Updates and recent posts about GPT-5.4..

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@faun shared a link, 1 year, 1 month ago

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The AI-powered DevOps revolution: Redefining developer collaboration

Aprilsteers GitHub's leap from legacy systems to serverless wonders, turning code-first DevOps into more than a buzzword. On the flip side? She tackles triathlons and communes with nature like it's nobody's business... read more

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@faun shared a link, 1 year, 1 month ago

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Persistent commit signature verification is generally available

Reviewers unlock a new superpower: commenting on push protection requests. Adds clarity. Offers context. Secret scanning just got a little less cryptic... read more

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@faun shared a link, 1 year, 1 month ago

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Enabling 1 MW IT racks and liquid cooling at OCP EMEA Summit

Google revamps its AI tech, swapping out the old wiring for+/-400 VDCjuice. Enter the fifth-genProject Deschutesliquid cooling, the latest in their mad scientist lab. The promise? A cool 1 MW per rack and uptime so reliable, you could set your watch by it—99.999%... read more

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@faun shared a link, 1 year, 1 month ago

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Run MCP Server in a Docker sandbox

MCP Proxytakes Docker's isolation to a higher plane. It sidesteps the security landmines ofnpxanduvxwhile morphing MCP intoSSE. Think of it as a clever hack against supply chain skullduggery... read more

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@faun shared a link, 1 year, 1 month ago

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Playwright MCP server to Run test and generate code.

mcp-playwrightnow handles29 MCP tool calls, whipping up Python or JS code like a true pro. Agents, remember: "startcodegensession" for scripts that don't miss a beat!.. read more

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@faun shared a link, 1 year, 1 month ago

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Do you really need a Vector Search Database?

Elasticsearchpulled a Houdini, besting the buzzed-about vector databases. It slashed costs by3xand effortlessly juggled a whopping600M embeddingslike it was born for the job... read more

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@faun shared a link, 1 year, 1 month ago

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Leveraging Chain‑of‑Thought Network Effects To Compete With Open Source Models

Open-source AImodels are hot on the heels of their proprietary cousins, speeding through life cycles that now barely stretch pastsix months. Companies caught in this sprint scramble to scale using reusableChain-of-Thought tokens—a crafty way to slice through redundant computation and chop down infer.. read more

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@faun shared a link, 1 year, 1 month ago

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Agentic AI 101: Starting Your Journey Building AI Agents

AI agents are evolving from simple chatbots into powerful, tool-using assistants capable of web search, automation, and even reasoning. This guide walks you through building your first agent using the Agno Python library—from setup and tool integration to memory and RAG features. With just a few lin.. read more

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@faun shared a link, 1 year, 1 month ago

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From MCP to multi-agents: The top 10 new open source AI projects on GitHub right now and why they matter

Get insights on the latest trends from GitHub experts while catching up on these exciting new projects... read more

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@faun shared a link, 1 year, 1 month ago

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Build a gen AI–powered financial assistant with Amazon Bedrock multi-agent collaboration

Amazon Bedrock's multi-agent frameworkacts like a brain transplant for your AI projects. It lets you unleash specialized AI agents on beastly tasks likefinancial analysis. Why rely on a lone LLM when you can have a band of them tackling the complexities of high-stakes operations? This approach zeroe.. 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.