This guy literally dropped a prompt that writes your entire business plan in mins

I built a simple multi-agent system to reply to some of my emails. This video will show you step by step how to do the same. Here is what you'll need: • Python • Google ADK • Zapier's MCP to access Gmail

"Agentic Design Patterns: A Hands-On Guide to Building Intelligent Systems" Read the Online eBook from Google at https://t.co/QG5bfTmrLD Buy hardcopy version at https://t.co/mCimPiYZu8

Jira is so slow and bloated that it was worth to spend some time to build my own desktop app (that syncs incoming issues) How? 1. wrote a spec in gpt-5.2 2. paste spec to aistudio (Gemini 3 Pro) for frontend 3. paste spec to gpt pro for initial mvp backend code 4. create a new

Rate limiting is one of the most important concepts in system design - yet most people only know the basics. Behind the scenes, there are multiple algorithms, each designed to handle different traffic patterns, scalability needs, and fairness rules. Here’s the breakdown of the

A system design interview checklist you can fall back on every single time - regardless of whether it’s Reddit, Uber, or some made-up product. 1. Clarify the problem (before touching architecture) What exactly are we building? Who are the users? What’s in scope and what’s out?

Lotta people on the TL who have never been staff at a big company telling me today that Opus 4.5 is AGI for software engineering 👍

At Staff Engineer level, observability is not “how do I debug this service?” but becomes “how do I prevent the org from flying blind?” You’re no longer designing dashboards for your team but you’re shaping how the entire system communicates pain, risk, and confidence. Here’s

Culture is what happens when the manager leaves the room. Early in my career, I heard this line and didn't think too much about it. Then I experienced it firsthand again and again and realised how true it was. Companies write their values on a wall, run workshops but none of it

How Nginx Works End to End

Understanding system design patterns is essential for building reliable, scalable systems. Here’s a simplified breakdown with real-world analogies. 1. Failure Handling Patterns Handle service crashes and recovery smartly. - Circuit Breaker: Stops calling failing services to

Perplexity just quietly dropped a 42-page internal guide on how they actually use AI at work.

"Running 1:1s for Engineers". Here’s what works for for Can: a simple, repeatable structure that he uses every single week. It’s based on the popular People, Product, Process format by Can Duruk https://t.co/IyufgJhMI1

Startup Engineering Team Organisation https://t.co/HaFILTlFCM

API Pagination Techniques 1. Offset-Based Pagination → Definition ✓ Uses offset and limit parameters to fetch specific slices of data. → Example GET /products?offset=20&limit=10 → Pros ✓ Simple and widely supported ✓ Easy to implement and understand → Cons ✓ Slow

Build production-ready real-time voice AI agents! TEN is an open-source framework for building multimodal, conversational AI systems that run in real time. It handles the full real-time loop for voice interactions with audio input, ASR, LLM, TTS, streaming, and tool calls

Every AI coding assistant has the same problem. They generate code in isolation. And have no awareness of: - Your existing codebase patterns - Your security requirements - Your technical debt - Your test coverage standards Finally, there's an MCP that solves this and detects

Want better database observability? PlanetScale has Prometheus-compatible metrics exporters for both Vitess and Postgres. This plugs right in with tools you already know: Grafana, Datadog, and other popular monitoring platforms.

Being knee-deep in Postgres, things I miss from MySQL: - B-tree table storage - Vitess - Undo log based MVCC - SHOW TABLES - Vitess - Buffer that doesn't rely on OS page cache - SHOW CREATE DATABASE But mostly, Vitess.

Stop paying for $3,000 "RAG" bootcamps. Qdrant just put a full, production-grade vector search course on YouTube. For free. This isn't a demo. It's a 7-day sprint where the final project is to ship a complete, production-ready documentation search engine. The full curriculum