Practical how-to guides for setting up, configuring, debugging, and running AI agents in 2026. Every guide is tested. Every guide is short. Most apply to any AI agent platform; some are Gravity-specific and marked.
To set spending limits on an AI agent, give it three controls that work together: a per-run cap so one task cannot run away, a budget cap so total spend stays inside a window, and an auto-pause that stops the agent…
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To schedule an AI agent with cron, you write a five-field expression that says when the run should fire, attach it to the agent, and set the time zone explicitly. A cron schedule turns a one-off agent into a…
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An agent that never fails does not exist. APIs time out, tools return garbage, a model invents a step that was never asked for, and a permission check blocks an action halfway through a task. The question that…
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A team workspace for AI agents is a shared space where everyone buys, runs, and governs the same agents under one set of rules, instead of each person quietly building their own. The short answer to "how do I create…
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Connecting an AI agent to a private API is what turns a chatbot into something that does real work. The agent stops describing what could happen and starts reading your inventory, creating tickets, or pulling a…
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A data pipeline moves data from where it lives to where it is useful, cleaning and checking it on the way. The hard part is rarely the happy path. Sources change a column name overnight, a feed sends half its usual…
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To audit an AI agent's decision history, you reconstruct a single run from its log: the input it received, the plan it formed, every tool it called with the arguments and results, the final output, who triggered it,…
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A prompt is not documentation; it is the logic of the agent. Change a line and you change how the agent behaves, sometimes for the better, sometimes in ways you only notice three days later when results quietly…
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An agent that passes every test in the lab can still fail on its first real day. Test data is tidy; the real world is not. Going live is its own discipline, separate from proving the agent works on known cases, and…
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Some jobs are too big for one agent. Producing a competitor analysis means researching several companies, summarising each, and assembling a comparison; doing all of that in a single agent stretches it thin and makes…
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Most useful agent work is not a single action. Chasing an overdue invoice means pulling the ledger, finding what is overdue, drafting a message for each client, sending it, and logging the result. That is a…
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The fastest way to lose trust in an agent is to let it do something irreversible that it got wrong. The fix is not to supervise everything, which would defeat the point of automating, but to design the agent so a…
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Choosing an AI agent platform looks easy until you have to defend the decision to a CFO, a security review, and a procurement officer simultaneously. The marketing pages are interchangeable. The pricing is opaque…
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If you can build an AI agent in n8n, LangChain, make.com, or any of the other workflow tools that have eaten the last three years, you can earn from it. The path from a working workflow to actual recurring revenue is…
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"Training an agent on our docs" usually means fine-tuning in marketing copy and retrieval-augmented generation in code. The marketing version sounds fancier; the code version actually works for what most companies…
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Rate limits are the boring failure mode that takes out demos when they go to production. The agent runs fine on five test requests, then 500 requests arrive in a minute and a third silently disappear. This guide is…
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The first agent you ship has three tools. The third one has thirty. Somewhere between three and thirty, reliability cliffs and you cannot tell why. The cliff is real, the causes are predictable, and the mitigations…
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Most teams connect their first agent to Slack in 30 minutes using a personal token, then spend three weeks unpicking the consequences. This guide is the safe path from start: a bot app, narrow scopes, allow-listed…
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An agent that can put events on your calendar saves an hour a week. An agent that can put events on the wrong calendar costs you a customer. The difference is two layers of allow-listing, an explicit timezone…
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A human approval step is the cheapest insurance policy in agent operations and the most over-applied governance pattern. Done well it catches the actions that should never happen and stays out of the way for…
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Processes change. New CRM field, new approver, new review step, new tool. The agent that was right last quarter is silently wrong this quarter, and the gap shows up as runs that look fine on the surface but produce…
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An AI agent that has not been tested is an AI agent waiting to do something embarrassing or expensive on your behalf. Testing an agent looks different from testing software because the agent does not have a fixed…
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Sharing an AI agent with a team is the moment most agents quietly turn into a liability. The agent that one person built, supervised, and trusted now runs on inputs from people who did not write the prompt, with…
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An AI agent without a spending cap is an open tab on a model provider. Most of the time the bill is small. The expensive day is the one where the agent loops on a malformed input, or chains a search tool with itself…
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Restricting an AI agent to business hours is one of the cheapest reliability wins available. Most agent incidents are not catastrophic; they are awkward. An automated follow-up arriving at 3 a.m. looks like spam. A…
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One-shot prompts and recurring agent prompts look the same on the page and behave differently in practice. A one-shot prompt runs once; you see the output; you re-prompt if it is wrong. A recurring agent prompt runs…
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An agent stopped mid-task is not the same as an agent that finished. If the agent has already taken some actions and not others, the world is in an inconsistent state. A flight booked, a hotel not yet booked. A label…
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Setting up a first AI agent is straightforward in 2026. The platforms work, the model quality is high enough, and the integrations cover most things a small business or solo professional cares about. What is not…
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"Roll back the agent's action" is not one operation. It is four operations, each appropriate for a different tier of action. Treating all rollbacks as equal leads to over-engineered Tier 1 actions and…
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Code fails loudly. An exception is thrown, the process crashes, the error reaches the dashboard, the operator gets an alert. AI agents fail differently. The agent picks a wrong interpretation, takes a wrong action,…
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