Manifest Weekly #05
Manifest now works with any AI agent, routing by task type, two new subscription providers, and Docker-only self-hosting.
5,369 stories
Manifest now works with any AI agent, routing by task type, two new subscription providers, and Docker-only self-hosting.
Learn AI for incident management step by step: data prep, workflow design, human oversight, and KPIs like MTTR, MTTA, and alert reduction.
Early results from MirrorCode benchmark with METR: AI agents can complete weeks-long coding tasks, including reimplementing a 16,000-line codebase.
Learn what MMLU, GPQA Diamond, SWE-bench, HealthBench, and Chatbot Arena actually measure, and how labs game benchmark scores.
How we built a two-stage prompt injection classifier that achieves 0.99 F1 with sub-10ms latency.
L'articolo Build AI Agents That Take Action Using MCP: 5 Practical Business Use Cases proviene da Tiledesk.
How to give AI agents access to fast, state-of-the-art remote browsers.
Getting started with AI agents doesn’t have to be complex. Start with simple workflows like inbox summaries and follow-ups, and build from there.
Developer audiences hate generic AI content. Here's a content workflow that turns community mentions and a social listening API into original technical content at scale.
A public, weekly view of AI agent adoption and turn times inside Zed, plus a few patterns worth watching.
Most AI agent tutorials make the same mistake: they route every task to the most expensive model available. A character count doesn't need GPT-4. A presence check doesn't need Sonnet. A regex doesn't
ACP lets you keep your favorite editor but swap the AI agent, or keep your agent but use it from any editor. Here's what actually works today in Goose.
How AI in DevOps replaces manual server work with AI terminals, approval-based commands, and real-time monitoring. Save 80% time.
Learn what AI tokens are, why Claude hits limits fast, and how to cut waste from context windows, history, files, tools, and reasoning.
From fabricated case law to billion-dollar reversals, a three-year history of AI adoption and why the tools that worked kept a professional in the loop.
The “one god‑agent that does everything” sounds cool but fails in production. A small team of focused assistants—powered by Clawdi—works much better.
Updates to the Model Context Protocol (MCP) governance team: a new Lead Maintainer and an addition to the Core Maintainer group as the open-source project continues to grow.
AI for cross-department communication made simple. Centralize knowledge, automate handoffs, and measure ROI with a step-by-step rollout plan.
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