Vikram K.

As COO at www.jaiinfoway.com this is an important signal for where agentic AI is heading. Non technical implementations are catching up fast but the real story is iteration speed and learning loops. Building Cowork entirely with Claude Code shows how agents are becoming first class workers not just assistants. At www.jaiinfoway.com we see this shift clearly as enterprises move from copilots to autonomous task execution with guardrails. UX will evolve tooling will mature but the direction is set. Curious how others here see non technical users adopting agent driven workflows this year. Are we ready for agents as coworkers. #Jaiinfoway #AgenticAI #Claude #AIAgents #EnterpriseAI #FutureOfWork #AIProductivity #AITransformation #AILeadership

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"I have only made this letter longer because I have not had the time to make it shorter." - Blaise Pascal'' This also applies to software demos. We've tightened the onboarding workflow and now have a 60 second demo of the journey from a blank slate in Claude Code to a deployed preview application on VeilStream.

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This is a really interesting article about writing agents with the Claude Agent SDK. It gets into design advice that you should consider when writing an agent with Claude. It chimes with what I’ve read about the development of Claude Code (write as little business logic as possible and concentrate on getting out of the way of the model). The general takeaway for me is from the three-block flow chart in the middle: Give the agent good tools/affordances in three categories: Gather Context, Take Action, Verify work. Do that at the right granularity, with good feedback, and then let the model do the driving. It’s deceptively simple, but it has a goldilocks quality to it. Trying to make a more complex flow chart with many more boxes and lines constrains the AI to just the things you could think of in advance and makes it overfit to what you know today. Trying to make it simpler by, for example, giving the agent a whole existing API as a single tool can overwhelm it with too much choice and then too much context in the responses. It’s definitely worth reading if you're interested in building or using agents, irrespective of AI vendor. https://lnkd.in/eKF2rXWb

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I've authored a blog for developers who are new to vector embeddings and semantic search - if that's you, hopefully you'll find it helpful! #semanticsearch #vectorsearch #vectordatabase #vectorembeddings #densevectors #sparsevectors #elasticsearch https://lnkd.in/eAU8uACZ

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Claude Cowork applies the same agentic architecture that powers Claude Code, but inside Claude Desktop, so you can delegate multi-step knowledge work without living in the terminal. This article explores what Cowork is, how it differs from chat and Claude Code, and how to extend and use it responsibly. The full article is in the first comment below.

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love the analogy that my cohost Iury gave - think of your AGENTS[.]md like the constitution of your codebase! we also go into an important paper that tries to answer the question that we've all had at some point - are these AGENTS files we're all meticulously creating, even worth it?

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I’ve just published the next installment in my "Theory of Durable Execution" series. Across frameworks we hear terms like workflows, activities, virtual objects, handlers, and functions. Underneath the terminology, they’re all describing a small number of execution patterns. In this new post, I break durable functions down into three forms: 🔹 Stateless functions for one-shot deterministic logic 🔹 Sessions for long-running, interactive orchestration 🔹 Actors for persistent, message-driven state To get there, I walk through: 🔹 The behavior–state continuum 🔹 How identity, lifetime, communication, and concurrency shape execution semantics 🔹 How frameworks like Temporal, Restate, DBOS, and Resonate map onto these forms This builds on the previous two posts in the series: 🔹 Demystifying Determinism in Durable Execution 🔹 The Durable Function Tree (part 1 and 2) This was the last post in this series, distilling the various frameworks down to a simpler logical model. Full post: The Three Durable Function Forms https://lnkd.in/eJHpY9qC

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From Claude Code for developers to Claude Cowork for everyone else—this is a real shift. Stop controlling prompts and start controlling outcomes. Instead of just chatting, you give Claude access to a local folder so it can read, edit, and create files to tackle multi-step tasks like organizing docs, building spreadsheets, or drafting reports. It’s the move from “assistant” to true AI agents at work. Sure, it has bugs—but directionally, it’s very promising. #AI #Claude #vibecoding https://lnkd.in/ghmFtTFp

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Some thoughts about RSS and how social services like Mastodon, Bluesky, or even LinkedIn could make use of it to populate posts on their service. Dave Winer dubbed it inbound RSS. https://lnkd.in/eJfPvXaU

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Open Responses is an open-source spec based off OpenAI's Responses API, with backing so far from OpenRouter, Vercel, HuggingFace, LM Studio, Ollama, and vLLM. https://openresponses.org Will more providers get on board? It'd be so nice to have a true standard for LLM APIs.

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A great post on how AI can change workflows for the better and reduce costs significantly (by Lee Robinson) Cursor website makeover: https://leerob.com/agents - reducing page complexity by removing an entire CMS and a bunch of redundant dependencies - huge savings in CDN costs - easy updates with agents - great use of the new Cursor browser window Seems like that with AI and coding agents, the cost of an abstraction has never been higher. Curious -> what gains were you able to get recently by rethinking workflows that predate AI?

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Many folks underestimate the long-tail effects which good blog posts can have. It's easy to be discouraged when writing something, and then there are no reactions to it at all. Yet, in some cases, I've received comments and feedback for posts months after publishing them. Some of them keep being shared years later. So focus on writing high value pieces and have some patience, they'll find their readership eventually. Blogging is a long game.

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Most teams still ship software through a loop of vague docs, interpretation, rework, and drift. We’ve accepted it as normal, even when half our defects come from unclear requirements—not the code itself. This year I shifted to a different workflow: Plan with AI → review the plan like a PR → iterate → let the model implement → polish → ship. It feels less like “AI coding” and more like removing sand from the gears. I wrote about why this change works, and why planning-as-code might be the next quiet upgrade for engineering teams: 👉 When Planning Becomes Code https://lnkd.in/eCh8mdwF

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To date, writing extensions for Envoy has been a laborious process that involves writing C++ and compiling a fully custom build of the entire proxy.  Can we make that easy and make Envoy more approachable by developers?. Can we create an ecosystem of reusable extensions around it - akin to how npm ecosystem fundamentally altered Node.js's trajectory. With that vision, we at Tetrate have been working with Envoy community to first make Envoy easy to extend by any developer. We added dynamic modules a year ago and then added a proper Go and Rust SDK around it. Today, we are making the developer experience much easier and announcing a home for Envoy extensions with an open source extension marketplace around it. Thanks Matt Klein Anna Berenberg for your support and thanks Rohit Agrawal Ben Plotnick Anubhav Aeron for early feedback and trials. You can read more about Built on Envoy here: https://lnkd.in/gbNz9-3v and see a cool demo video from our engineering lead Ignasi Barrera on how to write a simple Go extension and test it locally for Envoy to not allow AI calls to specific models. https://lnkd.in/gcpYJyjD

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Venting a little frustration here while developing a new mapping feature in RidgeText. Gemini is much lazier than Claude. It actively finds ways to avoid doing work, like saying "but the direct REST API is preferred for our current architecture" instead of determining why it's preferred when our structure doesn't matter. We're an LLM tool using Vertex functions. Whether those functions are REST, server-side scripts, MCP calls, or anything else doesn't matter. I hate that I have to tell Gemini to do better when Claude consistently lays out proper research plans. https://ridgetext.com

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