180 stories
Every year, teams face the same decision: pay to patch brittle bots or switch to computer use agents that adapt to change. Here is what changes and why agents are now the durable option.
Pick the right Coasty CUA version for your workflow. v3 offers explicit control with a verifier, v4 runs autonomously with an on-board pass/fail check. Build robust computer use agents quickly.
Your RPA bots are breaking more often as UIs change, and your maintenance backlog is growing. Computer use agents survive those changes, follow SOPs directly, and scale where RPA stalls.
RPA bots break when UIs change, and manual SOPs only humans can follow. Computer use agents see the screen, recover from errors, and work on any app. Here’s how to automate the long tail of IT support without the maintenance treadmill.
Traditional RPA fails when UIs change or exceptions appear, creating blind spots in compliance. Computer use agents see the screen, read the result, and stay in control. Here is what changes for your governance and risk posture.
Manual resume screening kills deals and costs companies 3-4x a salary per hire. AI computer use agents are finally good enough to replace it. Here's how to actually do it.
Legacy RPA depends on brittle selectors that break with UI changes. Computer use agents see the screen, adapt, and follow SOPs directly. Here is how to move forward.
Traditional RPA breaks every time the UI changes, forcing your developers into a rebuild treadmill. Computer use agents let you automate changing processes without picking up a new set of brittle selectors.
Attended RPA bots break with every UI change, and manual SOPs sit on the shelf. Here is a pragmatic path to swap them for computer use agents that see the screen, follow the process, and adapt.
Traditional RPA halts on screen changes and errors, forcing constant rebuilds. Computer use agents see and adapt. See how agents reduce maintenance and costs while RPA stays in its lane.
Traditional RPA hits a wall when UIs change or exceptions show up. Computer use agents see the screen and adapt, offering a durable path beyond brittle bots and endless rebuilds.
Build a computer use agent that reads the screen and clicks on real UI elements. The /v1/predict endpoint turns a screenshot and instruction into raw actions like move_to, click, type. Learn the request format, loop, and pricing.
OpenAI's Operator is a marketing stunt. It controls real desktops but only succeeds 38% of the time on OSWorld benchmarks. That's worse than a junior dev. Here's why you should use Coasty instead.
Pause a computer use agent when it hits a barrier. Reuse the same machine and trajectory to resume exactly where you left off. Build agents that handle CAPTCHAs, approvals, and edge cases without brittle selectors.
Doctors spend 8 hours a day on EHRs. AI tools only complete 36% of 100-step workflows. Coasty achieves 85.6% on OSWorld, the best computer use AI agent that can finally automate real healthcare work.
Why are you paying $20 a month for a tool that can't even type correctly? OpenAI's Operator fails. Anthropic's Computer Use is buggy. You're wasting thousands per employee on broken automations. Here's the only computer use agent worth using.
73% of test automation projects fail. Selenium is brittle, expensive, and stuck in 2020. AI computer use agents don't break. Here's why you're wasting time on the wrong tool.
RPA projects often suffer from hidden maintenance costs when UIs change. Computer use agents can lower that cost and expand automation to processes that were previously impossible to automate.
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