vlad

AI agents are already buying online. How to build a business they can buy from: 1/ Pick a task an agent needs to outsource: generate product images, retrieve company data, deploy an app. 2/ Define the offer: required inputs, exact output, price and delivery time. 3/ Expose the purchase and delivery flow through an API or MCP tools: get a quote, order, check progress, retrieve the result. 4/ Accept payments through a card checkout or MPP for paid API calls. docs.stripe.com/payments/mac… 5/ Make the business discoverable: publish pricing, output examples and integration docs. List it in relevant agent directories. 6/ Test the entire journey: give an agent a task and a budget, then check whether it can find your service, buy it and use the result. Track completed, paid jobs.

How to build a self-driving Fortune 500 company: 1/ Map the business as an information flow → A customer has a problem. They give you information. You do the work, deliver a solution and find out whether it helped. Map what each step needs and produces. 2/ Make an AI agent the app customers use → Text + voice in, generative UI out. Customers describe what they need; the agent does the work and generates the interface to deliver the result. 3/ Give that agent the full customer context → Keep track of the customers problem, constraints, previous interactions, what was delivered and whether they were satisfied. Each interaction should add to that understanding. The agent will have embedded CRM 4/ Connect it to agents doing longer work in the background → Use Replit, ChatGPT or Claude to build and run the backend workflows: research, calculations, content production, monitoring. The customer-facing agent passes along the task and context, then brings the result back to the customer. 5/ Give the system a business goal and a precise measure of success → Define what a successful customer outcome looks like and how it contributes to the business. Measure completed jobs, repeat purchases and profit. For qualitative work, use AI judges with clear criteria and examples of good and bad results. 6/ Choose signals you can measure frequently → Annual revenue is too slow to guide daily changes. Track whether customers finish the task, accept the result, request revisions or come back. Check that improvements in these signals also improve the main business metric. 7/ Make adaptation part of the system → Customers will change what they want. The agent sees their new questions, objections and feedback directly. Use that evidence to update the service, test the changes and measure whether the next customers get better results.

Link for AI agent for 3D part design: agentplace.io/admin/dashboar….

Free Template Alert 🚨 AI agent that helps people design 3D parts through conversation. It understands the request, builds a visual response, remembers changes, and can take action through connected tools. Here’s what you get: 1/ An agent you can explain the job to → “I need an L-bracket for an 18 mm shelf with two M4 screws.” The agent uses those requirements to create the model. 2/ Voice and text in the same conversation → Say “make it 6 mm thick and add a rib.” The agent applies the changes to the part you’re working on. 3/ An agent with its own interactive interface → The response includes a 3D model, dimensions, and a section view. You can see what the agent is working on as the design changes. 4/ Context across iterations → The agent builds on previous work. Compare the updated part with the earlier version without explaining the project again. 5/ Actions through connected tools → With a printer integration configured, ask the agent to send the selected version to print. 6/ Progress inside the same experience → The printing workflow can bring status, progress, and remaining time back into the agent’s interface. 7/ Your own agent, available by link → Give customers a place to describe what they need and work with the agent directly in their browser. 8/ A template you can adapt → Add your instructions, business knowledge, and connected tools to shape how the agent serves your customers. I’ll share the agent link in the next post.

Mark Zuckerberg said -- You are NOT going to know that you are writing code. here’s Astra generating UI in real time: UI on the left and code being written live on the right. You need an interface, the agent builds it, you use it and move on. But this isn’t limited to interfaces. Codex creates tons of supporting code for debugging, testing or even creating a video. Mine recently created an entire app to find a few pixels that were flickering in our UI. software is becoming fully disposable, and software is really for computers. We will speak with machines through AI wherever we are: on a Mac, on the web, at home or wearing glasses. AI models will interpret our intent and run Python, JS, Rust or Java on VMs without us worrying about it.

A stunning, fully personalized customer experience with intelligent UI

These agents keep blowing my mind..

This chat has an answer to why almost all frontier models average around 100 tokens/s.

you can build it on Agentplace.io

one of those days