Carlos Sanchez

Carlos Sanchez

@csanchez.org

Author of Jenkins Kubernetes plugin. Open Source, Kubernetes, DevOps, Progressive Delivery, and automating all the things @adobe

437 followers133 following258 posts

Docker Maven images are now ready for 3.10 on Eclipse Temurin, for Alpine and Ubuntu Resolute. Resolute is also available for all Temurin variants. Example: maven:3.10.0-eclipse-temurin-27-resolute

🤔 "Harness choice has little effect on task success rate, but can significantly affect the cost" "A simple harness can be competitive" "Models may perform better with other harnesses than with their own. So it turns out that your Claude models may not need Claude Code…" harnesstax.github.io

harnesstax.github.ioHarnessTax: How Much Does the Harness Matter for Coding Agents?What does a coding-agent harness actually add, and at what cost? It turns out your Claude models may not need Claude Code… We evaluate 21 model–harness pairs spanning seven models and three harnesses—...

Lots of interesting takes here. One thing I miss: the perf factory should also address business outcomes (we are doing that with usage data analysis)

Gergely Orosz@gergely.pragmaticengineer.com

Here's what OpenAI's agentic software factory looks like, today. It's surely not token efficient, but eg agents "babysitting" releases to prod is something new, and an interesting approach. Details: newsletter.pragmaticengineer.com/p/openai-sof...

> Death of the IDE & pull requests. PRs and code reviews are being rethought > Agents handhold both the code changes and the changes behind feature flags. Builds its own (feature flags) monitoring dashboard to use

> We are building an agent that “handholds” a change all the way to production Low-risk changes follow an easier path; areas of the codebase can opt in to an agent that will auto-approve low risk PRs, removing human acceptance as a bottleneck and improving velocity.

Tested Jev to see what the buzz is all about and this is what I found for my generative websites case 🧵 TL;DR: it's not a chatbot. It's a "choice machine." And for the right job, it's stupidly fast, cheap, and accurate No free text generation, ever.

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My generative websites demo bsky.app/profile/csan...

Carlos Sanchez@csanchez.org

My talk "Agentic Sites: Building Hyper Personalized Websites" from AI Engineer SF is now up I show a demo of site content being autogenerated live in under ~1.5 seconds, opening the door to a extremely personalized web experience, while keeping the content on brand www.youtube.com/watch?v=jebp...

Tested Jev to see what the buzz is all about and this is what I found for my generative websites case 🧵 TL;DR: it's not a chatbot. It's a "choice machine." And for the right job, it's stupidly fast, cheap, and accurate No free text generation, ever.

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Regular LLMs are like asking someone to write an essay. Jev is handing them a multiple-choice bubble sheet. If your task IS actually a bounded decision (classify, rank, select, score) you don't need an essay. You need a bubble sheet.

Tested Jev to see what the buzz is all about and this is what I found for my generative websites case 🧵 TL;DR: it's not a chatbot. It's a "choice machine." And for the right job, it's stupidly fast, cheap, and accurate No free text generation, ever.

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Intent classification: also 15/15 (100%) tweaking the process. Instead of generating the response text make Jev answer if product X was mentioned (yes/no) The one real limit I hit: fully open-ended extraction (arbitrary "use cases"/"features" with no fixed list). Jev genuinely can't do that

💰 Cost check: ran it against ~28 other providers (Bedrock Claude/Nova/Llama, Cloudflare Workers AI, self-hosted models). Jev landed in the CHEAPEST tier on par with micro-models, while being the fastest 100% on block selection. ~80-400x cheaper than Claude Sonnet/Opus for equivalent accuracy.

Tested Jev to see what the buzz is all about and this is what I found for my generative websites case 🧵 TL;DR: it's not a chatbot. It's a "choice machine." And for the right job, it's stupidly fast, cheap, and accurate No free text generation, ever.

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My site has a generative pipeline with 2 stages: 1️⃣ Classify user intent + extract entities 2️⃣ Pick which UI blocks to render (hero, comparison table, testimonials, etc.) Both are "decision" tasks, not "writing" tasks. Perfect test case for Jev

Block-selection results: 15/15 (100%) ✅ I turned "which blocks should render?" into 21 parallel yes/no questions (one per block type), answered in a SINGLE API call, then combined with plain code logic. Matched Claude Sonnet 4's accuracy at ~4.4x the speed.

Tested Jev to see what the buzz is all about and this is what I found for my generative websites case 🧵 TL;DR: it's not a chatbot. It's a "choice machine." And for the right job, it's stupidly fast, cheap, and accurate No free text generation, ever.

My talk "Agentic Sites: Building Hyper Personalized Websites" from AI Engineer SF is now up I show a demo of site content being autogenerated live in under ~1.5 seconds, opening the door to a extremely personalized web experience, while keeping the content on brand www.youtube.com/watch?v=jebp...

youtube.comAgentic Sites: Building Hyper Personalized Websites — Carlos Sanchez, AdobeCarlos Sanchez types a request for a coffee machine he can use while camping, and the page assembles itself in under two seconds. Not a search result. A page, with camping appropriate machines,…

I also show what a experience could be with the integration of multi modality: talking to your voice home assistant, getting results on your Google TV. No more science fiction. This was built on Adobe AEM, Cerebras fast inference and Google Gemma 4 model

Thanks for the feedback too! ありがとうございます #kubecon

Carlos Sanchez@csanchez.org

Packed room for our #KubeCon Japan. #ArgoRollouts with AI Agent orchestration to autofix production issues while safely doing canaries with @kevindubois.com ありがとうございます kubecon-cloudnativecon-japan-2026.sessionize.com/session/1145...

Back from speaking at @aidotengineer.bsky.social in SF last week and #googleioconnect Berlin just before. Lots of energy and cool (AI) stuff * The self-improving codebase is real * The agentic org chart * Agentic web standards * Agent sandboxing * Open models, training, fine-tuning #AIEngineer

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Models, Training and datacenters: plenty of companies selling inference, model routing, training, post-training, fine-tuning,... on open models

Back from speaking at @aidotengineer.bsky.social in SF last week and #googleioconnect Berlin just before. Lots of energy and cool (AI) stuff * The self-improving codebase is real * The agentic org chart * Agentic web standards * Agent sandboxing * Open models, training, fine-tuning #AIEngineer

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The agentic web is getting standardized. WebMCP (Chrome): sites expose in-browser tools directly to agents, no DOM scraping. MCP Apps: servers push interactive UI back into agent chats. ARD/ai-catalog.json: agents discover tools & agents at runtime. auth.md agents register users without signup forms

Agent sandboxing is the new infra fight: Gemini Enterprise Agent Sandbox, AWS Lambda Sandboxes, k8s agent-sandbox and substrate, Nvidia OpenShell, Modal, E2B,... Workload isolation + fast snapshot/restore

Back from speaking at @aidotengineer.bsky.social in SF last week and #googleioconnect Berlin just before. Lots of energy and cool (AI) stuff * The self-improving codebase is real * The agentic org chart * Agentic web standards * Agent sandboxing * Open models, training, fine-tuning #AIEngineer

The self-improving codebase, aka Dark Factory, is real, but old rules still apply. Good CI/CD, e2e tests & canaries directly speed up the agentic loop — skip them and humans stay the bottleneck. ie. Uber already write, review, test & merge PRs with barely any human touch

The agentic org chart. Forget managing multiple tabs — the new model is for one human to interact with one "AI manager" that manages multiple agents. Cloud dev environments let those sessions run nonstop at scale, no need to keep your laptop open.

At Google I/O in Berlin this week and AI Engineer World’s Fair in SF next week I will be presenting Adobe frontier work on using fast inference to individualize websites as you visit them - Audience of One of1.live #googleio #aiengineer

I've burnt 80% of my AI budget for the month in one day building a PoC with #kubernetes agent sandbox and agent substrate. Totally worth it, will post details. And I can always get more budget 😀

TIL I ate silk worms one month ago from some friendly Koreans that were sharing their food. I was lost in translation but now I ran the video through Antigravity to extract subtitles and surprise! they were actually tasty 😋 Beondegi 번데기 = silkworm pupae