5 Fun Projects for LLM Inference Engineering
Want to understand what makes LLMs fast? Build the systems yourself.
1,978 stories
Want to understand what makes LLMs fast? Build the systems yourself.
Learn how to build a 7-step social media workflow to simplify content planning, approvals, scheduling, automation, and reporting.
Point ANTHROPIC_BASE_URL at DeepSeek, Kimi, GLM or Ollama, set all four model tiers, test with curl and /status. Check the cache before the bill.
Build a Python pipeline that answers questions from PDFs and links each answer to its page, then check the citations before you trust them.
<ul><li>Bundled CLI v0.1.11: Claude Code and Codex <b>tool calls</b> — built-in tools, MCP tools and the programs a shell command runs — and <b>prompts</b> are recorded, so the dashboard shows which tools agents use and how long each question took.
Dograh and Retell AI compared row by row: open source, self-hosting and on-prem, platform fees, models, telephony, transfer and QA, with list prices.
A roundup of Retell AI alternatives, hosted and open source, with list prices from each vendor's page, where each one can run, and who should stay on Retell.
A step-by-step move from Retell AI to Dograh: read agents from Retell's API, rebuild the flow, re-point webhooks, test, then take numbers off Retell's trunk.
Here’s what 520 enterprise AI leaders told us about getting locked into frontier labs TL;DR. The technical leaders responsible for AI adoption say vendor lock-in worries them, and many have …
Prompt injection turns AI agents against their owners. Learn direct and indirect attacks, real exploits like EchoLeak and GitHub MCP, and the containment defenses that actually hold up.
In Model Context Protocol (MCP) systems, LLMs select tools from metadata rather than from their implementations. Names and descriptions summarize what a tool does, while the parameter schema specifies the fields a tool accepts and how they are organized.
Enterprise customer-support agents increasingly rely on Large Language Models (LLMs) to execute bounded, tool-using workflows. We study this problem through the lens of Skill LLMs: specialized executors that operate within a selected skill context and must complete a narrow, stateful workflow under…
Build apps that see the world, understand what’s happening, and take action. Roboflow Agent is an assistant for computer vision that takes you from idea to working solution, from choosing models to plugging the system into your business.
Most tutorials on how to build an AI agent hand you code or lock you into one vendor's tool. Here's a path that still works next year.
AWS Agent Registry is the centralized, governed catalog for agents, MCP servers, agent skills, gateways, and custom resources within your organization. As organizations scale to hundreds of such resources, a name and description alone are insufficient for effective governance and discovery.
Learn how the AWS Generative AI Innovation Center Partner Agent Factory and Anchor Browser built AI agents that autonomously pay for x402-protected web resources and APIs.
Learn how Orange Business used LangChain and LangSmith to build Live Intelligence, a governed AI platform for agents, evals, observability, and production scale.
Here is Gemini 4 Argon explained in 3 points that get increasingly niche. First is a strong understanding of 3D space and visuals. A lady took pictures of her desk, and Argon turned them into a playable racing game with Blender MCP and Three.js.
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