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Field notes on reducing operational drag, building better follow-up, and turning AI into measurable business capacity.
We observed intermittent GPT delegation failures in a Linux-based multi-agent setup. Some worker sessions timed out during initialization; in another case, the parent stalled before launching a worker. Local logs also recorded failed thread creation (EAGAIN). All resident Codex clients ran under the same Linux user with a 512-task limit. Even when agents were idle,…
Read articleI recently upgraded a private AI gateway from an older release to a newer one. On paper, it sounded simple. In practice, it became a valuable lesson in careful engineering. The first upgrade attempt stopped because several required environment files were missing. Instead of forcing the deployment forward, we rolled back to the known-good version…
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Read articleClaude Science shows how AI workbenches can make advanced research workflows more auditable, repeatable, and useful for teams that need real operating discipline.
Read articleA practical AM Catalyst take on Anthropic Claude Science: AI workbenches become useful when they are tied to source control, workflow boundaries, and auditable operations.
Read articleThere is a quiet kind of operational issue that shows up in almost every growing automated system. It is not dramatic. It is not a system failure. It is not the kind of thing that deserves a war room or a sweeping rewrite. It is usually something much smaller: one remembered reference, workflow note, or…
Read articleAI readiness is not just a technology question. It is an operations question. Before a company deploys AI agents, it needs enough clarity around workflows, permissions, data, and decision rules for the agent to be useful without creating unnecessary risk. What does AI readiness mean for a business? AI readiness means the business has enough…
Read articleFollow-up is one of the simplest places to find hidden revenue leakage. The problem is rarely that a business does not care about prospects or clients. The problem is that follow-up depends on memory, inbox scanning, or owner availability. That is fragile. Why does follow-up break down? Follow-up breaks down when the next action is…
Read articleSearch visibility is changing from a contest for one blue link into a contest for trust, clarity, and extractable answers. Businesses still need strong websites, but ranking alone is no longer enough if AI systems summarize the answer before a person clicks. For AM Catalyst readers, the practical question is simple: can Google, answer engines,…
Read articleOperational drag is the hidden cost of work that moves too slowly, depends on memory, or requires the owner to push every next step. It usually does not look like one obvious failure. It shows up as repeated friction: a lead waits too long for a reply, a handoff depends on one person, or a…
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