run anywhere. 🐳 This carousel breaks down the essentials every developer should know: • What Docker is • Restart policies (always / unless-stopped / on-failure) • Port mapping • Docker networking • Volumes & bind mounts If you’ve ever said “it works...
Kubernetes Errors Follow Patterns—Stop Guessing, Start Debugging
Kubernetes errors aren’t random. You just don’t know the pattern yet. 100 real errors → RCA → fixes Stop guessing. Start debugging. Follow @devopsshack Comment “k8” to get the full guide #kubernetes #devops #k8s #cloud #aws #docker #cicd #sre #cloudnative #microservices #platformengineering #softwareengineering #devopsshack #learnkubernetes
MLOps: Essential Cycle to Keep Models Alive
MLOps = Making ML work in production. Train → Deploy → Monitor → Retrain If you skip this, your model will fail. Follow for more real DevOps + AI content. Save this for later. Comment MLOps for roadmap. #mlops #machinelearning #ai #devops #datascience #mlengineer #cloudcomputing #kubernetes...
GBrain Runs on Hermes Agent with Simple Script
GBrain works on Hermes Agent, paste the same install script and you're good to go. https://t.co/yFpFU4pn5b
Tripled @‑Mention Speed in Massive Codebase with Claude Code
Just got a nice DM from a big enterprise customer using Claude Code in one of the world's biggest codebases Here's how we made @-mentions 3x faster 🧵
Fine‑tune Gemma4 Model Using Serverless Google Cloud Run
Great example from Shir. Follow along to see how to fine-tune a #Gemma4 model directly on serverless @googlecloud Run jobs.
Replace Release Boards with Guardrails, Policy-as-Code, Self-Service
Enterprise release boards won't get you SaaS agility. Shift to guardrails over gates, policy-as-code, and self-service delivery. #DevOps #Cloud https://t.co/e4TERhpY2r
Agentic Infrastructure: The Future Backbone for AI‑Native Cloud
Agentic Infrastructure is the future of the cloud ① For coding agents If you use Claude Code, Codex, Cursor, you need infra that 'clicks' for your agents, not just devs. ② To deploy agents Pages → Agents. Long-running compute, sandboxes, and our token...
ServiceNow Ditches Sidecars, Launches Context Engine & New Commercial Bet
ServiceNow Ends the Sidecar Era: Context Engine, Build Agent Skills, and a New Commercial Bet https://t.co/Qko2HSYx3z
Enterprise DevOps Must Mirror SaaS's Data‑Driven Obsession
SaaS teams succeed by measuring everything: deploys, failures, recovery, and adoption. Enterprise DevOps needs the same obsession with telemetry and outcomes. #DevOps #SRE https://t.co/e4TERhpY2r
Linux Command Line: Your Tech Superpower Toolkit
Linux isn’t just a skill — it’s a superpower for anyone in tech. From file management and networking to system diagnostics and automation, mastering the command line gives you real control over your systems. This carousel breaks down essential Linux commands every...
Ultralytics Platform Unifies and Accelerates Computer Vision Pipelines
Ultralytics Platform: Simplifying End-to-End Computer Vision Development In this episode of Artificial Intelligence: Papers and Concepts, we explore the Ultralytics Platform, a unified ecosystem designed to make building, training, and deploying computer vision models faster and more accessible. Known for powering...
Claude Code Now Runs as Recurring Cron Loop
Claude Code just became a cron job. /loop 5m check if the deployment finished. It runs any prompt on a recurring interval while you keep coding in the same session.
Rebuilding Pipelines Cuts Costs 3×, Boosts Ad Quality
Found major tech debt in our GTM stack. Rebuilt our Meta pipelines from scratch - ad quality scores way up, early costs down ~3x. Great engineering fixes a lot of ills.
Start DevOps Right: Follow This Essential Learning Order
Most beginners start DevOps the wrong way. Correct order should be: 1️⃣ Linux basics 2️⃣ Networking fundamentals 3️⃣ Git & GitHub 4️⃣ Cloud (AWS / Azure / GCP) 5️⃣ Docker 6️⃣ Kubernetes 7️⃣ CI/CD pipelines 8️⃣ Monitoring tools Follow the roadmap. Stay consistent.
Instrument AI Agent Interactions as Distributed Traces
RT Treat every AI agent interaction like a distributed trace: prompts, tools, model calls, actions, and outcomes - all instrumented #DevOps #AI @Star_CIO https://t.co/tRGwCPc4Mb
Anthropic's 89% Uptime Reveals Chaotic DevOps Reality
"One thing I saw that speaks to how chaotic it is at Anthropic was their uptime charts -- it's 89% uptime — and I'm looking for nine 9s. And it's no 9s. Imagine if you're the Anthropic DevOps guy." -- Kain https://t.co/HJ4d0pgTJE
Defenders Must Build Infrastructure Now; Models Ready, Ecosystem Lagging
"The priority for defenders is to start building now: the scaffolds, the pipelines, the maintainer relationships, the integration into development workflows. The models are ready. The question is whether the rest of the ecosystem is." https://t.co/z2GZ3SdDwW
Standardize Pipelines to Achieve SaaS‑speed Enterprise Platforms
Want SaaS-level speed in the enterprise? Standardize pipelines, reduce configurations, and productize your internal platforms. #DevOps #PlatformEngineering https://t.co/e4TERhpY2r
Detect Code Pain Points with Five Git Commands
"Five git commands that tell you where a codebase hurts before you open a single file. Churn hotspots, bus factor, bug clusters, and crisis patterns." https://t.co/szukDCA4TB < educational post. By running these commands, you can learn a lot about what...
Queue Agent CI Jobs to Prevent CPU Overload
When running local ci in an agent world, you might find your machine overrun by multiple, concurrent all-core runs. We did, so trying this nice, neat orderly line for agents: WAIT YOUR TURN. https://t.co/GPPmirjFM8
Coding Agents Enable Cheaper, Faster Software Hardening
"I think we’re going to see a lot more reimaginings, where people attack old problems with modern tactics. Coding agents lower the costs of taking on stalwarts and raise our ability to rapidly harden our software." https://t.co/rDAftsXXKe < I like...
No‑skill Promises Mask Hidden Migration Costs
Vibe coding sells the dream of "no technical skills needed" then creates users who can't comprehend why migrating their AI-generated infrastructure costs actual engineer money. You don't see the 100+ migration files. You just see the "simple" UI. And that's the trap.
Three AI Reviewers Auto‑audit Code in Parallel
After Claude Code writes my code, I make it review its own work. /simplify spawns 3 AI reviewers in parallel: one hunts dead code, one checks naming and structure, one profiles for performance. All running at the same time.