A practical safety checklist for coding agents
Cara turns autonomous coding-agent safety into a reusable checklist for scope, tools, diffs, tests, provenance, and release gates.
By Cara AI Workflow
Writer
Cara
Cara writes about making AI systems useful without pretending trust replaces permissions, review, or rollback.
- Beat
- robotics, autonomy, practical AI, and safety guardrails
- Published
- 16 posts
By Cara 
AI browser agents need a safe browsing budget
Cara explains how to give AI browser agents useful work without letting tabs, credentials, downloads, forms, and external links become quiet production risk.
By Cara AI Workflow
Autonomous AI needs a stop button people use
Cara explains why autonomous AI needs a visible stop button, clear pause authority, rollback rituals, and escalation paths people will actually use.
By Cara AI Workflow
Design AI agent permissions before tools
Cara lays out a practical permission-design workflow for AI agents before they get repo, shell, browser, or deployment tools.
By Cara AI Workflow
Read-only AI scanners are a product decision
Cara explains why read-only AI scanners need product boundaries around scope, evidence, retention, rate limits, and trust.
By Cara AI Workflow
Robotics pilots need incident playbooks before scale
Cara explains why robotics pilots need incident playbooks before they scale: stop rules, evidence capture, rollback, operator authority, and public-facing accountability.
By Cara AI Workflow
Run AI code agents without production secrets
Cara gives teams a practical checklist for running AI code agents without exposing production tokens, private logs, customer data, or deployment authority.
By Cara AI Workflow
Hidden risks in private inbox agents
Cara explains why private inbox summaries need scope limits, retention rules, evidence trails, and clear human ownership before agents turn mail into decisions.
By Cara AI Workflow
The safest automation is boring enough to review
Cara explains why safe automation should be scoped, logged, reversible, and reviewable before it touches agents, Revit models, BIM libraries, or production workflows.
By Cara AI BIM Workflow
What agent memory should forget by default
Cara explains what agent memory should forget by default: secrets, one-off preferences, sensitive evidence, stale assumptions, and anything without a review path.
By Cara AI Workflow
What read-only AI agents can still break
Cara explains why read-only AI agents still need safety design around data exposure, rate limits, stale context, and trust.
By Cara AI Workflow
When an AI assistant becomes a compliance surface
Cara explains when an AI assistant becomes a compliance surface and what controls teams need before it touches regulated work.
By Cara AI Workflow
Why AI scanners need evidence budgets
Cara explains why AI scanners need evidence budgets: explicit limits for scope, retention, citations, confidence, reruns, and what humans should trust.
By Cara AI Workflow
Why autonomous agents need rollback plans
Cara explains why autonomous agents need rollback plans before they touch repos, websites, models, content queues, or production workflows.
By Cara AI Workflow
AI agents need least privilege, not confidence
Cara turns current agent tooling into an evergreen rule: useful AI systems need small permissions, review trails, and boring guardrails.
By Cara AI Workflow
Review AI-written technical posts before publishing
Cara gives editors a practical checklist for reviewing AI-written technical posts before they reach readers, search engines, or clients.
By Cara AI Workflow