Blog
Deeper looks at the features behind the release notes — how they work, and why we built them that way.
Series
How Agent Anything connects to the platforms teams already run — Slack, Missive, and more — and what each integration unlocks.
The easiest way into a company is often through software its people already trust, delivered as a routine update. We asked an agent, working in a sealed-off workspace with nothing to steal, to check a new release of an AI coding tool before anyone installed it. Here is what it found and why that matters.
Read post →Teams bringing AI into sensitive work need to know what it worked with, what it was authorized to do, where it ran, and what its checks reported. Here is how we build a workspace that answers those questions as the work happens, and why outside evaluators are starting to ask them.
Read post →An AI agent can become part of how other people know you, work with you, and experience your professional capabilities. Not a replacement for you, and not an impersonation of you. Part of how you're present. Knowing my context is not the same as having my consent.
Read post →Most enterprises now have agents in production, and the only two signals anyone watches are whether the job ran and what the monthly bill looks like. A harder question is which of those agents is actually earning its keep. The answer is already in your telemetry; it just needs someone, or something, reading it.
Read post →When teams adopt AI, the temptation is to build forty separate bots or manage forty different conversations and project folders. Intelligent workspaces take a different shape: the context, the evidence, and the decisions for one body of work stay together.
Read post →The hardest thing to explain about Agent Anything is what memory is for once more than one person and more than one AI tool are involved. This short video shows two engineers working in different tools, a product owner asking their own assistant, and one organizational memory with a name on every note.
Read post →The safest agent is not necessarily the one with the fewest capabilities. An agent constrained so tightly that it cannot use judgment is often not useful enough to justify having it.
Read post →In late 2024, while building Memory Box, we started on an idea we called a Memory Pack, a way to package the knowledge behind human-AI work so someone else could continue from it. BlockWyre is now using Agent Anything to carry expertise developed in its own agents into separate client environments.
Read post →When an MCP connector changes what an agent can do, yesterday's approval should not automatically carry forward.
Read post →More people, agents, vendors, and tools can produce more output without leaving behind more shared understanding. The problem is not that organizations use many tools. It is that the work fractures along the same boundaries.
Read post →Most AI tools are built around conversation, and disappear once the session ends. Attexa Arc is a private, durable environment where models and agents do governed work instead, and where your organization, not the model, keeps the context, authority, and evidence.
Read post →An Internet-Draft now before the IETF proposes a standard for AI-agent action receipts. It is a good sign for the category, and it maps closely to the governance architecture we already run in Attexa Witness and Verified Actions.
Read post →Most headlines about AI agents right now are about agents breaking their boundaries. Here's a quieter example: two unrelated agents, a governed shared memory, and a real commitment that came back to the person who had genuinely forgotten making it.
Read post →A real example from our own team: before an industry dinner, Agent Anything checked a guest list against the CRM, verified what mattered against outside sources, and corrected what was wrong, all before the first guest walked in.
Read post →OpenRouter's acquisition proves model access is worth billions. But choosing a model isn't the same as giving it somewhere to work. Here's how Agent Anything, Agent Fleet, and Attexa fit together.
Read post →Missive's native AI assistant now connects to Agent Anything as MCP servers: the Bridge turns an email thread into a shared Thinktank note, and a personal Memory Box key tucks a private one away.
Read post →Slack is one of the core ways Agent Anything reaches a team: Thinktank notes publish to a channel automatically, and anyone can ask the bot a question right where they're already working.
Read post →Most AI has memory now. What still hasn't caught up is what happens to it once it matters to more than one person. How the Personal Assistant, Thinktank, and sub-agents keep context durable and owned by the organization, not the vendor.
Read post →A short introduction to Agent Anything and to this blog, including the recurring "Agent Anything knows..." series we're starting here.
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