Summarizer

IMHO no one is really pioneering. A lot more is possible than what is being done. I wrote a blog post about useful agents in a business setting ( https://www.generativestorytelling.ai/blog/posts/useful-corp... ) that highlights AI being proactive. I mean table stakes stuff, why isn't an agent going through all my slack channels and giving me a morning summary of what I should be paying attention to? Why aren't all those meeting transcriptions being joined together into something actually useful? I should be given pre-meeting prep notes about what was discussed last time and who had what to do items assigned. Basic stuff that is already possible but that no one is doing. I swear none of the AI companies have any sense of human centric design. > pull relevant context from Slack, Notion, and your codebase, then provide you with a prioritized list of actions. This is an improvement, but it isn't the central focus. It should be more than just on a single work item basis, more than on just code. If we are going to be managing swarms of AI agents going forward, attention becomes our most valuable resource. AI should be laser focused on helping us decide where to be focused.

My current expectation is that the Cowork/Codex set of "professional agents" for non-technical users will be one of the most important and fastest growing product categories of all time, so far. i.e. agents for knowledge workers who are not software engineers A few thoughts and questions: 1. I expect that this set of products will be extremely disruptive to many software businesses. It's like when a new VP joins a company, they often rip and replace some of the software vendors with their personal favorites. Well, most software was designed for human users. Now, peoples' agents will use software for them. Agents have different needs for software than humans do. Some they'll need more of, much they'll no longer need at all. What will this result in? It feels like a much swifter and more significant version of Google taking excerpts/summaries from webpages and putting it at the top of search results and taking away visits and ad revenue from sites. 2. I've tried dozens of products in this space. For most, onboarding is confusing, then the user gets dropped into a blank space, usage limits are uncompetitive compared to the subsidized tokens offered by OpenAI/Anthropic, etc. It's a tough space to compete in, but also clearly going to be a massive market. I'm expecting big investment from Microsoft, Google etc in this segment. 3. How will startups in this space compete against labs who can train models to fit their products? 4. Eventually will the UI/interface be generated/personalized for the user, by the model? Presumably. Harnesses get eaten by model-generated harnesses? A few more thoughts collected here: https://chrisbarber.co/professional-agents/ Products I've tried: ai browsers like dia, comet, claude for chrome, atlas, and dex; claw products like openclaw, kimi claw, klaus, viktor, duet, atris; automation things like tasklet and lindy; code agents like devin, claude code, cursor, codex; desktop automation tools like vercept, nox, liminary, logical, and raycast; and email products like shortwave, cora and jace. And of course, Claude Cowork, Codex cli and app, and Claude Code cli and app. Edit: Notes on trying the new Codex update 1. The permissions workflow is very slick 2. Background browser testing is nice and the shadow cursor is an interesting UI element. It did do some things in the foreground for me / take control of focus, a few times, though. 3. It would be nice if the apps had quick ways to demo their new features. My workflow was to ask an LLM to read the update page and ask it what new things I could test, and then to take those things and ask Codex to demo them to me, but it doesn't quite understand it's own new features well enough to invoke them (without quite a bit of steering) 4. I cannot get it to show me the in app browser 5. Generating image mockups of websites and then building them is nice

I agree, in general we are going to find that ultimately most employee end users don't want it. Assuming it actually makes you more productive. I mean, who the hell wants to be 10X more productive without a commensurate 10X compensation increase? You're just giving away that value to your employer. On the other hand, entrepreneurs and managers are going to want it for their employees (and force it on them) for the above reason.

I dont see companies doing that. it can be business ending. only AI bros buying mac mini in 2026 to setup slop generated Claws would do that but a company doing that will for sure expose customer data.

> My current expectation is that the Cowork/Codex set of "professional agents" for non-technical users will be one of the most important and fastest growing product categories of all time, so far. I agree this is going to be big. I threw a prototype of a domain-specific agent into the proverbial hornets' nest recently and it has altered the narrative about what might be possible. The part that makes this powerful is that the LLM is the ultimate UI/UX. You don't need to spend much time developing user interfaces and testing them against customers. Everyone understands the affordances around something that looks like iMessage or WhatsApp. UI/UX development is often the most expensive part of software engineering. Figuring out how to intercept, normalize and expose the domain data is where all of the magic happens. This part is usually trivial by comparison. If most of the business lives in SQL databases, your job is basically done for you. A tool to list the databases and another tool to execute queries against them. That's basically it. I think there is an emerging B2B/SaaS market here. There are businesses that want bespoke AI tools and don't have the discipline to deploy them in-house. I don't know if it is ever possible for OAI & friends to develop a "hyper" agent that can produce good outcomes here automatically. There are often people problems that make connecting the data sources tricky. Having a human consultant come in and make a case for why they need access to everything is probably more persuasive and likely to succeed.

> There are businesses that want bespoke AI tools and don't have the discipline to deploy them in-house. I don't know if it is ever possible for OAI & friends to develop a "hyper" agent that can produce good outcomes here automatically. There are often people problems that make connecting the data sources tricky. Having a human consultant come in and make a case for why they need access to everything is probably more persuasive and likely to succeed. Sort of agreed, though I wonder if ai-deployed software eats most use cases, and human consultants for integration/deployment are more for the more niche or hard to reach ones.

Maybe but the product category is not necessarily a monolith in the same way that Claude Code is. These general purpose tools will have to action across a heterogeneous set of enterprise systems/tools. A runtime environment must be developed to do that but where that of the agent ends and that of the enterprise systems begins is a totally open question.

> Maybe but the product category is not necessarily a monolith in the same way that Claude Code is. These general purpose tools will have to action across a heterogeneous set of enterprise systems/tools. What would make it not be a monolith? To me it seems like there'll be a big advantage (e.g. in distribution, user understanding) for most people to be using the same product / similar interface. And then the agent and the developer of that interface figure out all the integrations under that, invisible to the user.

I mean there is a runtime layer that needs to be developed, and some of it may live in CC/Codex and some might live in the various enterprise systems. Someworkflow automations and some amount of the semantic layer may for instance exist in your CRM/ERP/data platform. Yes the front-end would be owned by the chat interface, but part of the solution may exist in the various enterprise systems. This would be closer to a distributed system than a monolith. The demos and marketing language point to this as the direction of travel (i.e. the reference to Atlassian Rovo, etc.).

I think the coding market will be much larger. Knowledge work is kind of like the leaf nodes of the economy where software is the branches. That's to say, making software easier and cheaper to write will cause more and more complexity and work to move into the Software domain from the "real world" which is much messier and complicated.

> market uptake. I think the market uptake of Claude Cowork is already massive.

You know what happens to a predator who makes its prey go extinct? AI is doing the same

really struggling to understand where this is coming from, agents haven't really improved much over using the existing models. anything an agent can do, is mostly the model itself. maybe the technology itself isn't mature yet.

My view is different. Agent products have access to tools and to write and run code. This makes them much more useful than raw models.

Yes, I think they unlock a whole new level of capability when they have a r/w file system (memory), code execution and the web.

Just yesterday my non-technical spouse had to solve a moderately complex scheduling problem at work. She gave the various criteria and constraints to Claude and had a full solution within a few minutes, saving hours of work. It ended up requiring a few hundred lines of Python to implement a scheduling optimization algorithm. She only vaguely knows what Python is, but that didn't matter. She got what she needed. For now she was only able to do that because I set up a modified version of my agentic coding setup on her computer and told her to give it a shot for more complex tasks. It won't be trivial, but I do think there's a big opportunity for whoever can translate the experience we're having with agentic coding to a non-technical audience.

Couple of people in my company have vibe coded some chat interface and they’re passing skills and MCPs that give the model access to all our internal data (multiple databases) and tools (Jira, Confluence etc). I wonder if there’s something off the shelf that does this?

Sherlocking ramps up into IPO Bunch of startups need to pivot today after this announcement including mine