There are only two ways to use LLMs in a computer program: as part of a pipeline, or as an agent. In other words, either you express the control flow of the program in code, or you give a LLM tools and allow it to manage the control flow itself1.
truefoundry/trueforge
The open-source agent harness - the runtime layer that turns an LLM into a working agent.
AI Agents: Key Concepts and How They Overcome LLM Limitations
An AI agent is an autonomous software entity that is often used to augment a large language model. Here's what developers need to know.
The Agent Harness
A specification for agent behavior that LLM frameworks leave undefined: error handling, context management, tool execution, and state transitions.
Multi-agentic Software Development is a Distributed Systems Problem (AGI can't save you from it)
Recently, I've been thinking a lot about scaffolding and languages for managing systems of LLMs coordinating with each other — new programming languages might be the ideal solution for this area.
Optimizing Agentic Workflows using Meta-tools
Agentic AI enables LLM to dynamically reason, plan, and interact with tools to solve complex tasks. However, agentic workflows often require many iterative reasoning steps and tool invocations,...
Adding payments to your LLM agentic workflows
This post discusses integrating the Stripe agent toolkit with large language models (LLMs) to enhance automation workflows, enabling financial services access, metered billing, and streamlined operations across agent frameworks.
LLM Agents are simply Graph — Tutorial For Dummies
Ever wondered how AI agents actually work behind the scenes?
LLM Agents are simply Graph — Tutorial For Dummies
Ever wondered how AI agents actually work behind the scenes?
If an AI agent can’t figure out how your API works, neither can your users
Discover how LLM‑powered agents act as tireless API testers—exposing friction in docs, errors, and design—and learn six essential strategies (consistency, comprehensive docs, rich errors, example‑driven tutorials, simplicity, and feedback loops) to elevate your API’s developer experience for both humans and machines alike.
I accidentally turned LLM memory into program analysis :: pwning.systems
Why I stopped trying to give LLM agents a better memory and instead built Lemmalog, a Datalog engine that maintains an agent's knowledge as analysis state, with provenance, retractions and incremental evaluation, plus what happened when I benchmarked it on LongMemEval and LoCoMo.
Agent Recipes
Explore common agent recipes with ready to copy code to improve your LLM applications.
Pieces | Infinite Artificial Memory for your Digital Workers and Agents
Pieces is your AI companion that captures live context from browsers to IDEs and collaboration tools, manages snippets and supports multiple llms - all while processing data locally for maximum control.
mesh-llm/scripts/build-llama.sh at main · Mesh-LLM/mesh-llm
Distributed AI/LLM for the people. Share compute privately or publicly to power your agents and chat. - Mesh-LLM/mesh-llm
