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
Updates and recent posts about GPT-5.4.. Link
Link
@faun shared a link, 1 year, 1 month ago
FAUN.dev()
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
Link
@faun shared a link, 1 year, 1 month ago
FAUN.dev()
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
Link
@faun shared a link, 1 year, 1 month ago
FAUN.dev()
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
Link
@faun shared a link, 1 year, 1 month ago
FAUN.dev()
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
Link
@faun shared a link, 1 year, 1 month ago
FAUN.dev()
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
Link
@faun shared a link, 1 year, 1 month ago
FAUN.dev()
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
Link
@faun shared a link, 1 year, 1 month ago
FAUN.dev()
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
Link
@faun shared a link, 1 year, 1 month ago
FAUN.dev()
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
Link
@faun shared a link, 1 year, 1 month ago
FAUN.dev()
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
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.
