» Tag
llm
536 postsAI alignment research is unintentionally building a censor's toolkit
An ICML 2026 award-winning position paper shows how RLHF, pretraining filters and system prompts are already being weaponized by states and companies for censorship.
Lead Quorum: Multi-Agent Scorer That Abstains on Disagreement
Lead Quorum uses ADK and A2A to compare two independent Gemini readings, refusing to score and explaining exactly why when signals conflict.
Why Startups Shouldn't Go Direct to a Single AI Provider
Locking a startup's stack to one AI provider creates costly technical debt. OpenAI-compatible, multi-provider APIs offer a cheaper, more flexible alternative for engineering teams.
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.comSkill Retriever Brings 10K-Category Semantic Skill Discovery to Hermes
Skill Retriever maps 1,200+ skills into a 10,000-category taxonomy for Hermes Agent, surfacing the 5 most relevant skills for each query automatically.
My AI Reviewer's Real Problem Was Sequencing, Not Rules
A writer's AI-assisted editorial reviewer kept failing in new ways until distinct reasoning tasks were staged as separate passes instead of expanding the rubric.
Building Fault-Tolerant AI Agent Workflows with Temporal and CrewAI
How enterprise AI agent systems can combine Temporal's durable orchestration with CrewAI's stateless reasoning agents to survive crashes, retry safely, and gate on human approval.
Tessera: An Open-Source AI Agent Layer That Refuses Answers Without Proof
Tessera is a deterministic AI agent framework that unifies enterprise data into one knowledge graph and refuses to answer without traceable evidence.
Why LLM Apps Must Be Engineered as Distributed Systems
A production AI app broke under load—not because of the model, but missing queues, caching, retries and observability. Backend engineering is the real differentiator.
Final Token Preference Optimization Tackles Reasoning Model Doom Loops
Antidoom uses Final Token Preference Optimization to fix repetitive doom loops in reasoning models, cutting loop rates sharply in LFM2.5 and Qwen3.5 without broad model degradation.
KV Cache Quantization's Effect on KLD in Qwen3.6-27B
A KL-divergence benchmark on bartowski's Qwen3.6-27B GGUF quants (Q8/Q6/Q5) shows KV cache quantization at (q8_0,q8_0) preserves quality almost for free.