The first time I deployed a Next.js app to production, it took me three days. Not because the app was complicated — it was a straightforward portfolio site. It took three days because I had no idea what I was doing with AWS, I'd never written a GitHub Actions workflow, and every tutorial I found either skipped the hard parts or assumed I already knew them. By the time I was done, I had a deployment pipeline I was genuinely proud of: push to main, GitHub Actions runs the build, tests pass, the app deploys to an EC2 instance behind CloudFront. Zero manual steps. Zero downtime deploys. Total cost: about $5/month. This guide is the one I wish had existed. We're going to deploy a Next.js app to AWS from scratch — EC2 for compute, CloudFront for CDN, GitHub Actions for CI/CD — with every step explained so you understand what you're building, not just copying commands. Why AWS Instead of Vercel? This is a fair question. Vercel is genuinely excellent for Next.js, and for most projects it's the right call. You push, it deploys. Done. AWS makes sense when: You need to control the infrastructure (compliance, data residency, custom VPC configuration) You're running other services (databases, queues, lambdas) in AWS and want everything in the same network You want to learn infrastructure skills that transfer to enterprise environments Your app has specific performance requirements that benefit from custom CloudFront configuration You're a freelancer or consultant who wants to bill separately for infrastructure If none of those apply to you, use Vercel. This guide is for when they do. The Architecture Here's what we're building: ┌────────────────────────────────────────────────────────┐ │ GITHUB ACTIONS CI/CD │ │ │ │ Push to main → Build → Test → Deploy to EC2 │ └──────────────────────┬─────────────────────────────────┘ │ SSH deploy ▼ ┌────────────────────────────────────────────────────────┐ │ AWS EC2 INSTANCE │ │ │ │ Ubuntu 22.04 LTS │ │ Node.js 20 + PM2 (process manager) │ │ N

The LedgerSync pipeline was inserting 1.5 million rows into PostgreSQL using pandas.to_sql() . It took four minutes per run. I switched to psycopg2's COPY command and it dropped to 18 seconds. Same data, same schema, same machine. That is not an optimization tip. It is the difference between a pipeline that fits in an Airflow schedule and one that does not. This article is about patterns like that: the ones that matter when you are building pipelines that run on a schedule, not when you are writing ad-hoc queries. Loading Data: to_sql vs execute_values vs COPY There are three ways to write rows from Python into PostgreSQL, and the performance gap between them is significant. pandas to_sql issues one INSERT statement per row by default, or a multi-row INSERT with method="multi" . It is the easiest to write and the slowest for any serious volume. psycopg2 execute_values batches many rows into a single multi-row INSERT VALUES statement. About 5x faster than to_sql for medium-sized loads. psycopg2 COPY streams rows directly to PostgreSQL using its native bulk-load protocol. No statement parsing, no row-by-row overhead. For LedgerSync at 1.5M rows, this was the one that mattered. import psycopg2 import io import pandas as pd conn = psycopg2 . connect ( " host=localhost dbname=proj_db user=proj_user password=proj_pass " ) def bulk_copy ( df : pd . DataFrame , table : str , columns : list [ str ]): buf = io . StringIO () df [ columns ]. to_csv ( buf , index = False , header = False ) buf . seek ( 0 ) with conn . cursor () as cur : cur . copy_from ( buf , table , sep = " , " , columns = columns ) conn . commit () print ( f " Loaded { len ( df ) } rows into { table } " ) Use COPY for initial loads and large backfills. For incremental daily writes of a few thousand rows, execute_values is fine and gives you more control over conflict handling: from psycopg2.extras import execute_values def bulk_insert ( rows : list [ dict ], table : str ): if not rows : return columns = list

The first gameplay trailer shows off bloody melee combat.

I would like some advice from well experienced devs that you would give to junior devs submitted by /u/Dizzy_External2549 [link] [留言]

At its big State of Play show on Tuesday, Sony shared new look Marvel's Wolverine, the next big title from Insomniac Games that's launching exclusively on PS5 on September 15th. Dressed in the iconic yellow Wolverine outfit, Logan slunk around and stabbed his way through a bunch of enemies, using his blades to take them […]

There's a specific feeling you get after your third production caching incident. It's not panic....

Running multi-turn or multi-agent AI sessions? There is a consistent degradation pattern across tools: context fills with repeated history, tool schemas, and subagent handoffs. A 2026 paper by Bai et al. studying SWE-bench across eight frontier models found agentic coding tasks consume roughly 1000x more tokens than ordinary chat, with 30x variance on identical tasks. Accuracy does not rise with spend. In one tracked research synthesis run I observed context hit 450,000 tokens. The agent dropped early constraints, re-queried sources already in history, and required manual reset. After adding three controls, the same class of task peaked near 85,000 tokens: PLAN.md and INVARIANTS.md outside the conversation window, read fresh each major turn A 2,000-line read budget gate per turn (agent states intent before any retrieval) Out-of-band notes for subagent coordination so side traffic never enters the main transcript Dynamic tool discovery produces similar ratios. One harness reduced input tokens 96% and total spend 90% by loading schemas only for tools the agent actually selects, rather than injecting a full catalog on every call. Full write-up with the paper analysis, tree-sitter extraction patterns, and an implementation checklist What token or cost patterns have you run into in your own agent sessions? submitted by /u/magicroot75 [link] [留言]

AI agent built into your CRM who works leads for you Discussion | Link

Microsoft missed the boat on apps, so get ready for agents.

While the majority of Summer Game Fest takes place over the weekend, Sony is getting a jump on things with its next State of Play showcase, which airs on June 2nd at 5PM ET. It’s coming at a pivotal time for the PlayStation brand: The PS5 keeps getting more expensive and Sony’s big bet on […]

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Hollow Knight joins the Amazon Luna game catalog this month.