Updates and recent posts about GPT-5.4..

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@goutham-annem started using tool Amazon ECS , 7 hours, 44 minutes ago.

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@eon01 gave 🐾 to The unwritten laws of software engineering , 10 hours, 48 minutes ago.

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@varbear shared a link, 13 hours ago

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Build and Deploy a Remote MCP Server to GKE in 30 Minutes

Google walks you through shipping a remoteMCP serveronGKE AutopilotusingFastMCPandstreamable-http, swapping localstdiofor shared HTTP endpoints. The clever bit: theGateway APIhandles managed SSL plusCLIENT_IP session affinity, so one centralized server beats everyone running redundant local copies... read more

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@varbear shared a link, 13 hours ago

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The unwritten laws of software engineering

- Always related - first rollback, then debug. - Backups aren’t real until restored. - You’ll hate yourself for bad logs. - ALWAYS have a rollback plan. - Every external dependency will fail. - If there's risk, use the “4 eyes” rule. - Nothing lasts like a temporary fix... read more

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@varbear shared a link, 13 hours ago

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How building an HTML-first site doubled our users overnight

Building HTML-first forms using Astro instead of React dramatically increased completion rates and sustainability, highlighting the effectiveness of lightweight, accessible web components for all users, regardless of browser or connectivity... read more

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@varbear shared a link, 14 hours ago

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Everything a Senior Engineer Needs to Know About What's Inside an LLM

The shift from RNNs totransformerssolved sequential bottlenecks and long-range decay issues withself-attention. Transformers use encoding, decoding, and tokenization to process sequences efficiently and accurately. This evolution led to models like GPT, which excel at tasks with minimal fine-tuning .. read more

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@varbear shared a link, 14 hours ago

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Google hits 50% IPv6

The 50% IPv6 milestone is real, but adoption differs by country. Analysts who report lower figures use population-weighted sampling, while their per-country adoption rates match the higher estimate... read more

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@varbear shared a link, 14 hours ago

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Building in the Age of Collaborative Coding

The speed of innovation is crucial for teams, and AI tools have enabled faster work. A collaborative coding model where teams build, review, and ship alongside AI agents is key to staying ahead in workflows. Three shifts have reshaped how teams build, leading to the adoption of a new collaborative c.. read more

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@kaptain shared a link, 14 hours ago

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Tigera introduces unified control plane for Kubernetes-based AI agent security

Tigera launched Lynx for general availability, a Kubernetes-native control plane that operators place in the path of AI agent calls so teams can enforce identity and policy... read more

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@kaptain shared a link, 14 hours ago

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Kubernetes QoS vs. Linux Cgroups: The Mixed-Resource Pod Risk

Designing Kubernetes manifests with mixed configurations can lead to unpredictability in how resources are managed between containers. This is due to the different ways Kubernetes and Linux handle requests, limits, and OOM situations. To avoid operational risks and ensure stability, it is crucial to.. 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.