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A DOGE recruiter is staffing a project to deploy AI agents across the US government

Anthony Jancsoaims to unleashAI agentson more than 300 tasks across federal fronts. Translation: watch out, 70k jobs might vanish. Unsurprisingly, not everyone's cheering; brace for the fireworks... read more  

A DOGE recruiter is staffing a project to deploy AI agents across the US government
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How To Set Up a Model Context Protocol Server

Model Context Protocol (MCP)is like that cool tool you didn't know you needed. It's a nimble bridge between LLM models and developer tools, though someday it might just become the backbone of future libraries—nothing fancy, just fundamental. EnterFastMCP, the under-the-radar hero. Fire it up, and it.. read more  

How To Set Up a Model Context Protocol Server
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Agents in your software factory: Introducing the LLM primitive in Dagger

Daggerjust cranked its engine into overdrive with nativeLLMintegration. Now, AI agents can rev through your CI/CD workflows, automating tasks like code reviews with impressive flair. The new configuration lets LLMs jive with programmable building blocks in your code, all securely sandboxed. Consider.. read more  

Agents in your software factory: Introducing the LLM primitive in Dagger
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Explainable AI Needs Explainable Infrastructure

AWS S3 choked, and prediction accuracy took a nosedive. Voilà: an uninvited reminder thatexplainable infrastructureis crucial for genuine AI transparency. It’s not just a hunch—47% of AI downtime stems from these scaffolding snafus. Luckily, warriors likeOpenTelemetryandGrafanastep up, offering a wa.. read more  

Explainable AI Needs Explainable Infrastructure
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Perplexity CEO says its browser will track everything users do online to sell 'hyper personalized' ads

Perplexity'snew browser,Comet, prowls beyond its app, sniffing out user data for targeted ads. It mirrors Google's relentless data quests. In a plot twist, they're joining forces withMotorolato sneak their app onto every Razr straight from the factory... read more  

Perplexity CEO says its browser will track everything users do online to sell 'hyper personalized' ads
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Open source AI models favor men for hiring, study finds

Open-source AI's at it again. Picks men over women. Shocking, right? EnterLlama-3.1, the rebel. It ignores gender in 6% of cases, which is a small but mighty improvement. Yet, even the upgraded models can't shake the gender wage gap. TakeMinistral, for instance, slapping an 84 log point penalty on w.. read more  

Open source AI models favor men for hiring, study finds
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How to Build an Agent

Craft a code-editing agent in under 400 lines. It's just an LLM, a loop, and some enhanced tokens. No rocket science here—just solid, hands-on engineering... read more  

How to Build an Agent
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Prompt chaining reimagined with type inference

Graceusesbidirectional type inferenceto simplify prompt chaining. No more wrestling with schema definitions. Think: less JSON, more wizardry... read more  

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ngrok is also now your Kubernetes ingress

ngrok's Kubernetes Operatortakes the tangle out of K8s networking. Picture this: labyrinthine paths shrink into tidy URLs, and traffic feels the firm hand ofTraffic Policy. Get ready forv1.0. It promises shiny, new features and bids farewell to "edges" in favor of a sleek focus on endpoints. Expect .. read more  

ngrok is also now your Kubernetes ingress
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v1.33: New features in DRA

Kubernetes Dynamic Resource Allocation (DRA)is shaking up device management. Expect tools likeDriver-owned Resource Claim Statusfor tracking device data like a hawk, andPartitionable Devicesto squeeze max juice from resources. Keep an eye out: DRA goes full throttle in v1.34, making device handling .. read more  

GPT-5.4 is OpenAI’s latest frontier AI model designed to perform complex professional and technical work more reliably. It combines advances in reasoning, coding, tool use, and long-context understanding into a single system capable of handling multi-step workflows across software environments. The model builds on earlier GPT-5 releases while integrating the strong coding capabilities previously introduced with GPT-5.3-Codex.

One of the defining features of GPT-5.4 is its ability to operate as part of agent-style workflows. The model can interact with tools, APIs, and external systems to complete tasks that extend beyond simple text generation. It also introduces native computer-use capabilities, allowing AI agents to operate applications using keyboard and mouse commands, screenshots, and browser automation frameworks such as Playwright.

GPT-5.4 supports context windows of up to one million tokens, enabling it to process and reason over very large documents, long conversations, or complex project contexts. This makes it suitable for tasks such as analyzing codebases, generating technical documentation, working with large spreadsheets, or coordinating long-running workflows. The model also introduces a feature called tool search, which allows it to dynamically retrieve tool definitions only when needed. This reduces token usage and makes it more efficient to work with large ecosystems of tools, including environments with dozens of APIs or MCP servers.

In addition to improved reasoning and automation capabilities, GPT-5.4 focuses on real-world productivity tasks. It performs better at generating and editing spreadsheets, presentations, and documents, and it is designed to maintain stronger context across longer reasoning processes. The model also improves factual accuracy and reduces hallucinations compared with previous versions.

GPT-5.4 is available across OpenAI’s ecosystem, including ChatGPT, the OpenAI API, and Codex. A higher-performance variant, GPT-5.4 Pro, is also available for users and developers who require maximum performance for complex tasks such as advanced research, large-scale automation, and demanding engineering workflows. Together, these capabilities position GPT-5.4 as a model aimed not just at conversation, but at executing real work across software systems.