Top 5 LLM APIs on a Tight Budget
Choosing an API for production or prototype work when money is tight means balancing per-call price, model capability, latency, and operational overhead. This list prioritizes practical cost per unit...
Read more →Blog
Perspectives on recent AI research and what matters in practice.
The Tradeoffs in Hallucination Mitigation Strategies When Cost Matters
Hallucinations are not just a technical nuisance. They are a business and product risk. Reducing them costs money and time, and different mitigation techniques trade off compute, latency, engineering...
Read more →Why Most Teams Get LLM Caching Strategies Wrong for Solo Developers
Most guidance on caching LLM results assumes production traffic, multi-person teams, and fixed SLAs. Solo developers do not operate under those constraints. They trade off developer velocity, cost con...
Read more →Queen-Bee Agents: A BeeSpec-Centered Architecture for Governed Enterprise MCP Orchestration
•arXiv: 2606.06545
Title: Queen-Bee: A Practical Architecture for Governed Multi-Agent Orchestration...
Read more →Paper: Queen-Bee Agents: A BeeSpec-Centered Architecture for Governed Enterprise MCP Orchestration
The Most Overlooked LLM Orchestration Tools for Regulated Industries
Regulated industries impose requirements that change how teams build LLM systems: auditable decisions, end-to-end data lineage, human-in-the-loop checkpoints, strict access controls, and reproducible...
Read more →The Most Important LLM Inference Engines When Accuracy Matters
When accuracy is the primary requirement, choosing an inference engine is not just about speed or cost. Different runtimes implement differently optimized kernels, numerical precisions, quantization s...
Read more →POIROT: Interrogating Agents for Failure Detection in Multi-Agent Systems
•arXiv: 2606.02282
Title: Agents Auditing Agents: Practical takeaways from POIROT...
Read more →Paper: POIROT: Interrogating Agents for Failure Detection in Multi-Agent Systems
Why Most Teams Get AI Project Failure Modes Wrong in 2026
Teams are still treating AI projects like models to be tuned instead of systems to be operated. In 2026 the technology changed: foundation models, retrieval-augmented systems, multi-model orchestratio...
Read more →Fighting Numerical Hallucinations via Data-centric Compilation for Online Financial QA
•arXiv: 2605.31064
Title: Compiling Numeric Answers: Practical takeaways from a data-centric compiler for financial QA...
Read more →Paper: Fighting Numerical Hallucinations via Data-centric Compilation for Online Financial QA
Towards trustworthy agentic AI: a comprehensive survey of safety, robustness,...
•arXiv: 2605.23989
Title: Practical trust for agentic AI: what this new survey gets right and what still needs work...
Read more →Paper: Towards trustworthy agentic AI: a comprehensive survey of safety, robustness, privacy, and system security
Efficient and Transferable Agentic Knowledge Graph RAG via Reinforcement Learning
•arXiv: 2509.26383
Title: Training one agent to query knowledge graphs: what KG-R1 gets right and what still matters in production...
Read more →Paper: Efficient and Transferable Agentic Knowledge Graph RAG via Reinforcement Learning
Runtime-Certified Bounded-Error Quantized Attention
•arXiv: 2605.20868
Runtime-Certified KV Cache Quantization for Safe Long-Context Inference...
Read more →Paper: Runtime-Certified Bounded-Error Quantized Attention
EngiAI: A Multi-Agent Framework and Benchmark Suite for LLM-Driven Engineering...
•arXiv: 2605.19743
Title: What EngiAI Gets Right About Multi-Agent Engineering Workflows, and Where it Still Falls Short...
Read more →Paper: EngiAI: A Multi-Agent Framework and Benchmark Suite for LLM-Driven Engineering Design
Multi-Paradigm Agent Interaction in Practice:A Systematic Analysis of Generator-Evaluator, ReAct...
•arXiv: 2605.16821
Title: Building Multi-Paradigm Agent Systems that You Can Operate...
Read more →Paper: Multi-Paradigm Agent Interaction in Practice:A Systematic Analysis of Generator-Evaluator, ReAct Loop,and Adversarial Evaluation in the buddyMe Framework
AgenticAITA: A Proof-Of-Concept About Deliberative Multi-Agent Reasoning for Autonomous Trading...
•arXiv: 2605.12532
Title: Deliberative Multi-Agent LLMs for Trading: a Practical Look at AgenticAITA...
Read more →Paper: AgenticAITA: A Proof-Of-Concept About Deliberative Multi-Agent Reasoning for Autonomous Trading Systems
Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward Modeling
•arXiv: 2604.08178
Title: Trajectory-Level Reward Models and What Plan-RewardBench Gets Right...
Read more →Paper: Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward Modeling
A Self-Healing Framework for Reliable LLM-Based Autonomous Agents
•arXiv: 2605.06737
Title: Self-healing LLM agents in practice: what this paper gets right and what it leaves hanging...
Read more →Paper: A Self-Healing Framework for Reliable LLM-Based Autonomous Agents
E-mem: Multi-agent based Episodic Context Reconstruction for LLM Agent Memory
•arXiv: 2601.21714
Title: Episodic Context Reconstruction with E-mem: promising idea, hard systems work...
Read more →Paper: E-mem: Multi-agent based Episodic Context Reconstruction for LLM Agent Memory
Bian Que: An Agentic Framework with Flexible Skill Arrangement for...
•arXiv: 2604.26805
Title: Bian Que and the Practicalities of LLM Agents for Online Operations...
Read more →Paper: Bian Que: An Agentic Framework with Flexible Skill Arrangement for Online System Operations
EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce
•arXiv: 2604.23993
Title: Training an on-prem product-matcher from agentic reasoning with RL...
Read more →Paper: EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce
Memanto: Typed Semantic Memory with Information-Theoretic Retrieval for Long-Horizon Agents
•arXiv: 2604.22085
Title: Memanto and the memory trade-offs you actually care about in production agents...
Read more →Paper: Memanto: Typed Semantic Memory with Information-Theoretic Retrieval for Long-Horizon Agents
Automatic Ontology Construction Using LLMs as an External Layer of...
•arXiv: 2604.20795
Title: Using Ontologies as an External Memory for LLMs: Practical gains and the engineering work it hides...
Read more →Paper: Automatic Ontology Construction Using LLMs as an External Layer of Memory, Verification, and Planning for Hybrid Intelligent Systems
Agentic Large Language Models for Training-Free Neuro-Radiological Image Analysis
•arXiv: 2604.16729
Title: Agentic LLMs for Brain MRI Workflows: a practical take on a training-free pipeline...
Read more →Paper: Agentic Large Language Models for Training-Free Neuro-Radiological Image Analysis
SocialGrid: A Benchmark for Planning and Social Reasoning in Embodied...
•arXiv: 2604.16022
Title: SocialGrid: separating planning from social reasoning in embodied multi-agent tests...
Read more →Paper: SocialGrid: A Benchmark for Planning and Social Reasoning in Embodied Multi-Agent Systems
A 3D SAM-Based Progressive Prompting Framework for Multi-Task Segmentation of...
•arXiv: 2604.13367
Title: Adapting SAM to 3D for radiotherapy injury segmentation: promising method, practical gaps...
Read more →Paper: A 3D SAM-Based Progressive Prompting Framework for Multi-Task Segmentation of Radiotherapy-induced Normal Tissue Injuries in Limited-Data Settings
Development, Evaluation, and Deployment of a Multi-Agent System for Thoracic...
•arXiv: 2604.12161
Title: Automating Tumor Board Summaries: a useful engineering step, not a finished clinical tool...
Read more →Paper: Development, Evaluation, and Deployment of a Multi-Agent System for Thoracic Tumor Board
Fairboard: a quantitative framework for equity assessment of healthcare models
•arXiv: 2604.09656
Title: Fairboard and the hard truths about equity in medical imaging models...
Read more →Paper: Fairboard: a quantitative framework for equity assessment of healthcare models
Extracting Breast Cancer Phenotypes from Clinical Notes: Comparing LLMs with...
•arXiv: 2604.06208
I read arXiv:2604.06208 with the kind of skepticism I bring to most papers that compare large language models with established knowledge-driven approaches. The authors set out to extract breast cancer...
Read more →Paper: Extracting Breast Cancer Phenotypes from Clinical Notes: Comparing LLMs with Classical Ontology Methods
LLMs-Healthcare : Current Applications and Challenges of Large Language Models...
•arXiv: 2311.12882
Title: LLMs in healthcare: a broad survey that skips the deployment hard parts...
Read more →Paper: LLMs-Healthcare : Current Applications and Challenges of Large Language Models in various Medical Specialties
An Explainable Vision-Language Model Framework with Adaptive PID-Tversky Loss for...
•arXiv: 2604.02502
Title: An Explainable Vision-Language Framework for Lumbar Spinal Stenosis: Promising ideas, clinical hurdles...
Read more →Paper: An Explainable Vision-Language Model Framework with Adaptive PID-Tversky Loss for Lumbar Spinal Stenosis Diagnosis
BioCOMPASS: Integrating Biomarkers into Transformer-Based Immunotherapy Response Prediction
•arXiv: 2604.00739
Title: Aligning biomarkers with transformer representations to improve immunotherapy response prediction...
Read more →Paper: BioCOMPASS: Integrating Biomarkers into Transformer-Based Immunotherapy Response Prediction
Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification
•arXiv: 2506.04450
Title: Differentially Private LoRA for Radiology Reports: a useful step, not a panacea...
Read more →Paper: Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification
Causal Graph Neural Networks for Healthcare
•arXiv: 2511.02531
Title: Causal Graph Neural Networks for healthcare: useful idea, but not a turnkey fix...
Read more →Paper: Causal Graph Neural Networks for Healthcare
From Physician Expertise to Clinical Agents: Preserving, Standardizing, and Scaling...
•arXiv: 2603.23520
Title: Encoding master physicians into a small LLM: what Med-Shicheng gets right and where it still falls short...
Read more →Paper: From Physician Expertise to Clinical Agents: Preserving, Standardizing, and Scaling Physicians' Medical Expertise with Lightweight LLM
Cerebra: A Multidisciplinary AI Board for Multimodal Dementia Characterization and...
•arXiv: 2603.21597
Cerebra: a practical look at a multimodal AI board for dementia risk and diagnosis...
Read more →Paper: Cerebra: A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment
A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk...
•arXiv: 2603.21597
Title: A Practical Look at Cerebra: Multi-agent Multimodal AI for Dementia Risk and Diagnosis...
Read more →Paper: A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment
The Validity Gap in Health AI Evaluation: A Cross-Sectional Analysis...
•arXiv: 2603.18294
Title: The Validity Gap in Health‑LLM Benchmarks: Composition Matters...
Read more →Paper: The Validity Gap in Health AI Evaluation: A Cross-Sectional Analysis of Benchmark Composition
Deployment and Evaluation of an EHR-integrated, Large Language Model-Powered Tool...
•arXiv: 2603.17234
Title: Using an LLM to triage surgical patients in the EHR: promising results, practical gaps...
Read more →Paper: Deployment and Evaluation of an EHR-integrated, Large Language Model-Powered Tool to Triage Surgical Patients
TheraAgent: Multi-Agent Framework with Self-Evolving Memory and Evidence-Calibrated Reasoning for...
•arXiv: 2603.13676
Title: TheraAgent's promise and limits: multi-agent memory and trial-calibrated reasoning for PET theranostics...
Read more →Paper: TheraAgent: Multi-Agent Framework with Self-Evolving Memory and Evidence-Calibrated Reasoning for PET Theranostics