Writing about production AI systems, system design, and lessons learned from building platforms at scale.
Anthropic shipped Claude Opus 4.8 on May 28, 2026. SWE-Bench Pro jumps from 64.3% to 69.2%, Fast Mode runs 2.5× faster at 3× lower cost, and Dynamic Workflows lets Claude Code orchestrate hundreds of subagents. Here's the full developer breakdown.
Google's Gemini CLI shuts down June 18, 2026. A practical, step-by-step migration guide to Antigravity CLI with before/after code, env vars, auth, and CI fixes — done in 15 minutes.
GitHub disclosed a supply chain breach this week exposing internal code and customer data. I audited Modelia's dependency tree right after — here's what I found, what you should check, and the patching playbook for 2026.
Meta, Amazon, Microsoft and Google are spending record amounts on AI infrastructure while cutting 170,000 jobs in 2026. A grounded, honest read on what this actually means for engineers 1–3 years into their career.
Model Context Protocol hit 97 million installs in 2026 but most tutorials stop at hello-world. A hands-on guide to building production MCP servers with real code, auth, tool registration, and observability — from a production engineer at Modelia.
Gartner says 60% of code will be AI-written by end of 2026. Stack Overflow says 84% of developers use AI but only 29% trust it. I've shipped production systems with AI daily for 18 months — here's what's real, what's hype, and what changes for your job.
Anthropic's unreleased Claude Mythos model uncovered 10,000+ zero-day vulnerabilities in a month through Project Glasswing. What AI-powered vulnerability discovery means for developers, dependency security, and the future of cybersecurity in 2026.
Shopify just shipped an AI agent that reviews your app for App Store compliance before submission. How the new self-review tool, Partner Dashboard tracking, and automated pre-submission checks change Shopify app review in 2026.
Anthropic released Claude Opus 4.7 on April 16, 2026. A hands-on look at what changed, how it compares to Opus 4.6, the new xhigh effort level and task budgets, and what the Project Glasswing safeguards mean for production AI systems.
A comprehensive guide to architecting type-safe microservices using tRPC, Prisma ORM, and Node.js. Learn patterns from Asynq.ai and Modelia.ai's studio platform to achieve 40% performance improvements.
Learn techniques to improve database performance by 40%. Real-world examples from production systems at Asynq.ai and Modelia.ai handling millions of requests daily.
Modern strategies to build blazing-fast React applications. From code splitting to memo patterns, real techniques from building EduFly and GyanSathi LMS.
From development to production: containerization strategies that ensure consistency, security, and scalability. Lessons from deploying EduFly on AWS.
Master the new App Router, Server Components, and data fetching patterns. Everything you need to build production-ready Next.js applications.
Insights from building frontend interfaces at Bharat Electronics Limited (BEL) for the Indian Airforce — rigorous processes, reliability, documentation, and the weight of critical systems.
Implementing effective caching patterns that reduced our API response times by 60% at Asynq.ai. Learn cache invalidation, TTL strategies, and common pitfalls.
Go beyond basics with discriminated unions, template literals, and conditional types. Real patterns from enterprise codebases at Modelia.ai.
Cost-effective cloud architecture that grows with your startup. How I architected EduFly to serve 15K+ users on AWS with 99.9% uptime.
Automate your deployment pipeline from testing to production. Real workflows from EduFly, Asynq.ai, and Modelia.ai deployments.
How we built autonomous AI agents at Asynq.ai and Modelia.ai that reason, plan, and execute multi-step tasks. Practical patterns for tool use, memory, orchestration, and guardrails in production agentic systems.
How we use Anthropic's Claude API to power agentic workflows at Modelia.ai — from tool use and extended thinking to structured outputs and multi-turn agents. Practical patterns for building reliable AI agents with Claude.
Lessons from running agentic AI systems at scale — how we handle failures, monitor agent behavior, manage costs, and scale from single agents to multi-agent pipelines at Modelia.ai and Asynq.ai.
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