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llm
536 postsMulti-Agent Architecture Patterns for Real-World Financial Systems
Engineering patterns for safely deploying LLM agents in African microfinance systems: bounded authority gates, bias audits, and shared-state coordination across agent pipelines.
LLM agents are breaking 20-year-old web architecture
Stateful LLM agents are exposing cracks in the stateless-server-plus-database web architecture. The missing piece: a routing primitive that can address running processes directly.
The Expensive Model Was Cheaper: Six Lessons from an LLM Judge
Insights from the Rekall app reveal unexpected lessons in model selection and cost implications for engineers.
CommitBrief — AI code reviews, right in your terminal
A provider-agnostic, local-first CLI that reviews your staged changes, a historic range, or a whole GitHub pull request. Zero telemetry, no server. Free and open source.
commitbrief.comCruxible: An Open-Source Governed Truth Layer for AI Agents
Cruxible replaces unreliable text-based memory for AI agents with a deterministic, auditable state layer. Open-source, Apache-2.0 licensed, built with Python and SQLite.
A Video Editor Where the LLM Never Watches the Video
This innovative video editor enables efficient editing without LLM watching the video.
Sub-1-Bit LLM Compression: A New Approach via Latent Factorization
The LittleBit Project enhances language model efficiency through sub-1-bit compression.
When LLM Judges Agree: A Question of Trustworthiness
The independence of LLM judges is more important than majority voting. A new method aims to enhance reliability by modeling judge relationships.
Training a 3.8B LLM to 0.384 CORE for $998 – Hugo Vergnes
Hugo Vergnes trained a 3.8B parameter LLM for $998, achieving 0.384 CORE score. The project highlights the significance of a configuration-driven framework.
An Open Agent Security Benchmark: Uncaught Attacks
An open benchmark featuring 497 attacks targeting modern LLM agents has been established.
Context Engineering in LLM Applications
Context engineering optimizes LLMs with domain knowledge for better performance. It uses an index for more accurate responses.