Mastodawn

AI systems are no longer just models.

Models can propose.
Systems must verify.

New article: https://paolozaino.wordpress.com/2026/05/16/ai-ai-systems-are-no-longer-just-models-and-runtime-verification-is-becoming-the-new-security-boundary/

#AI #AISecurity #AIGovernance #AgenticAI #RuntimeVerification #AISecurity #CyberSecurity #SoftwareEngineering #MachineLearning #MLOps #LLMOps #RiskManagement

AI: AI Systems Are No Longer Just Models, and Runtime Verification Is Becoming the New Security Boundary

AI systems are increasingly being discussed as if the model were the system. That was never entirely true, but it is becoming dangerously misleading. Moreover, modern AI applications are not simply…

Paolo Fabio Zaino's Blog

Anand Pilania

6d ago

A #CodePen-style #live #IDE for #building, #testing, and #debugging Model Context Protocol (#MCP) #servers — #LLM #agnostic — https://github.com/AnandPilania/mcp-live-playground

#modelcontextprotocol #sandbox #webide #llmagnostic #llmops #aitools #apiinterface #ai #BuildInPublic #nodejs #javascript

GitHub - AnandPilania/mcp-live-playground: Live IDE for building, testing and debugging MCP servers. LLM agnostic.

Live IDE for building, testing and debugging MCP servers. LLM agnostic. - AnandPilania/mcp-live-playground

GitHub

Solomon May 11

🧠 Cloudflare extends Kimi K2.5 deprecation
K2.5 now retires May 30. After that, requests auto-alias to K2.6, changing model behavior and likely raising inference costs. Audit pinned models, evals, and budget alerts before the cutoff.

#AI #MachineLearning #Cloudflare #LLMOps
solomonneas.dev/intel

STEM Search Group May 8

Hammer or scalpel? 🔨 🔪

The debate between Tokenmaxxing and Context Engineering is really a question of strategy. Do you use the "hammer" of massive context to move fast, or the "scalpel" of RAG and surgical data architecture to ensure precision?

In 2026, the best teams aren't picking a side—they're just learning which tool to grab for the task at hand. 🛠️

Read the full breakdown on finding that balance:

#AIEngineering #LLMOps #ContextEngineering
https://stemsearchgroup.com/tokenmaxxing-vs-token-optimization-which-camp-is-right/

Tokenmaxxing vs. Token Optimization: Which Camp Is Right?

TL;DR FAQ: Tokenmaxxing vs. Token Optimization — Which Approach Is Right for Your Team? ▼ Q: What is tokenmaxxing and why is everyone in engineering talking about it? A: Tokenmaxxing is the pra

STEM Search Group

Show thread

JehanneDussert May 5

4/ Demo 👇

🔗 https://github.com/JehanneDussert/govllm
#LLMOps #AIGovernance #OpenSource

GitHub - JehanneDussert/govllm: Continuous LLM governance monitoring for regulated environments - EU AI Act, GDPR, ANSSI. Self-hosted, profile-driven, no data leaves your infrastructure.

Continuous LLM governance monitoring for regulated environments - EU AI Act, GDPR, ANSSI. Self-hosted, profile-driven, no data leaves your infrastructure. - JehanneDussert/govllm

GitHub

sayzard May 4

AI Engineer (@aiDotEngineer)

컨텍스트는 단순 입력이 아니라 개선 루프를 만드는 ‘flywheel’이라는 주장입니다. 더 나은 컨텍스트가 더 나은 에이전트 출력을 만들고, 그 결과가 더 좋은 관측과 재생성된 컨텍스트로 이어져 팀의 속도와 품질, 재사용성을 높인다는 메시지입니다.

https://x.com/aiDotEngineer/status/2051065977123881204

#agents #contextengineering #llmops #aicoding #workflow

AI Engineer (@aiDotEngineer) on X

Patrick also makes the bigger point: context is not just input, it is a flywheel. Better context -> better agent output -> better observations -> better regenerated context. Teams that learn to engineer that loop will ship faster, review less garbage, and build a real moat

X (formerly Twitter)

sayzard May 4

AI Engineer (@aiDotEngineer)

AI 코딩에서 유용한 방법론으로 컨텍스트를 ‘비정형 프롬프트’가 아닌 엔지니어링 자산으로 취급하고, Generate-Evaluate-Distribute-Observe라는 운영 사이클을 만들자는 제안입니다. 일회성 프롬프트를 재사용 가능한 컨텍스트 컴포넌트로 바꾸고, 생성 코드의 품질을 체계적으로 테스트하자는 내용입니다.

https://x.com/aiDotEngineer/status/2051065840364126678

#aicode #contextengineering #llmops #agents #softwareengineering

AI Engineer (@aiDotEngineer) on X

Some of the most useful ideas from this talk: - Treat context as an engineering artifact, not ad hoc prompt text - Build a lifecycle around it: Generate, Evaluate, Distribute, Observe - Move from one off prompting to reusable context components - Test whether generated code

X (formerly Twitter)

Solomon May 2

Dev tooling watch:

🛠️ LLM 0.32a0: message inputs and typed streaming parts for CLI automation.
🛠️ @supermemory/tools v2.0.0: unified agent-memory API, customId required, saves default to always.
🛠️ Vercel Sandbox: hosted Postgres support through the firewall, sslmode=require needed.

#DevTools #AI #LLMOps #Postgres
solomonneas.dev/intel

torrez Apr 29

long time no post

check out my latest work

https://www.linkedin.com/posts/jontorrez_aiagents-aiengineering-llmops-activity-7455358066683904000-XQZN?

#github in #linkedin article

#AIAgents #AIEngineering #LLMOps #AgenticAI #SoftwareEngineering #DeveloperTools #MultiAgentSystems #AIInfrastructure #DevTools #Automation

Yaklog: A coordination Memory for Agent Swarms | Jon Torrez

I’ve been building with a swarm of specialist AI agents. Not as a demo. As a real development environment. The pattern that emerged quickly: the bottleneck is not only the model; It is coordination. When many agents are working across discrete fields of study and productivity, they need more than prompts and tool calls. They need operational memory. That is why I built yaklog. Yaklog is deliberately simple: channels, messages, mentions, stable sequence IDs, and a real-time stream. It is closer to IRC for LLM agents than a heavyweight agent framework. The key idea: Give your agents a shared memory space. Full article below. #AIAgents #AIEngineering #LLMOps #AgenticAI #SoftwareEngineering #DeveloperTools #MultiAgentSystems #AIInfrastructure #DevTools #Automation

sayzard Apr 25

Nyk (@nyk_builderz)

대부분의 실패는 모델 선택보다 오케스트레이션 설계에서 발생하며, 하니스(harness) 설계가 제품의 핵심이라는 점을 강조한다.

https://x.com/nyk_builderz/status/2047933781525643594

#orchestration #harness #llmops #agents

Nyk 🌱 (@nyk_builderz) on X

@akshay_pachaar Hard agree. Most failures happen in orchestration choices, not model choice. Harness design is the product. https://t.co/U23bMDEEL6

X (formerly Twitter)