Solid

Solid gives AI agents their own computers, accounts, and budgets, then lets them take on a job from start to finish. You describe what you need in plain language, and the agents work out the steps, connect to the tools the job requires, build anything that is missing, and check the result before reporting back. The product is positioned for complex, long-running work that a person or a team hands over rather than supervises click by click. Instead of a personal assistant that lives inside a chat window, Solid is described as a system for work that continues after you close your laptop: the agents keep going and ping you when it is done. The site lists builders and operators at companies including Revolut, ElevenLabs, EY, British Airways, NVIDIA, Stanford, Berkeley, MIT, NYU, Swiggy, and the Government Digital Service among its users. The problem Solid targets is the distance between asking for something and actually having it done. A request in a chat tool typically ends with a suggestion, a draft, or a set of instructions that a person still has to carry out across several apps. Real jobs, however, involve signing up for services, connecting accounts, writing code, deploying it, testing it, and following up — often over hours or days. Solid's answer is to give the agents their own machines, their own accounts, and a budget, so they can perform those steps themselves. The website stresses that no prebuilt connector is required: agents can connect through an API, build a missing integration, or operate a website, desktop application, or phone app directly. That matters because the tools needed for a job are frequently ones that have never been added to an integration directory, and because the person delegating the work may not know how to use them either. Self-sufficiency is the first capability Solid highlights. The agents choose the tools they need and handle the setup themselves, even for software you have never used; the site's framing is that if a person can use it, they can too. They work from their own devices — Windows and macOS computers, Linux servers, iPhones, and Android phones — and their own Google and Apple accounts. Beyond devices and accounts, they can sign up for services and pay for them within the budget and approval rules you set. The illustration the site uses shows an agent controlling its computers and phones alongside account badges, a budget gauge, and a checked payment receipt. The practical effect is that you are not asked to prepare an environment, purchase the tooling, or configure integrations before work can begin; you provide the access that is required, choose the approval rules, and let the agent work out the rest. Solid describes its agents as self-healing. If a tool fails or their setup breaks, they can investigate the failure, make a repair, and check that the job runs again; when they genuinely need help, they explain what is blocking progress rather than stalling silently. This is paired with self-improvement: the next job starts with what they learned. The agents keep the fixes that worked and learn from your team's corrections, and those lessons change how they use tools and approach future jobs. The site illustrates this with an agent reusing a corrected pattern from a previous job as a drawing guide for the next one. In practice, this means corrections are not one-off patches that have to be repeated — feedback about how something should be done becomes part of how the agent operates on later, similar work. Self-scaling covers how Solid handles work that outgrows a single agent. The agents can create more Solid agents or bring in outside agents such as Codex and Claude Code, divide the work across whatever tools the job needs, coordinate the team, and return a single checked result. The site's illustration shows a Solid agent gathering results from other agents working across business tools and handing one verified outcome to a person. This matters for jobs that are too broad or too long for one worker: rather than a single agent attempting everything sequentially, the work can be split across agents and then reassembled into one deliverable. The example workflows Solid publishes follow the same pattern — a defined job with a numbered sequence of steps, ending in a result a person can review, approve, or share. Overall, Solid works as an always-on system rather than an interactive session. You bring the goal and the ground rules; the agents work out the steps, check the result, and report back. While a job runs, you can watch progress — the site's example shows an agent that has connected Gmail and HubSpot, researched on LinkedIn, built a dashboard, deployed it, and is verifying the data — but you do not have to be present. You close your laptop, and the agents keep working, messaging you when the result is ready or asking when they need a decision. You choose what the agents can access and which actions require approval; for example, they can research and draft freely while approval is required before sending a message, buying a service, or deploying a change. The agent is described as a meta-agent that can see and manage its own workspace within the access you give it, so you can ask what is running, why it is needed, or how much a job cost, including a breakdown of the AI usage, machines, and purchases used for the job. The stated benefits follow from that design. You are not managing every step of setup and troubleshooting, because the agents handle configuration, connections, and code on their own. You do not need to stay online or babysit a process, because the job continues without you and returns a finished result rather than an open question. Costs are visible and bounded: budgets and approval rules limit what agents can spend, and each job's consumption of AI, machines, and purchases can be broken down on request. Corrections persist across jobs, so instructions do not have to be repeated. When an agent remains blocked, it explains what needs your help, and the site notes you can also talk to a real person on the Solid team. For teams, the outcome is the ability to delegate more work without giving up control. Solid publishes example workflows that show what a finished job looks like, each starting from a first request and ending with a result you can review. In a sales demo workflow, an agent reads customer meeting notes, maps the buyer's workflow, builds the demo with sample data, hosts and tests the app, and returns the hosted link along with test results. In lead generation, an agent applies your targeting criteria, researches buying signals on LinkedIn, qualifies accounts and contacts, drafts outreach and waits for approval, then follows up, books qualified meetings, and updates the CRM. For AI product evaluation, an agent builds user scenarios and success criteria, runs after each release or change, simulates users completing key tasks, judges outcomes against expected behavior, and reports what passed, what failed, and why. A bug resolution agent investigates a production alert, reproduces the issue and assesses its impact, writes and tests a fix, opens a pull request for engineer approval, and verifies recovery after deployment. A support agent reads a stalled ticket, gathers the full customer history, finds the cause across systems, applies the fix within your policies, and confirms and records the resolution. Solid is aimed at individuals and teams with work they lack the time or expertise to do, and the site lists builders and operators at large companies, universities, and public sector organizations. On integrations, the position is that none are required in advance: agents can connect through an API, build a missing integration, or operate a website, desktop software, or phone app directly, using the access you approve. Pricing is subscription-based, with the full monthly payment becoming one balance for AI usage, machines, and purchases the agents make, with no extra platform fee. Starter is $40 per month for getting started with a focused task, a simple app, or a small workflow; Pro is $160 per month for regular work, active app building, and more room to test and iterate; Max is $640 per month for heavier workloads, larger apps, and several projects running at once. The trial lets you start with $20 on Solid. A Solid API lets you deploy always-on agents inside your product, and an enterprise offering adds access, budgets, policies, and approvals across a workspace, running on Solid Cloud, in your own VPC, or on-premises depending on your setup. The takeaway Solid offers is a shift from assisted work to delegated work. By giving agents their own computers, accounts, and budgets, and by letting them handle setup, repair, coordination, and verification, the product aims to let you hand over a goal — a sales demo, a researched lead list, an evaluation run, a production fix, or a stalled ticket — and receive a checked result without supervising the steps in between. You keep the ground rules, the approvals, and the spending limits; the agents keep working, and they ping you when it is done.