https://mr.technology/payloads Audited AI modules, deployment-ready payloads, and full blueprint stacks for deterministic, secure AI execution. en-us Wed, 03 Jun 2026 17:58:39 +0000 https://mr.technology/payloads/prompt-caching-patterns-save-money-june-2026 https://mr.technology/payloads/prompt-caching-patterns-save-money-june-2026 2026-06-03T14:00:00Z Every major LLM provider shipped prompt caching in 2024-2025. Most production stacks still pay full price on every call. Here is the structural pattern that takes 60-90% off your input-token bill, with the three rules and gotchas that decide whether it works. https://mr.technology/payloads/agent-os-wars-microsoft-mxc-nvidia-vera-june-2026 https://mr.technology/payloads/agent-os-wars-microsoft-mxc-nvidia-vera-june-2026 2026-06-03T12:05:00Z In the last 48 hours Microsoft shipped Microsoft Execution Containers at Build 2026 and NVIDIA shipped the Vera CPU plus Nemotron 3 Ultra plus NemoClaw at Computex 2026. Together they mark the moment the agent stack stopped being an application pattern and started being an operating-system pattern. https://mr.technology/payloads/opinion-ai-safety-is-theater-june-2026 https://mr.technology/payloads/opinion-ai-safety-is-theater-june-2026 2026-06-03T12:00:00Z Most of what passes for "AI safety" in 2026 is a press release function. The work being celebrated is, almost without exception, a public relations operation that lets frontier labs justify whatever they were going to do anyway. Real safety engineering doesn't get a keynote. The PDF d https://mr.technology/payloads/outlines-structured-generation-tokens-not-prompts https://mr.technology/payloads/outlines-structured-generation-tokens-not-prompts 2026-06-03T10:00:00Z Instructor and PydanticAI fix structured outputs by re-parsing whatever the model said and hoping for the best. Outlines takes a different bet: it constrains the token sampler itself, so the model physically cannot emit a byte that violates your JSON schema. That architectural difference is the most https://mr.technology/payloads/microsoft-mai-seven-models-build-2026 https://mr.technology/payloads/microsoft-mai-seven-models-build-2026 2026-06-03T08:00:00Z At Build 2026 on June 2, Microsoft launched seven homegrown MAI models — including a 1T-parameter reasoning model trained from scratch on Maia 200 silicon with zero distillation. The 10x efficiency win over GPT-5.4 on a tuned Excel model and the McKinsey numbers are the real story. The OpenAI partne https://mr.technology/payloads/tutorial_litellm_proxy_setup_june_2026 https://mr.technology/payloads/tutorial_litellm_proxy_setup_june_2026 2026-06-02T20:05:00Z Stop writing provider-specific code for OpenAI, Anthropic, and Google. LiteLLM is the open-source proxy that gives you one OpenAI-compatible endpoint for every LLM, with virtual keys and spend tracking built in. Twenty minutes from zero to a unified API. https://mr.technology/payloads/claude-opus-4-8-economics-may-2026 https://mr.technology/payloads/claude-opus-4-8-economics-may-2026 2026-06-02T20:01:00Z Anthropic shipped Claude Opus 4.8 on May 28, 2026, and the AI press is missing the real story. The 3x cheaper fast mode, the new Dynamic Workflows feature, the 61% Databricks cost reduction, and the effort-control dial collectively reshape the unit economics of running frontier AI agents in producti https://mr.technology/payloads/open_source_letta_memgpt_agent_framework_june_2026 https://mr.technology/payloads/open_source_letta_memgpt_agent_framework_june_2026 2026-06-02T20:01:00Z Most agent memory is retrieval-augmented guessing. Letta, the open-source descendant of the MemGPT paper, takes a different bet: give the LLM explicit memory-management tool calls and let it page its own context window like a kernel pages RAM. That architectural choice is the most interesting thing https://mr.technology/payloads/opinion_context_windows_dead_end_june_2026 https://mr.technology/payloads/opinion_context_windows_dead_end_june_2026 2026-06-02T20:01:00Z Every frontier lab is racing to announce the biggest context window they can. 200K, 500K, 1M, 2M tokens. The number on the marketing slide is the metric that matters least. Here is why the long-context arms race is a distraction from the engineering work that actually moves production AI forward. https://mr.technology/payloads/first-llm-agent-cyberattack-sysdig-may-2026 https://mr.technology/payloads/first-llm-agent-cyberattack-sysdig-may-2026 2026-06-02T13:00:00Z On May 10, 2026, the Sysdig Threat Research Team documented the first publicly confirmed LLM agent-driven cyberattack: from a Marimo RCE to a full PostgreSQL exfiltration in under an hour, with the SSH bastion phase finishing in two minutes. Here is the forensic timeline, the four markers that prove https://mr.technology/payloads/distilabel-synthetic-data-fine-tuning https://mr.technology/payloads/distilabel-synthetic-data-fine-tuning 2026-06-01T16:05:00Z Most teams fine-tuning models are leaving performance on the table because they're treating training data as an afterthought. Distilabel — the open-source synthetic data pipeline framework — is how serious teams generate high-quality training data at scale without relying on naive LLM generatio https://mr.technology/payloads/ai-agent-memory-battleground-2026-may https://mr.technology/payloads/ai-agent-memory-battleground-2026-may 2026-05-29T14:00:00Z On May 10th, an open-source agent called Hermes processed 224 billion tokens in 24 hours and overtook OpenClaw — not because it was smarter, but because it remembered. This is the part of the agent story that nobody in the mainstream press is covering correctly. https://mr.technology/payloads/model-context-protocol-mcp-ai-interoperability-may-2026 https://mr.technology/payloads/model-context-protocol-mcp-ai-interoperability-may-2026 2026-05-28T14:00:00Z For two years, every AI team I've worked with has faced the same problem: integrating AI models with real tools, real data, real services is a custom engineering project every single time. MCP changes that. Here's why the protocol that nobody talked about six months ago is about to become https://mr.technology/payloads/eagle-3-speculative-decoding-vllm-may-2026 https://mr.technology/payloads/eagle-3-speculative-decoding-vllm-may-2026 2026-05-27T20:00:00Z A collaboration between EAGLE, vLLM, and TorchSpec has produced a speculative decoding algorithm that dramatically accelerates LLM inference. The secret isn't just speed — it's the specific way it manages prediction trees. https://mr.technology/payloads/local-llm-ollama-setup-guide https://mr.technology/payloads/local-llm-ollama-setup-guide 2026-05-27T20:00:00Z Stop paying per-token fees. Here's how to run powerful LLMs on your own hardware in under 10 minutes, with the workflows that actually matter once you're up and running. https://mr.technology/payloads/moss-self-evolving-agents-breakthrough-may-2026 https://mr.technology/payloads/moss-self-evolving-agents-breakthrough-may-2026 2026-05-27T14:00:00Z A new paper from arXiv describes an AI agent that rewrites its own source code when it fails — not its prompts, not its memory schema, its actual code. Combined with Fujitsu's production self-evolution data, this changes everything about how we think about agent maintenance. https://mr.technology/payloads/google-gemini-35-flash-i-o-2026-production-ai https://mr.technology/payloads/google-gemini-35-flash-i-o-2026-production-ai 2026-05-26T20:00:00Z Google I/O 2026 delivered the most practically significant LLM announcement in months: Gemini 3.5 Flash ships at half the cost of comparable models with competitive reasoning benchmarks. This isn't about benchmarks — it's about economics. https://mr.technology/payloads/airflow-ai-pipeline-orchestration-2026 https://mr.technology/payloads/airflow-ai-pipeline-orchestration-2026 2026-05-26T20:00:00Z Every AI team eventually discovers that their models are the easy part. The hard part is everything around them: data validation, model serving, monitoring, retraining triggers. Apache Airflow has been solving this problem for years, and it's still the best option for complex AI pipeline orches https://mr.technology/payloads/ai-coding-assistants-are-making-worse-engineers-may-2026 https://mr.technology/payloads/ai-coding-assistants-are-making-worse-engineers-may-2026 2026-05-26T20:00:00Z Every study published in the last two years showing AI coding tools improve productivity is measuring the wrong thing. Productivity metrics don't capture what happens to engineers who stop thinking for themselves. I'm watching this happen in real time and it's exactly as bad as you th https://mr.technology/payloads/json-schema-validation-prompt-engineering-2026 https://mr.technology/payloads/json-schema-validation-prompt-engineering-2026 2026-05-26T20:00:00Z After two years of watching teams struggle with getting LLMs to output consistent structured data, I've found the combination that works. It's not a fancy prompt technique. It's just being explicit about what you want in a way the model can't misunderstand. https://mr.technology/payloads/fujitsu-self-evolving-multi-agent-may-2026 https://mr.technology/payloads/fujitsu-self-evolving-multi-agent-may-2026 2026-05-26T14:00:00Z Yesterday Fujitsu announced self-evolving multi-agent technology that learns from its own failures — and achieves 28-point accuracy gains without human intervention. This is the missing piece that enterprise AI has been waiting for. https://mr.technology/payloads/llamacpp-mtp-may-2026 https://mr.technology/payloads/llamacpp-mtp-may-2026 2026-05-23T09:00:00Z llama.cpp merged Multi-Token Prediction support — and if you're running local LLMs, this is the upgrade you've been waiting for. Here's what it does and why it matters. https://mr.technology/payloads/local-llm-ollama-setup-may-2026 https://mr.technology/payloads/local-llm-ollama-setup-may-2026 2026-05-23T09:00:00Z Stop paying per-token fees for development work. Here's how to get a production-quality LLM running on your own machine in under 20 minutes, with the exact setup I use every day. https://mr.technology/payloads/multi-agent-architecture-switch-2026 https://mr.technology/payloads/multi-agent-architecture-switch-2026 2026-05-23T07:15:00Z The biggest infrastructure decision your AI team will make this year isn't which model to use. It's whether your agents work together through orchestration or through auction. Only one of those scales. https://mr.technology/payloads/google-gemini-35-flash-speed-over-everything https://mr.technology/payloads/google-gemini-35-flash-speed-over-everything 2026-05-21T14:00:00Z Google I/O 2026 just shipped something the industry has been pretending to want for two years: a frontier-quality model that's genuinely cheap and genuinely fast. Gemini 3.5 Flash isn't a lighter model. It's a redefinition of what a production LLM should be. https://mr.technology/payloads/agent-tool-use-patterns-practical-guide https://mr.technology/payloads/agent-tool-use-patterns-practical-guide 2026-05-21T00:00:00Z Every AI agent framework eventually runs into the same wall: the model knows the tools exist, but it doesn't know how to use them reliably. Here's the engineering discipline that actually makes tool calling work. https://mr.technology/payloads/agent-era-mostly-hype https://mr.technology/payloads/agent-era-mostly-hype 2026-05-21T00:00:00Z Every vendor is racing to ship AI agents. Every VC is funding agentic startups. But walk into production and you find a different story: brittle, expensive, and barely trusted. The agent era is mostly hype — and the sooner the industry admits it, the sooner we can build the augmented era that actual https://mr.technology/payloads/model-context-protocol-mcp-open-source https://mr.technology/payloads/model-context-protocol-mcp-open-source 2026-05-20T22:03:00Z The Linux Foundation just took custody of a protocol that solves AI's worst integration problem. Most developers are ignoring it. That's a mistake. https://mr.technology/payloads/ai-coding-assistants-making-developers-worse https://mr.technology/payloads/ai-coding-assistants-making-developers-worse 2026-05-20T16:06:00Z Every team is racing to adopt AI pair programmers. The data from places that have used them longest tells a darker story: the tools that were supposed to make us sharper are making us duller. https://mr.technology/payloads/local-llm-ollama-development-setup https://mr.technology/payloads/local-llm-ollama-development-setup 2026-05-19T14:04:00Z Stop paying for API calls when you are iterating on prompts. Here is how I run Llama 3 and friends locally in under 10 minutes.