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Page 22 of 66
Insights on AI, machine learning, and technology strategy
A crafted public GitHub issue tricked an agentic workflow into posting private repo contents as a public comment. Narrower read access wouldn't have stopped it alone — the write path needed its own check.
The voice model keeps listening while it hands the hard part to another model in the background, then picks the conversation back up like nothing happened. That's the feature. It's also the reason nobody can reconstruct what occurred during the handoff.
Microsoft's Aspire team turned merged product PRs into draft documentation PRs automatically. The numbers are good. The reason it works is that almost none of the judgment calls were left to the agent.
NVIDIA and Hugging Face argue that agent behavior is a data problem, not just a model problem. Here's the disclosure sheet an operator should ask for before an agent gets approved for real work.
Alberta says Claude Code scanned 466 million lines of government code in 20 hours. The business lesson isn't the speed. It's the receipt that lets a human verify, test, approve, and revisit every fix before it ships.
Kimi K2.7 Code is available to Copilot Business and Enterprise, but GitHub ships the policy off by default. That is not a footnote. It is the review moment.
Ask a Mac admin which AWS account a developer's Claude Code install is actually authenticating against, and most can't answer without opening a terminal and guessing.
Constructed diagramThree bad Lighthouse runs can justify an investigation without justifying a code change. Use a blocking-work receipt to choose a fix, more measurement, or no change.
Rewst's new AI agent can turn a plain-language request into a runnable MSP automation. The safer question is whether the client can see the route before it touches QuickBooks.
GitHub Copilot session streaming gives enterprises a new kind of evidence: prompts, responses, and tool calls. The urgent question is who pulls the 48-hour record before it disappears.
Cursor just put a merge button in your pocket. Before Remote Control goes on for the whole team, decide what a phone is allowed to approve, review, and never touch alone.
A reversible workflow shortlist helps small-business owners choose a first AI pilot by review evidence, undo path, data boundary, owner, and first safe AI role.
Dive deeper into the subjects that matter to you
Implementation notes for building AI tools around real business data, handoffs, review queues, and safeguards.
Product notes, service updates, and BaristaLabs news that affect how small teams use AI at work.
AI market news translated into workflow decisions, risk boundaries, and practical next steps for small businesses.
Model concepts explained through thresholds, queues, and error costs that small teams can actually manage.
Plain-language guidance for owners and operators choosing one useful, reviewable AI workflow at a time.
Hands-on guides for approval policies, shadow weeks, agent receipts, and other AI workflow controls.