Four situations where an AI agent should stop and ask a person first, what the person should see, and how to keep the queue short enough to stay careful.
Read the postHow knowledge bases and retrieval work for AI agents, and the common ways they go wrong: bad extraction, poor chunking, stale content and unchecked answers.
Governed is an overused word. Here is what it should mean when an AI agent is doing real work: boundaries, decision points, a record, access control and limits.
Where to place approvals in an AI workflow, what the approver should see, how to avoid rubber-stamping, and how to handle rejection and silence.
Four situations where an AI agent should stop and ask a person first, what the person should see, and how to keep the queue short enough to stay careful.
RSA, Okta and IBM all shipped agent identity and control tools in autumn 2026. What they claim, what is still unclear and what to do with a small team.
A plain guide to choosing between a fixed AI workflow and an autonomous agent, with a decision table and a hybrid pattern you can build on a canvas.
What Article 14 of the EU AI Act asks of human oversight, who it applies to, the new 2027 dates and how workflow builders can design for it. Not legal advice.
What an AI agent audit trail should record, how long to keep it, how to handle personal data in logs, and how retries and re-runs fit in.
Short-term, long-term and shared agent memory explained, with rules for what to store, how to expire it and what should never go in at all.
A one-page AI governance policy for teams that build workflows and agents: scope, roles, approval tiers, logging and review. Copy it and edit.
How to retry failed AI workflow steps safely: backoff with jitter, idempotency keys, rate limit headers, and what to do when retries run out.
A plain explanation of the Model Context Protocol for non-developers, how to connect a server in a workflow and the five risks worth checking first.
How to start a workflow from any system with a webhook and call any API with an HTTP step, plus the security basics: signatures, secrets and idempotency.
Build a failed-payment workflow around Stripe webhooks: triage by decline reason, draft a polite message, and keep a human on the cancel decision.
Build an invoice workflow that reads PDFs with AI, checks the numbers with rules, routes by amount, and keeps a person on every payment decision.
Context engineering means deciding what the model sees at each step. A practical checklist for workflow builders: instructions, retrieval, state and budget.
Build an onboarding workflow: collect documents, answer policy questions from a knowledge base and route access requests to managers for approval.
How hostile text in emails, documents and web pages can steer an AI agent, and a practical checklist of limits, gates and tests that reduce the damage.
A practical way to test an AI workflow before release: build a small test set, pick graders, read the transcripts and rerun after every change.
Build a support triage workflow: classify, answer from your knowledge base, gate by risk, and hand tricky cases to a person with full context.
Scanned or digital, Arabic or bilingual: how to extract fields from PDFs reliably, validate them and send doubtful values to a person.
What analysts say about agentic AI projects being cancelled, the causes behind it, and a four-week pilot plan with a scorecard you can use to decide.
The UAE announced a government-wide agentic AI programme in April 2026. What it says, what it does not, and how to set oversight for your own agents.
Stop using one model for everything. Match each workflow step to a model by difficulty, risk and cost, with a cheap-first router and a fallback plan.
Four things from the last few weeks that matter if you run AI agents at work: agent sprawl, the EU AI Act delay, the new MCP spec and what to do.
Where AI workflow data actually goes, what the UAE and Saudi personal data laws say about moving it abroad, and a checklist for choosing a deployment.
Five common ways AI workflows fail, what each looks like in a step-by-step run trace, and the fix. Illustrative patterns, not customer stories.
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