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This is the second stage of my CodeAlpha Full Stack internship — two projects, built in a deliberate order so the patterns from the first carry forward. First was a project management tool (auth + real-time updates with Socket.io). This one is a store: products, cart, orders. Same stack — Express, Prisma, PostgreSQL, JWT — but the interesting part isn't the CRUD, it's the order-placement flow, which is the first genuinely transactional piece of logic in the whole internship. I'll walk through the schema decisions, the auth changes from project one, and then spend most of the time on the part that actually matters: making sure an order can never be created without correctly and atomically updating stock and clearing the cart. The schema model User { id String @id @default(cuid()) name String email String @unique password String role String @default("USER") createdAt DateTime @default(now()) orders Order[] cartItems CartItem[] } model Product { id String @id @default(cuid()) name String description String price Float image String? stock Int @default(0) category String createdAt DateTime @default(now()) cartItems CartItem[] orderItems OrderItem[] } model CartItem { id String @id @default(cuid()) quantity Int @default(1) user User @relation(fields: [userId], references: [id]) userId String product Product @relation(fields: [productId], references: [id]) productId String @@unique([userId, productId]) } model Order { id String @id @default(cuid()) status String @default("PENDING") total Float createdAt DateTime @default(now()) user User @relation(fields: [userId], references: [id]) userId String items OrderItem[] } model OrderItem { id String @id @default(cuid()) quantity Int price Float order Order @relation(fields: [orderId], references: [id]) orderId String product Product @relation(fields: [productId], references: [id]) productId String } Two decisions worth explaining, because they're easy to get wrong if you're building this for the first time. OrderItem.price is a

While researching API changes I noticed something — Google Maps removed DirectionsService on May 1 2026 with no soft fallback. Calls just throw runtime errors after the deadline. Most developers won't know until something breaks. So I built DepRadar — paste your package.json, it checks your exact stack against known deprecations and shows only the ones affecting you, with severity, sunset dates, and migration links. Currently tracks 13 real deprecations across: Google Maps (DirectionsService, DistanceMatrixService removed) OpenAI (Realtime API Beta sunset) AWS SDK v2 (maintenance mode) Microsoft Actionable Messages (retired) moment.js, request package And more Free → depradar.netlify.app Open source → github.com/Ahmed889-code/depradar What deprecations am I missing from your stack?

I've been coding with AI agents for about two years. Every major one. Cursor, Copilot, Codex, OpenCode. They're good at generating code. They all share one problem. They forget everything. You finish a session, close the window, and the agent resets. Next time you open it, you're starting from zero. "We use pnpm, not npm." "The database is SQLite, not Postgres." "Don't touch the migrations folder." You repeat yourself. Every. Single. Time. Some tools added memory features. Usually as an afterthought. A pinned file. A custom instruction. A context window that grows until it hits a wall and everything old gets silently dropped. I didn't want a bigger context window. I wanted an agent that accumulates knowledge the way a colleague does. Not by being retrained. By taking notes, writing down what it learned, and reading those notes next time. That's what Jean2 can do. Not through fine-tuning. Not through vector embeddings. Through files on disk that the agent reads and writes itself. But here's the thing: none of this is on by default. By default, Jean2 is as bare as Codex or OpenCode. A blank prompt. No memory. No skills. No session search. You opt in to each layer in workspace settings . That's the point. You build the agent you want, layer by layer. The Four Layers If you turn them on, Jean2's agent has four knowledge layers that persist across sessions. They're not features bolted on top. They're part of the system prompt that gets composed every time a session starts. 1. Workspace Memory Turn on workspace memory in workspace settings , and the workspace gets two files: MEMORY.md for shared knowledge and USER.md for your personal preferences within that workspace. Both live at <workspace>/.jean2/ . The concept is simple. Shared knowledge that's useful for any agent working in that workspace. "We use pnpm." "The database is SQLite." "Don't touch the migrations folder." Whatever agent you bring in, coding specialist, reviewer, docs writer, they all get the same context

Explore how the Aspire team turns merged product changes into SME-reviewed docs pull requests, closing the gap between release and documentation. The post Automating cross-repo documentation with GitHub Agentic Workflows appeared first on The GitHub Blog .

Lionel Messi and Cristiano Ronaldo are betting on AI, health tech, and startups. Mohamed Salah is taking a more traditional route beyond football.

Like its U.S. counterpart, the European Chips Act aims to foster the semiconductor industry — in part thanks to state subsidies. One of the beneficiaries is QuantumDiamonds, a German startup that applies a novel approach to inspecting chips.

After more than a decade of pushback, farmers and repair advocates have won access to equipment and services John Deere had long kept under its control.

Experiments in using AI to build AI show that the future doesn’t just belong to the frontier labs.