Platform engineering has won the argument. Some 90% of organizations have adopted at least one internal platform; golden paths are The post Platform engineering’s new job: serving environments at agent speed appeared first on The New Stack .
Can Grok 4.5 really match Opus for a quarter of the tokens? xAI released Grok 4.5 on July 8. It The post I trust Claude for everything. This test made me rethink that. appeared first on The New Stack .
I’m Matt Burns, Chief Content Officer at Insight Media Group. Each week, I round up the most important AI developments, The post Musk open-sourced Grok Build to fight Anthropic. Anthropic pays him $1.25 billion a month. appeared first on The New Stack .
The Hidden Cost of API Versioning Hell Continuous API evolution is non-negotiable in contemporary software development, yet maintaining backward compatibility remains an incredibly expensive and labor-intensive hurdle . Core schema mutations frequently force downstream enterprise clients into disruptive and unplanned refactoring cycles, stalling product velocity .
I have lost more afternoons than I would like to admit on this exact problem: a seed script that ran cleanly yesterday now crashes on its first INSERT , and the error message tells you something you already knew, namely that you have a chicken-and-egg dependency between two tables. SQL ERROR: insert or update on table "users" violates foreign key constraint "users_organization_id_fkey" DETAIL: Key (organization_id)=(1) is not present in table "organizations".
Developers building with AI have largely relied on proprietary models like Anthropic’s Fable and OpenAI’s GPT-5.6 Sol for their most The post Kimi K3 tops Arena’s coding leaderboard — and it’s open-weight appeared first on The New Stack .
As AI agents tackle more tasks, such as managing online accounts, authentication has become a practical engineering problem. For example, The post 1Password’s new browser integration for Claude changes how AI uses your credentials appeared first on The New Stack .
The year is 2026, and the way software is built has fundamentally shifted. We are no longer just writing code for other humans to read; we are building systems that AI coding agents, such as Cursor, GitHub Copilot Agent Mode, Claude Code, and autonomous CLI tools, will navigate, debug, and extend. As Java developers, we are blessed with robust tooling.
Ask most detection engineers what a SOC does, and they'll say: it finds compromised machines. That's the wrong question. Attackers stopped compromising machines as the primary objective years ago — machines are just where identities and trust relationships happen to execute. A stolen session token, a federated role assumption, an over-scoped service account: none of those are "a machine got popped.
As AI agents evolve beyond writing code toward handling everyday tasks for people, the infrastructure required to keep them on The post “They’re dead if they don’t offer this”: DoorDash’s CLI for agents may be out of necessity appeared first on The New Stack .
Modern enterprise software design has fundamentally shifted away from monolithic, single-threaded runtimes toward decoupled, containerized architectures. When building systems that handle high throughput — such as fintech services, automated reporting pipelines, or real-time distributed platforms — engineers must address two core infrastructure vectors: high-concurrency connection management and deterministic relational state execution.
A CI/CD pipeline that runs without errors creates a sense of correctness. The job is green. The deployment happened. The infrastructure must reflect what it should. This logic feels sound, and it breaks down in a specific way worth understanding. The pipeline knows what it was told to do at the time it ran. It does not know whether that was the right thing to do.
As enterprise leaders start deploying agentic workflows, they must establish the infrastructure to build and run them, one capable of The post Arm and Google offer a smarter option to run agentic AI workloads appeared first on The New Stack .
Microservices architecture is frequently presented as the natural evolutionary step for scaling modern systems. In presentations and case studies, it appears almost inevitable. Break the monolith into smaller services, deploy independently, scale selectively, and gain resilience through isolation. In practice, the story is more complex. Across long-running production environments, I have seen microservices introduce as many risks as they resolve.
Kubernetes controllers are what make the platform’s declarative model real. They observe the state, reconcile toward the intent, and keep The post From intent to enforcement: Lessons from operating Kubernetes controllers at scale appeared first on The New Stack .
Comic Sans has been mocked, memed, and muzzled from corporate communications since time immemorial, but most people won’t know that The post Microsoft just open-sourced the app that put Comic Sans on the map appeared first on The New Stack .
Postgres can run a reliable background job queue with FOR UPDATE SKIP LOCKED. Build a worker queue with retries using pg and Prisma Postgres, no broker required.
The Prisma Studio Migrations view shows every applied Prisma Next migration as a timeline with a visual diff, the executed SQL, and a schema diff.
Why we’ve stopped noticing the real improvement opportunity Since AI arrived, many people have mentioned that the bottleneck has shifted The post AI hasn’t shifted the bottleneck from coding to code review appeared first on The New Stack .
Ask a platform team about their deployment capabilities, and you will usually hear a genuinely impressive story. Progressive rollouts that The post You don’t have a deployment problem. You have a validation problem. appeared first on The New Stack .
Al has blindsided cloud native infrastructure management, rendering established platform engineering woefully inadequate. Original platform engineering often suffers from a developer-only focus, but a platform that serves only one persona in a multi-persona organization ultimately delivers a shrinking fraction of its potential enterprise value. Autonomous agents are already beginning to write, review, test, and deploy code or fixes with or without human intervention.
When Nothing Is Broken — But the System Still Fails You hit a failure. Tests are failing, or the system behaves in a way that doesn’t make sense. You check the code first. Nothing obvious. Then logs. Still nothing conclusive. You retry. Same result.
Caching was one of the most critical optimizations in modern AI systems long before most teams realized it. Early prototypes The post Why smarter AI caching sometimes makes everything slower appeared first on The New Stack .
Creator of the Linux kernel, Linus Torvalds, has refreshed his stance on the use of AI in software development with The post Linux creator Linus Torvalds tells AI haters to walk away from Linux, or go fork it appeared first on The New Stack .
Being a Python developer, I have lived through the chaos: setup.py, requirements.txt, virtualenv, pipenv, conda, flit, hatch, poetry — each has promised to fix what came before. In 2026, the dust has settled around these three contenders:
We were building a DevOps agent to help with on-call remediation. The idea was straightforward: when an incident fires, the agent reads the relevant runbook from our internal wiki, assesses the situation, and executes the appropriate remediation steps. No waiting for an engineer to wake up at 3 am, find the right page, and manually run through a checklist. The agent had the context, the tools, and the access it needed to act. It needed elevated privileges to do the job.
Offline-first behavior on iOS is not a cache toggle. It is a persistence decision that makes the device store the place where screens read, edits land, and state survives launch interruptions, suspension, and connectivity loss. Apple describes Core Data as a framework for saving permanent data for offline use on a single device, while SwiftData organizes persistent models around a ModelContainer and ModelContext that manage storage and lifecycle.
For the last decade, cloud cost optimization has been one of the most painful disciplines in enterprise technology. Every CTO, CIO, Head of Engineering, platform leader, and FinOps team knows the story.
MERN Stack Alternatives: Top Choices of 2026 Simplilearn.com
pgvector turns Postgres into a vector store; Prisma Next makes it type-safe. Build working semantic search on a temporary Prisma Postgres database in minutes.
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