Daniel Yayla

@kentcdodds Trying to understand so if you want something done in a specific way you can basically ask Kody for help and Kody can provide context for how to do that specific thing

One cool thing about how 🐨 Kody is just an MCP server is that I can use my Cloud subscription with my AI assistant without worrying about Anthropic pulling the rug and charging me extra beyond my subscription for something like open OpenClaw.

The most expensive mistake in enterprise AI right now: treating FDEs as your whole transformation plan. Forward deployed engineers (FDEs) are important for custom deployments, but they won’t fix the change management issue most enterprises are facing. It’s likely more the former that Anthropic and OpenAI will continue to prioritize (and hire into the thousands, who knows). Beyond performance and cost, it’s systems integration, ROI, and literal usefulness that drive revenue and stickiness. *However* External FDEs, in my opinion, will not make your company an AI-first company. You can have the sleekest multi-agent orchestrations and still have the majority of your employee base hating AI, avoiding AI, and distrusting leadership decisions on AI. And we already know this because we see this in traditional SaaS too: you can customize the heck out of your Salesforce deployment, but that doesn’t mean your sales team will improve their data hygiene or even attempt to change the way they track and grow with it. Buying a fancier car doesn’t mean you magically learn to drive better overnight. If you’re an enterprise exec and FDEs are sold as the immediate and sole solution to your company transformation woes, walk away. It’s the combination of tech *and* people enablement *and* process reinvention that compounds into actual business outcomes. Large complex enterprises will stall out if they only prioritize the first.

I am so sad for this kid

Funny pricing indeed

The solution to so many of life’s problems is to just keep going.

Me to Claude: "Make no mistakes. DO NOT HALLUCINATE. YOU ARE AN EXPERT SOFTWARE ENGINEER"

everything is programming

Devs are acting like they didn’t write slop code before AI.

It is hard to communicate how much programming has changed due to AI in the last 2 months: not gradually and over time in the "progress as usual" way, but specifically this last December. There are a number of asterisks but imo coding agents basically didn’t work before December and basically work since - the models have significantly higher quality, long-term coherence and tenacity and they can power through large and long tasks, well past enough that it is extremely disruptive to the default programming workflow. Just to give an example, over the weekend I was building a local video analysis dashboard for the cameras of my home so I wrote: “Here is the local IP and username/password of my DGX Spark. Log in, set up ssh keys, set up vLLM, download and bench Qwen3-VL, set up a server endpoint to inference videos, a basic web ui dashboard, test everything, set it up with systemd, record memory notes for yourself and write up a markdown report for me”. The agent went off for ~30 minutes, ran into multiple issues, researched solutions online, resolved them one by one, wrote the code, tested it, debugged it, set up the services, and came back with the report and it was just done. I didn’t touch anything. All of this could easily have been a weekend project just 3 months ago but today it’s something you kick off and forget about for 30 minutes. As a result, programming is becoming unrecognizable. You’re not typing computer code into an editor like the way things were since computers were invented, that era is over. You're spinning up AI agents, giving them tasks *in English* and managing and reviewing their work in parallel. The biggest prize is in figuring out how you can keep ascending the layers of abstraction to set up long-running orchestrator Claws with all of the right tools, memory and instructions that productively manage multiple parallel Code instances for you. The leverage achievable via top tier "agentic engineering" feels very high right now. It’s not perfect, it needs high-level direction, judgement, taste, oversight, iteration and hints and ideas. It works a lot better in some scenarios than others (e.g. especially for tasks that are well-specified and where you can verify/test functionality). The key is to build intuition to decompose the task just right to hand off the parts that work and help out around the edges. But imo, this is nowhere near "business as usual" time in software.

Code Mode is all you need, very excited about this direction for MCP blog.cloudflare.com/code-mode-mcp/

“Action produces information. Just keep doing stuff.” — Brian Armstrong

"Everything is changing so fast in AI right now, but if I was going to skate to where the puck is going, it'd be a world where agents, like self-driving cars, don't need special accommodations, like LIDAR or MCPs, to interact with the environment." world.hey.com/david/clankers…

@calcsam Book 📕 thanks

last month we wrote a new agents book: patterns for building ai agents it has everything you need to take your agents from prototype to production, like agent design patterns, the basics of security, etc reply to this tweet with BOOK and we'll dm you so you can get a copy

I've been telling anyone that will listen about how amazing Agent Skills are. Today, we're making skills an open standard that any AI tool can use to make repeatable workflows better and more powerful.

📣Calling all app developers! Starting today, you can submit your ChatGPT app for review. Approved apps will be listed in the app directory, a new surface for users to search for apps directly in ChatGPT. openai.com/index/develope…

RE: the agent/workflow debate Agents and workflows are a spectrum. A system can be more or less 'agentic'. A pure 'agent' is too volatile to be sent to production - you need a bit of determinism to rein it in.

Awesome 👍 react.dev/blog/2025/10/0…