How to set AI spending limits so agents can run freely
A clear budget is what lets you hand AI agents bigger jobs. Three numbers and one owner per agent get you there.
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Australia's planned AI safety laws: what's coming by 2027?
Canberra wants the most powerful AI built on proven safety systems, borrowing ideas from banks and airlines, so Australians can use it with confidence.
What is Google's Gemini agent? An AI coworker with its own email
Google has introduced an AI that gets a work account like a new hire, knows who approves what, and keeps a log of what it did.
Should an AI agent use your login? Why its own account is better
Give every AI agent its own identity and you can see exactly what it did, hand it more work and switch it on or off with one click.
What is GPT-6 Intelligent UI? ChatGPT now answers with buttons
This week ChatGPT learned to hand you sliders, charts and tiny tools instead of just paragraphs. Here is what changed and who gets it.
ChatGPT switched to GPT-6. How do you check your AI still works?
Model updates are usually good news. A short re-test tells you whether they are good news for your work.
Log your AI near misses before you have to explain an AI incident
The cheapest AI lesson is the one caught just before it reached a customer — if someone writes it down.
Every password in a shared doc is a permission your AI can find
Agents act on whatever access they can reach. Credentials left in docs, sheets and chats are access you never meant to grant.
Most AI pilots are designed to avoid the real work
Clean pilots skip permissions, exceptions and ownership, so they succeed on paper and then stall in production.
Before December, find every customer decision your AI is quietly shaping
From 10 December, many Australian businesses must explain where computer programs make or substantially inform significant decisions. Start mapping them now.
Your best AI use case may be the one nobody sees
Internal handoffs, follow-ups and approvals often pay back faster than the customer-facing demo.
Your AI should never approve a change to who gets paid
Payee and bank-detail changes need an out-of-band human check, because a convincing request is exactly what scammers now generate.
Overnight AI work needs a morning judgment queue
Agents can work while you sleep. The morning should bring a short stack of decisions, not a flood of notifications.
Your AI rules should say what never goes into the chat box
The most useful AI rule for a small team is a short list of data that never gets pasted into any tool.
Your best employees are becoming unpaid AI system integrators
Your top performers are burning hours carrying context between tools instead of making the calls only they can make.
Your AI agent needs an off switch someone has actually tested
Pause, override and take back control should be rehearsed before go-live, not discovered mid-incident.
Your team needs one place to see AI work in progress
Hidden in-flight agent work creates duplicate effort, collisions and missed approvals.
Your AI vendor will not carry the blame for what your agent does
Regulators are asking who is responsible when an agent acts. The business that deploys it should assume the answer includes them.
Automation breaks when the process gets interesting
Happy-path demos look fine until exceptions, incomplete inputs, or conflicting rules appear.
Your AI should learn from corrected work
Fixing the same mistake weekly means the company pays twice and the workflow never compounds.
The AI tool your team loves may be your most expensive shadow system
Popular unsanctioned tools fragment context and create invisible ops risk.
Your AI policy is useless if nobody can apply it mid-workflow
Paper policy is not governance; rules must show up as permissions, approvals and stops during the work.
A good AI handoff should survive the person who designed it
If the workflow dies when its creator is away, the business does not own it.
Your AI agents need role-based access, not identical access
Shared company memory is not a reason to hand every agent every credential.