Exploring Next
Full archive →Episodes on the research, tools, companies, and ideas shaping what comes next.
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EP 1113 AgentsAI SafetyAgent Trust HubClawhubAartsTool Use And Function CallingAgentic LoopsPrompt InjectionBlog
You Gave Your AI Agent Access, But Who Is Giving It Orders?
AI agent security risks stem from authority confusion—untrusted content issuing commands to software that already has user permissions—rather than model alignment failures.
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EP 1112 InferenceDev ToolsLlama CppQwenOllamaMixture Of ExpertsKV CacheQuantizationSparse ActivationModel RoutingInference OptimizationBlog
I changed one llama.cpp flag, and my 8GB laptop GPU now runs a 35B model faster than I can read
8GB of VRAM isn't the bottleneck, your settings probably are
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EP 1111 New ModelsDev ToolsLaunchOpenAIGpt 6 LunaStructured OutputToken EconomicsAgentic LoopsTool Use And Function CallingAPI Docs
Build more responsive apps with the Decisions API
Fast, focused, low-cost decisions for any application.
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EP 1110 AgentsDev ToolsLaunchVercelClaudeOpenAIAgentic LoopsState Management In Language ModelsDurable ExecutionRetry Loops And Error RecoveryAppend Only LoggingState SerializationTool Use And Function CallingTool
Vercel Open-Sources durable-harness for Crash-Proof Coding Agents
Vercel released durable-harness, an open-source package that logs every model and tool call so Pi, OpenCode, Claude Code and Codex sessions resume after crashes, timeouts and redeploys on Vercel, Postgres or a laptop.
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EP 1109 AgentsDev ToolsLaunchClaude DuetAnthropicAgentic LoopsTool Use And Function CallingState Management In Language ModelsDurable ExecutionClassifierCalibrationResearch Paper
Introducing Claude Duet
Claude Duet is a new app where Claude works as a proactive agent. The research preview opens by waitlist today for Pro and Max subscribers in the US.
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EP 1108 Dev ToolsOpenAICodexBlog
What FDE means at OpenAI
What forward deployed engineering means at OpenAI
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EP 1107 New ModelsInferenceLaunchRecursiveFlintMixture Of ExpertsQuantizationKnowledge DistillationSparse ActivationTask DecompositionContext WindowTool Use And Function CallingBlog
Introducing Flint - Recursive
Recursive self-improving superintelligence to automate knowledge discovery.
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EP 1106 AgentsTrainingScholarevolveQwen3 5 27bGpt 4o MiniAgentic LoopsTool Use And Function CallingState Management In Language ModelsRetrieval Augmented GenerationTask DecompositionPrompt EngineeringFine Tuning On Execution TracesResearch Paper
Learning from Research: Toward Lifelong Agent Harness Evolution
Language agents are expected to solve increasingly complex tasks, creating a growing need for continual improvement. One promising approach is to evolve the agent harness, the software that governs tool use, memory management, and task execution, while keeping the underlying language model fixed. Recent methods automate this process by using a meta coding agent to modify the harness based on execution feedback. However, relying on that agent's existing knowledge and observed failures can
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EP 1105 AI SafetyDev ToolsOpenAIGpt 6 AstraModel RoutingAnomaly DetectionBlog
Broad access through consistent standards
How OpenAI works with distribution partners to uphold consistent safeguards, support responsible access, and clarify expectations in our Usage Policies.
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EP 1104 AgentsAgent ObservabilityLaunchCtgtConcordanceQwenAgentic LoopsState Management In Language ModelsDeterministic InferencePrompt InjectionStructured OutputModel InterpretabilityNews
CTGT releases open source tool Concordance to trace why AI agents make inconsistent decisions
CTGT replaced the identifiers with stable labels, sorted the list and isolated each test in a fresh organizational environment. Five subsequent runs each produced the same 34 obligations.
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EP 1103 Agent ObservabilityDev ToolsLaunchConcordanceBoundarymlLlama 2Prompt EngineeringIn Context LearningState Management In Language ModelsResearch Paper
Deterministic Inference Did Not Make Our Pipeline Deterministic
We ran one synthetic banking manual through our pipeline four times and got four different sets of obligations, from a model that returned identical text for identical requests.
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EP 1102 AgentsAgent ObservabilityVijilTool Use And Function CallingState Management In Language ModelsAgentic LoopsConstraint VerificationRetry Loops And Error RecoveryAppend Only LoggingBlog
From feral to fiduciary: making AI agents serve your interests
Vijil argues AI agents should earn autonomy like credit: tested up front, capped by policy, and monitored constantly. Without that, they go feral.
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EP 1101 Model Behavior New ModelsInferenceNvidia Nemotron 3 5 Super VlReflection BeamAnthropicMixture Of ExpertsFine TuningContext WindowRetrieval Augmented GenerationTool Use And Function CallingAgentic LoopsState Management In Language ModelsQuantization
Model Behavior: Week of October 19, 2026
NVIDIA's Nemotron 3.5 Super VL, Beam's open-weight deployment story, and whether Subquadratic Snap's long-context claims actually reduce agent brittleness—the week's real motion was adoption, not benchmark crowns.
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EP 1100 AgentsAgent ObservabilityClaudeGpt 5GeminiAgentic LoopsTool Use And Function CallingState Management In Language ModelsContext Window ManagementTask DecompositionRetry Loops And Error RecoveryTool
From Microservices to Agents: the Next Evolution of Distributed Systems
The article examines the transition from microservices to agentic AI architecture in distributed systems. Microservices allow for functional decomposition, while agentic systems focus on decision decomposition. This shift introduces new complexities in observability, reliability, and system design, highlighting the need for updated architectural patterns and practices.
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EP 1099 InferenceAgentsLaunchLLM DIBM ResearchGlm 5 2KV CacheAgentic LoopsContext WindowMixture Of ExpertsState Management In Language ModelsInference OptimizationBlog
llm-d 1.0 Advances Open, Cost-Efficient AI Inference for Production Scale
Founded in 2025 by Red Hat, IBM (NYSE: IBM), Google Cloud, CoreWeave and NVIDIA, and now governed by the Cloud Native Computing Foundation (CNCF), llm-d plays a key role in the open foundation for enterprises deploying AI at scale in production.
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EP 1098 AgentsAgent ObservabilityCollibraVenturebeatAgentic LoopsState Management In Language ModelsToken EconomicsContext WindowConstraint VerificationAppend Only LoggingState SerializationNews
Scaling AI agents requires inventory, contracts and maintained context
As AI agent fleets grow, enterprises need inventory, enforceable contracts and maintained business context to control risk, cost and reliability.
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EP 1097 New ModelsInferenceLaunchMistralTimestralChronosSynthetic Data Generation For ValidationFine TuningAttention MechanismAutoregressive GenerationInference OptimizationAnomaly DetectionAgentic LoopsBlog
Timestral: Mistral's time-series foundation models | Mistral
State-of-the-art probabilistic forecasting in four sizes (5M–209M params), CPU-efficient, zero-shot ready.
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EP 1096 New ModelsInferenceLaunchInceptionMercury 3OpenAIDiffusion ModelsAutoregressive GenerationAgentic LoopsTool Use And Function CallingInference OptimizationContext WindowBlog
Diffusion at Scale: Introducing Mercury 3 – Inception
Mercury 3 is the most capable diffusion LLM released to date. It outperforms GPT-6 Luna and Claude Haiku 5.5 while running 4–8x faster at 1,000+ tokens per second.
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EP 1095 InferenceDev ToolsLaunchJevTypesafe AIDatabricksStructured OutputCalibrationModel RoutingEntity ResolutionRetrieval Augmented GenerationFine TuningNews
Decision models like Jev handle what SQL rules cannot. Here's how data teams use them
Decision models like Jev return typed labels with confidence scores instead of text, positioning them as a cost-effective middle layer between SQL rules and full LLM calls for high-volume classification tasks in data pipelines.
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EP 1094 InferenceDev ToolsLaunchNvidia DoryLlama CppOllamaKV CacheQuantizationContext WindowBlog
NVIDIA Dory 1.0 4B on a Mac: 3.7GB Fits 16GB, Fork Build Needed
NVIDIA's smallest Dory 1.0 4B build is a 3.673 GB Q5_K_M GGUF, so memory is settled on every current Mac. The blocker is software: no llama.cpp release reads the Dory architecture, so you build a pinned contributor fork.
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EP 1093 AgentsNew ModelsLaunchDeepseekDeepseek V4 1 FlashClaude Opus 5Mixture Of ExpertsTransformer ArchitectureReinforcement Learning From Human FeedbackRetrieval Augmented GenerationTool Use And Function CallingAgentic LoopsToken EconomicsAPI Docs
DeepSeek Just Released V4.1-Flash-1017, Scores 77.0 on DeepSWE, Opens Search API
DeepSeek has just released DeepSeek-V4.1-Flash-1017, a new checkpoint of its V4.1-Flash model. It is live on the DeepSeek website, app and API. DeepSeek claims stronger scores, faster task completion and shorter outputs than the September V4.1-Flash release. The company calls it a Pareto improvement in performance and cost. Alongside it, DeepSeek opened its Search and […]
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EP 1092 AgentsAgent ObservabilityGoogle ResearchHarness2Agentic LoopsTool Use And Function CallingState Management In Language ModelsPrompt EngineeringTask DecompositionFeedback LoopsResearch Paper
Harness^2: Recursive Agent Harnessing for an Open World
LLM agents' capabilities depend not only on their underlying models but also on their execution harnesses. Recursive self-improvement (RSI) offers a promising approach to automatically evolve these harnesses. However, deploying RSI in open-world settings still faces two critical challenges. First, open-world tasks are typically unseen during the harness design phase and novel at test time, leaving no ground-truth verifiers to reliably guide online harness edits. Second, the RSI process remains
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EP 1091 AnthropicBlog
Investing in the public benefit
We’re committing a portion of Anthropic’s shares to the Anthropic Public Benefit Fund, a new entity with a structure that increases the stake as the company grows.
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EP 1090 AI SafetyAnthropicResearch Paper
The AI expectations gap
How will AI reshape the economy in the years ahead? What is the core source of disagreement about AI's future impact on the economy? This note presents new survey evidence on these questions.
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EP 1089 AgentsDev ToolsLaunchHarkMuseInstinctTool Use And Function CallingAgentic LoopsState Management In Language ModelsNews
Hark releases an AI personal assistant with a focus on privacy | TechCrunch
The AI lab's personal assistant is an operating system from the future designed to compete with Muse, Dots, and Instinct.
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EP 1088 AgentsInferenceGartnerClaude OpusClaude FableAgentic LoopsTool Use And Function CallingContext Window ManagementRetry Loops And Error RecoveryModel RoutingToken EconomicsFine TuningNews
Gartner says agent costs will rise fivefold by 2028 even as tokens get cheaper. Here is how to keep them in check
Gartner forecasts agentic AI inference costs will rise fivefold by 2028 despite falling token prices, driven by agents consuming 5-30x more tokens per task than chatbots and labs reinvesting efficiency gains into costlier frontier models.
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EP 1087 New ModelsInferenceLaunchReflection BeamDeepseek V4Meta Muse GlimmerMixture Of ExpertsQuantizationSupervised Fine TuningReinforcement Learning From Human FeedbackContext WindowAgentic LoopsGitHub
Welcome Beam: a 501B open model you can own, customize, and scale
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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EP 1086 New ModelsAgentsLaunchBeamReflectionMirrorMixture Of ExpertsSpeculative DecodingAgentic LoopsTool Use And Function CallingReinforcement Learning From Human FeedbackLow Rank AdaptationKnowledge DistillationBlog
Beam is now available — Reflection
Make intelligence open and accessible to all
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EP 1085 Data InfraSynthetic Data Generation For ValidationBlog
Only 34% trust synthetic data's referential integrity — and it’s holding adoption back
Only 34% of leaders trust synthetic data's referential integrity. Learn how high data quality unlocks adoption in enterprise testing.
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EP 1084 AI SafetyEvalsAnthropicMetrClaudeBlog
Anthropic update on independent evaluators
Anthropic announces updates to embedding independent evaluators
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