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.
AI Agents for Nutritionists: What Actually Saves Time in 2026
The honest pitch for AI agents to a nutritionist or dietitian is not "scale your practice." It is "stop spending half your week on food logs, intake forms, and insurance paperwork that the client never sees." Most…
AI Agents for Healthcare Admins: What Saves Time in 2026
The honest pitch for AI agents inside a medical practice is not "AI doctor." It is "stop spending the front-desk's Tuesday afternoon on hold with United, calling about a prior auth that has been sitting in their…
AI Agents for Fitness Coaches: What Actually Saves Time in 2026
The honest pitch for AI agents to a fitness coach is not "10x your client roster." It is "stop dropping the Sunday-night check-in pile." Most online and hybrid coaches I talk to do not have a programming problem.…
AI Agents for Financial Advisors: Where They Save Time in 2026
The honest pitch for AI agents to a financial advisor is not "robo-advisor 2.0." It is "stop spending Sunday night writing the briefing notes for Monday's six client meetings." Most solo and small-team RIAs I talk to…
AI Agents for Course Creators: What Saves Time in 2026
The honest pitch for AI agents to a course creator is not "scale your course." It is "stop being the bottleneck on tier-1 student support during launch week." Most creators I talk to are not stuck on curriculum. They…
AI Agents for Bookkeepers: What Actually Saves Time in 2026
Bookkeeping runs on the same five tasks in a loop: categorise transactions, reconcile bank feeds, chase invoices, schedule bill payments, and prep the month-end close. Every one of those tasks is what an AI agent was…
AI Agent Update Cycles: Safe Change Management for Production Agents
Production AI agents need updates. Models improve. Prompts get tighter. Tools get added. The team finds a way to make the stopping rule clearer. The question is not "should we update" but "how do we update without…
AI Agent State Management: Memory, Checkpoints, and Durability
The single hardest non-model problem in agent engineering is state. The model is stateless. Every other part of the system that gives it the illusion of continuity, of memory, of resumption, is your code. Get it…
AI Agent Prompt Versioning: Storage, Promotion, Rollback
Code without version control is a hobby. Prompts without version control are a liability. The reason most agent prompts produce silent regressions in week six is not that the prompt got worse; it is that nobody can…
AI Agent Prompt Engineering: 5 Parts of a Production Prompt
Prompt engineering for AI agents is not the same craft as prompt engineering for chatbots. A chatbot prompt shapes one response. An agent prompt shapes a loop: the model picks a tool, reads the result, decides…
Multi-Agent Coordination Patterns: Supervisor, Peer, Market, Shared-State
The intuition that "more agents will do better than one agent" is wrong more often than it is right. Most production multi-agent systems exist because the work has genuine boundaries (different access controls,…
AI Agent Integration Patterns: Webhook, OAuth, MCP, Polling, Queue
Most AI agent failures in production are not model failures. They are integration failures. A webhook arrives twice and the agent acts twice. An OAuth refresh fails silently and the agent runs unauthenticated. A…
AI Agent Data Residency: EU, India, US Architecture Patterns
Data residency is one of the silent gating items for enterprise sales of AI agents. The product can be perfect, but if the prompts leave the EU, the deal dies. This guide is the architecture playbook for…
AI Agent Audit Trails: A Logging Design Guide
An AI agent's audit trail is the difference between "the agent took an action" and "we know why the agent took that action." It is what enables incident response, compliance audits, and the kind of post-hoc analysis…
AI Agents for SaaS Founders: Where They Actually Earn Their Keep
The honest pitch for AI agents to a SaaS founder is not "scale your team." It is "stop dropping the recurring five-to-fifteen-minute tasks that compound into churn." Most SaaS founders I talk to do not have a…
AI Recruiters in 2026: What They Screen and What They Miss
An AI recruiter is good at the half of recruiting nobody wants to do. It is dangerous at the half that decides someone's job.
AI Agents for Real Estate Agents: The Compliant Lead-and-Listing Stack
Real estate is one of the few industries where a single AI agent can be the difference between converting a lead and losing it to a faster competitor. Inbound buyer leads are perishable in a way that almost no other…
AI Agents for Marketing Agencies: The Real ROI Map
For most small-to-mid marketing agencies, AI agents are the difference between a 12% net margin and a 28% net margin on the same retainer book. Not because the agency hires fewer people, but because the agents soak…
AI Agents for Lawyers: Intake, Review, and Deadline Management Without Malpractice
Lawyers face the steepest constraints of any profession deploying AI agents in 2026 and the largest potential upside. The constraints are real: client confidentiality under Model Rule 1.6, competence under Rule 1.1,…
AI Agents for Freelance Designers: Run the Studio, Not the Drudgery
The honest job description for a freelance designer is "two roles in one person." Half the week is design work; half the week is studio operations. Intake calls. Scope clarification. Proposal drafts. Asset packaging.…
AI Agents for Ecommerce Stores: A Margin-First ROI Map
Open with margin, not vibes. A DTC store doing $1M ARR at a 65% gross margin and 7% net has roughly $70k in net profit and zero room to add headcount. An AI agent that recovers 2% of abandoned carts on a baseline…
AI Agents for Content Creators: Run the Distribution, Keep the Taste
Content creators in 2026 face a paradox. The tools to make and distribute content have never been more powerful, and the audience tolerance for AI-generated work passing as human has never been lower. The creators…
AI Agents for Consultants: The Proposal-to-Deliverable Stack
Consulting is a profession built on judgment, but a typical engagement is filled with the supporting work that produces the conditions for judgment: research, synthesis, slide drafting, meeting prep, status…
AI Agents for Accountants: The Reconciliation, Categorisation, and Client-Chase Stack
Accountants and bookkeepers face two pressures pointing in the same direction. Clients increasingly expect monthly close in five business days instead of fifteen. Margins on transactional bookkeeping are compressing…
AI Agent Security Best Practices: A 2026 Production Playbook
Most security guides written for large language models stop at the prompt boundary. They assume a single completion, no tools, no state, no autonomy. That model has not described production deployments for at least…
AI Agent Monitoring and Observability: A 2026 Production Playbook
The first time I shipped an agent without proper observability I did not notice quality degradation for nine days. Token costs were stable, latency was fine, error rates were nominal. The agent was answering…
AI Agent Governance and Compliance: A 2026 Operating Guide
For most of 2024 and the first half of 2025, AI governance for agents was a tomorrow problem. By mid-2025 it had become a this-quarter problem. The EU AI Act began entering force in stages, the NIST Generative AI…
AI Agent Cost Optimization: A 2026 Tactical Playbook
This is not a primer on AI agent pricing models. The taxonomy of per-token, per-task, per-agent, and capability-based pricing already lives at AI agent cost models explained. This piece is the operational sibling.…
Gravity vs Workato: Enterprise iPaaS vs Self-Serve Runtime (2026)
Workato and Gravity get put on the same shortlist when a buyer types "AI workflow automation" into Google and the search engine hands back both. The shortlist is misleading. Workato is an enterprise iPaaS. Gravity is…
Gravity vs Tray.ai: Low-Code Platform vs Sentence Runtime (2026)
Tray.ai and Gravity both ride the AI automation wave, but the buyer and the building experience are different. This comparison helps decide which category fits the work you have.