Notes on getting work done by agents
Comparisons, prices as of this month, and what actually works when you hand a task to an AI agent. Written by the people who build and test them.
How to Debug AI Agent Tool Errors
To debug an AI agent tool error, read the run trace to find the earliest step that failed, identify which class of error it is, reproduce that single tool call in isolation, then fix it at the layer where the fault…
How to Create an AI Agent From a Template
To create an AI agent from a template, pick a prebuilt agent that already does the job you want, then customize four things: the inputs it reads, the trigger that starts it, the tools and accounts it connects to, and…
How to Connect an AI Agent to a Database
To connect an AI agent to a database safely, give it a dedicated, scoped credential, start with read-only access, expose the schema so it writes correct queries, validate and parameterize every query before it runs,…
How to Build an AI Agent With Memory
To build an AI agent with memory, you build two layers and connect them. The first is short-term working memory, the text the agent holds inside its context window during a single run. The second is long-term…
AI Agent vs Autonomous System: The Difference
An AI agent is a software system that perceives its environment, reasons about a goal, and takes actions using tools or APIs, typically with human oversight available at key steps. An autonomous system operates…
AI Agent Grounding and Hallucination Control
Grounding is the practice of tying an AI agent's outputs to verifiable external sources: retrieved documents, live tool results, database records, or structured reference data. Hallucination is the opposite…
AI Agent for Trello Board Automation
An AI agent can automate the repetitive card management work that keeps a Trello board running: creating and routing new cards to the right list, moving cards when their status changes, sending due-date nudges to…
AI Agent for Monday.com Status Updates
Yes, an AI agent can automate Monday.com status updates end to end. It reads item and group statuses across your boards, builds a plain-language rollup, flags anything overdue or stuck, and posts the result on a…
AI Agent for Jira Backlog Grooming and Hygiene
Yes, an AI agent can automate the most tedious parts of Jira backlog grooming: scanning for stale tickets, identifying duplicates, flagging issues that are missing estimates or acceptance criteria, and surfacing…
AI Agent for Gmail Label Automation
Yes, an AI agent can automate Gmail label application: reading each incoming email, classifying it by sender, topic, and intent, and applying the right label or set of labels without you touching the message. The key…
AI Agent for Front Shared Inbox Automation
Yes, an AI agent can automate the structural work of running a Front shared inbox: reading every incoming conversation, classifying intent, assigning to the right person, tagging for reporting, drafting a suggested…
AI Agent for Airtable Record Enrichment
An AI agent can enrich Airtable records automatically: it reads new or incomplete records, looks up missing field values from external sources, writes the enriched data back into the correct fields, flags potential…
AI Agent Emergent Behavior, Explained
Emergent behavior in AI agents refers to actions, strategies, or outcomes that were not explicitly programmed but arise from the interaction of an agent with its tools, its environment, or other agents at scale. It…
AI Agent Capability Maturity Levels Explained
An AI agent capability maturity model is a conceptual framework that describes, level by level, how much an agent can do without human involvement, how errors are caught, and what conditions must hold for the system…
What Is Agentic Reasoning? A Clear Explanation
Agentic reasoning is the process by which an AI agent decides what to do next, step by step, in order to reach a goal. It is what separates an agent from a standard language model response: instead of answering in…
AI Agents for Mortgage Brokers: Docs and Rate Watch
Mortgage brokerage runs on documents, deadlines, and rate windows. Missing one borrower item can delay a closing by weeks; a rate move you catch late costs a client real money. AI agents handle the operational layer,…
AI Agents for Medical Billing: Claims and Coding Support
Medical billing teams spend a significant portion of every day on work that is structured, repetitive, and rule-driven: scrubbing claims before submission, sorting denial codes, looking up modifier rules, and chasing…
AI Agents for Law Firm Intake: Triage and Follow-Up
Law firm intake is where potential clients either become clients or leave for the next firm on their list. The quality of the intake experience, specifically how quickly the firm responds, how clearly it…
AI Agents for Insurance Agents: Quote, Renew, Follow Up
Insurance agents spend a significant portion of their working week on tasks that are structured and repeatable: sending renewal notices, following up with new leads, collecting application documents, and updating…
AI Agents for Architecture Firms: RFPs and Specs
Architecture firms run on two parallel tracks: design work and coordination work. The design track is where principals earn their fees. The coordination track, proposals, spec updates, submittal logs, RFI chains,…
Tool Calling vs Function Calling: What's the Difference
Function calling and tool calling describe the same core behavior: a language model emits a structured request for an external capability, and the runtime executes it. The terms are often used interchangeably, but…
AI Agent Reflection and Self-Correction Explained
Agent reflection is the process by which an AI agent evaluates its own output, identifies problems, and revises the result before returning it. It is how agents catch their own mistakes without requiring a human in…
AI Agent Long-Term Memory Strategies, Explained
Long-term memory in an AI agent is any mechanism that stores information outside the active context window so it can be retrieved in a future session. Without it, an agent starts fresh on every run: no record of…
AI Agent Determinism and Control: A Practical Guide
LLM-based AI agents are probabilistic by default: the same input can produce different outputs on different runs. This guide explains where that variability comes from and the practical techniques teams use to…
AI Agents for Staffing Agencies: Source and Screen Faster
Staffing agencies win or lose on speed and throughput. The agency that sources a strong shortlist first, screens accurately, and moves candidates through the process without losing them to slow communication gets the…
AI Agents for SEO Agencies: Automate Audits and Reports
SEO agencies spend a large portion of each month on work that is structured and repeatable: running audits, pulling rank data, building client reports, researching keywords, and monitoring competitors. AI agents…
AI Agents for SaaS Customer Success Teams
SaaS customer success teams are expected to do more with fewer touches: protect net revenue retention, accelerate time-to-value for new accounts, and surface expansion opportunities, all while the book of business…
AI Agents for PR Firms: Media Lists and Coverage Tracking
PR agency work is 60 percent research and tracking, 40 percent relationship and strategy. Every pitch requires finding the right journalist, reading their recent coverage, personalizing the hook, and then monitoring…
AI Agents for Etsy Sellers: Automate Your Handmade Shop
Running an Etsy shop means doing the creative work and the shop operations yourself, usually at the same time. Every order needs a confirmation message, every shipped package needs a tracking update, every listing…
AI Agents for Dropshippers: Automate Orders and Suppliers
AI agents for dropshippers handle the operational work that scales badly with humans: routing orders to suppliers, syncing tracking numbers, sending customer updates, and monitoring supplier stock and prices. You…