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Fueling the Agentic Web Revolution with NLWeb and PostgreSQL

Microsoft just leveled upNLWeb. The open-source project now plays nice withPostgreSQLandpgvector, bringing scalable vector similarity search straight into your database. No need for a separate vector DB—run natural language interfaces right on your existing Postgres stack. System shift:This is more.. read more  

Fueling the Agentic Web Revolution with NLWeb and PostgreSQL
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This New AI is 100x Faster at Reasoning Than ChatGPT

Sapient Intelligence’s HRM AI model challenges “bigger is better” in AI with a small 27M parameter design outperforming much larger models on reasoning tasks. The architecture mimics the brain, with a slow “planner” and rapid “worker,” achieving jaw-dropping results on benchmarks... read more  

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AWS deleted my 10-year account and all data without warning

AWS permanently nuked a 10-year customer account—data, backups, everything—after a payment verification failed. That alone broke their own 90-day retention policy. It gets messier. Looks like an internal script meant to run as a “dry run” went full send in production. Blame a Java CLI parsing edge .. read more  

AWS deleted my 10-year account and all data without warning
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A practical guide on how to use the GitHub MCP server

GitHub offers a managed MCP endpoint to simplify infrastructure management and streamline AI workflows, enhancing collaboration and code review processes... read more  

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Does platform engineering make sense for startups?

Platform engineering isn't just for the big dogs anymore. Startups are picking it up as astrategic edge, building tight, high-leverage tooling from day one. Think:templated CI/CD pipelines, plug-and-play infra modules, zero-handoff onboarding. Done right, these early bets smooth the path and keep d.. read more  

Does platform engineering make sense for startups?
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Proton launches free standalone cross-platform Authenticator app

Proton just droppedProton Authenticator, a free 2FA app that actually respects your privacy. It’s cross-platform, offline-friendly, and skips the usual junk—no ads, no trackers, no bait-and-lock-in. It’s gotend-to-end encryption, a biometric lock, and lets youexport TOTP seedslike it’s your data (b.. read more  

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How to use Terraform to generate secrets

Terraform just leveled up secret handling inAzure Key Vault. It now supports automated secret generation withrandom_password, plus full lifecycle control—rotation, expiration, and storage—baked right into your IaC. Secrets stay marked as sensitive. They're managed in one place. And thanks to Terraf.. read more  

How to use Terraform to generate secrets
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We built an MCP server so Claude can access your incidents

Incident.io dropped an open sourceMCP server in Gothat plugs Claude into their API using theModel Context Protocol. That means Claude can now ask questions, spin up incidents, and dig into timelines—just by talking. The server translates Claude’s prompts into REST calls, turning AI babble into real.. read more  

We built an MCP server so Claude can access your incidents
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AWS Lambda now supports GitHub Actions to simplify function deployment

AWS Lambda just got a smoother ride to prod. There’s now a nativeGitHub Actions integration—no more DIY scripts to ship your serverless. On commit, the new action packages your code, wires up IAM viaOIDC, and deploys using either.zip bundles or containers. All from a tidy, declarative GitHub workfl.. read more  

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Who does the unsexy but essential work for open source?

Oracle led the line-count race in the Linux 6.1 kernel release—beating out flashier open source names. Most of its work isn’t headline material. It’s deep-core stuff: memory management tweaks, block device updates, the quiet machinery real systems run on... read more  

Who does the unsexy but essential work for open source?
GPT (Generative Pre-trained Transformer) is a deep learning model developed by OpenAI that has been pre-trained on massive amounts of text data using unsupervised learning techniques. GPT is designed to generate human-like text in response to prompts, and it is capable of performing a variety of natural language processing tasks, including language translation, summarization, and question-answering. The model is based on the transformer architecture, which allows it to handle long-range dependencies and generate coherent, fluent text. GPT has been used in a wide range of applications, including chatbots, language translation, and content generation.

GPT is a family of language models that have been trained on large amounts of text data using a technique called unsupervised learning. The model is pre-trained on a diverse range of text sources, including books, articles, and web pages, which allows it to capture a broad range of language patterns and styles. Once trained, GPT can be fine-tuned on specific tasks, such as language translation or question-answering, by providing it with task-specific data.

One of the key features of GPT is its ability to generate coherent and fluent text that is indistinguishable from human-generated text. This is achieved by training the model to predict the next word in a sentence given the previous words. GPT also uses a technique called attention, which allows it to focus on relevant parts of the input text when generating a response.

GPT has become increasingly popular in recent years, particularly in the field of natural language processing. The model has been used in a wide range of applications, including chatbots, content generation, and language translation. GPT has also been used to create AI-generated stories, poetry, and even music.