Daily roundup

AI agent news for small business: 29 October 2026

GitHub's plain-English agent workflows go live for everyone, Claude gets ready-made legal tools, and Microsoft opens up the agent engine behind Copilot.

1. GitHub Agentic Workflows is now generally available, letting you write automations in plain-language Markdown that coding agents run inside GitHub Actions

   It handles chores like sorting new issues, explaining failed builds and updating docs, and it's open to GitHub Free accounts too, though the default engine needs a Copilot license. The agents start with read-only access in a sealed-off sandbox, which is a good default to copy for any agent you set up.

   Source: GitHub. Related guide: How to keep an AI agent secure: a 9-step checklist.

2. Anthropic adds a gallery of ready-to-use legal tools to Claude, from contract review tables to cite checks, with every answer linked to its source

   Each tool opens with an example, Claude does the first pass, and a lawyer applies judgment to the result. If you have a pile of contracts or leases, the useful habit is the same at any size: let the agent pull out the terms, then check each one against the linked original language before you rely on it.

   Source: Anthropic. Related guide: Which AI agent actions need a human OK? A simple approval rule.

3. Microsoft makes the Copilot harness, the agent engine behind GitHub Copilot and Copilot Studio, available to build your own agents through Microsoft Foundry

   A harness is everything around the AI model: the instructions, tools, sandbox and controls that let an agent finish a job. Microsoft says it works with 20+ models and supports MCP (Model Context Protocol, a standard way to plug tools into agents) and agent skills, so you can switch models without rebuilding the rest.

   Source: Microsoft. Related guide: AI agent tools vs skills vs MCP: what each one is and which to turn on.

4. Jedify launches Data Agents: describe a business question in plain language and an agent watches your numbers on a schedule and explains what changed

   The agents only see the data the person asking is already allowed to see, and results can arrive by Slack or email. Even with simpler tools, that's the rule to follow: a reporting agent should get read access to the numbers it needs and nothing more.

   Source: Jedify (GlobeNewswire). Related guide: Connect only what you need.

5. Monte Carlo launches Bayes, an AI teammate that spots when other agents go wrong and proposes fixes for engineers to approve

   The company cites a 2026 study finding 74% of enterprises had pulled back or shut down a customer-facing agent after launch. It's an enterprise product, but the lesson scales down: test an agent on real examples before customers see it, and keep checking it after.

   Source: Monte Carlo (GlobeNewswire). Related guide: How to test an AI agent before you give it real access.

6. Articul8 releases Bivia, a decision model that gives agents yes-or-no and pick-one answers with a confidence score, and can decline when the evidence is thin

   The pitch is cost: many small steps in an agent's job don't need a big, expensive model, just a quick, checkable decision. Whatever you use, a cheaper model for routine steps and an "I'm not sure, ask a person" option are two easy ways to keep agent bills and mistakes down.

   Source: Articul8 (GlobeNewswire). Related guide: How much does an AI agent cost per month? The real costs and how to cap them.

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