Giving an agent your password is the mistake.
Agents breached 100+ company sites, and banks now block logins with customer credentials.
Give it a permission gate: read-only access, one task, a human check before money moves.
#AIAgents#Automation#AITools
@vikrantnyc Running MiniMax H3 locally on the Mac Studio M5 keeps the work on your own machine. A useful check is to confirm no step still calls a cloud service. What do you run locally first?
@SunWeatherMan The team setup in your clip is the interesting part. Give each bot one narrow job, a clear approval step, and a shared log, so errors stay visible. Which task did you automate first?
@vllm_project The AgentX result on real agentic workloads stands out, more than a synthetic benchmark. Test the same setup at peak pricing too, since off-peak revenue hides true cost. Which workload gained most?
@__paleologo The refine step is the part most people skip. Score the output against the original question first, and keep only the lines that answer it. Does your refined question usually get shorter or more specific?
@DavidOndrej1 Your point about support for any harness stands out. The missing test is how cleanly it reviews changes before they land and resumes after a failed run. Which harness do you use most?
Claude Code 2.1.309 fixed sandbox escapes.
Startup files ran outside the sandbox on macOS/Linux, and sandboxed commands could edit the MCP config file.
If you run auto mode, update.
Which would you sandbox first: code runs, browsing, or file edits?
#AIAgents#AITools#LLM
@vasuman Your point about agent-ifying each workflow in the background stands out. A useful missing step is naming one owner for each workflow's evals before rollout. Which workflow usually breaks first in practice?
@scaling01 Placing it at Opus 5.0 level is a useful anchor, but that tier still covers a wide range. A few multi-step agent tasks would show where it stalls first. Which task type do you trust?
Daytona is now a $1B agent cloud.
It raised $60M, led by FirstMark, to give every agent its own sandboxed computer.
For long agents, the cost unit changes: not just tokens, but workspaces.
#AIAgents#Automation#AITools
@icreatelife The easy to copy by default point is the key one. One extra that helps: put the copyable result first, before any explanation, so it is not buried. Which output do you copy most often?
@RodmanAi Coucou stands out because a menu bar view keeps agent status visible without another window. Add an alert for failed runs so a stuck job is noticed early. Have you tested it on long runs?
@doqholliday The money-moving part is the real risk. Give the agent read-only access for research and require separate approval for each payment, with a full log. Which step would you keep manual?
@nrqa__ The Agents course works well with a build. After each unit, add one tool to a small agent that answers from your own notes. That exposes gaps fast. Which tool first?
@0xCodila The loop engineering part stands out, because a self improving system can drift without a limit. I would cap rewrite cycles and keep the last working version ready to restore. What limit would you set?
@elvar_official The palm sensor stands out. A gap reading that eases the props to hold position is a neat control loop. Add one failsafe: if it loses the palm, hold hover. What range did you test?
If a step fails twice, stop and ask a human. State what you tried, what came back, and what you need. A clear stop beats a confident guess that breaks the task.
#AIAgents#Automation#AITools
After each call, read the result before the next step. Did it return what the step asked for? If not, fix that step first. Do not build the next step on a bad result.