Who do you work with as an AI automation consultant?

Operations-heavy teams of roughly 10–50 people: agencies, professional services firms, and growing startups. The common thread is a team losing real hours every week to repetitive work that a system could handle.

Why work with an independent AI automation consultant over an agency?

With an agency, you pitch a senior partner and get handed off to junior contractors learning on your dime. With me, the person who scopes the architecture is the person who writes the code and puts it into production. You get faster turnaround, no communication telephone games, and direct accountability.

What tools and platforms do you use for workflow automation?

I build with Asana for workspace architecture and task rules, Zapier for cross-tool integrations, and custom TypeScript services or LLM frameworks when reasoning is needed. I focus on reliable tools your team already uses, building fail-safes so automations don't break silently when field names or API quotas change.

How long does an automation project take?

A single automation is usually one to two weeks. A connected system across a few tools is more like three to four. Scope is agreed before any work starts.

Do you work hourly or fixed price?

Fixed-scope, fixed-price only. No hourly billing. We agree what's being built and what it costs, then I build it.

What tools do you use to build automations?

Usually Asana for project tracking, Zapier for workflow automation, direct APIs for system integration, and LLM-powered agents (often with RAG) where reasoning is needed. No custom software is built unless off-the-shelf tools can't do the job.

Do we own the automation you build?

Yes. When it's done, it's yours, running in your tools, on your accounts, with documentation so you or another developer can maintain it without me.

Field Notes

Writing on AI, automation, and shipping real things.

Build logs, strategy, and industry breakdowns. Specific over conceptual — written to be useful, not to fill a calendar.

Tags:

Build LogAI AgentsQualityWorkflowGatekeeper

12 min readOctober 12, 2026

Nobody grades their own exam: I open-sourced my release gate

The gate from my AI agent workflow is now a free, open-source tool any coding agent can install. It grades every claimed task against the real code, wakes a fleet of fresh AI reviewers, and refuses to ship without a receipt. Some of the reviewer methods are borrowed from smarter people, and they get their credit here.

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StrategyAI AgentsQualityWorkflow

17 min readOctober 4, 2026

A simplified flow of the AI agent workflow in flat vector style: problem, think, brief, build, check, gate, ship, all resting on a bar labeled the library

My complete AI agent workflow, from problem to shipped software

The full workflow I run to ship software with AI agents: think first, build against a frozen copy, let four checkers and a deterministic gate judge the result, then ship with a receipt. Walked through end to end, grounded in a real failure from my Seepient project, and the working summary of my book The One-Person Engineering Team.

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IndustrySeepientOpenAIGrokAI Agents

9 min readOctober 1, 2026

Cover image for openai dots grok bot vs seepient

OpenAI Dots and Grok Bot Are Here. Seepient Made a Different Bet.

OpenAI just launched Dots and xAI launched Grok Bot, two takes on the always-on AI worker. I built Seepient, and I think they got the ambition right and the relationship wrong. Here's the honest comparison.

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Build LogSeepientAI Agents

5 min readSeptember 29, 2026

A flat vector building with four pillars marked with a lock, cycle arrows, ledger lines and a plug, standing on a dashed replaceable foundation block

AI Agent Architecture: How I Design Agents a Business Can Depend On

Most AI agents work in demos and fall apart under real load. This is the architecture I use: layers, approval gates, fallback chains, and vendor freedom, so an agent survives the days a business actually needs it.

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StrategyAI Agents

7 min readSeptember 29, 2026

Cover image for custom ai agent development

What Custom AI Agent Development Actually Involves (From Someone Who Builds Them)

Custom AI agent development is less about clever prompts and more about approvals, memory, and failure handling. Here is what the work actually looks like when it has to survive a real business.

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StrategyPart 3AnalyticsStrategyGA4AI AgentsSmol Analytics

9 min readAugust 29, 2026

Side-by-side comparison diagram of Smol Analytics vs Google Analytics 4 for business leadership

Smol Analytics vs. Google Analytics 4: The Practical Guide for Growing Businesses

A candid comparison between Smol Analytics and Google Analytics 4 on performance, implementation costs, privacy, and how AI agents are rendering legacy dashboards obsolete.

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Build LogPart 2AnalyticsAI AgentsNext.jsSelf-HostingSmol Analytics

11 min readAugust 28, 2026

Zyntopia telemetry pipeline connected to self-hosted Smol Analytics and Antigravity AI agent

How I Implemented Smol Analytics for Zyntopia: Self-Hosted Setup and Autonomous AI Monitoring

A complete build log of how I implemented Smol Analytics (created by Arjun Patel) on a private VPS, instrumented Zyntopia's Next.js application, and connected AI agents for autonomous monitoring.

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IndustryPart 1AnalyticsAI AgentsOpen SourceSmol Analytics

10 min readAugust 27, 2026

Smol Analytics architecture showing cookieless ingestion and native AI agent integration

The AI-Native Analytics Engine: Introducing Smol Analytics for Modern Businesses

How Smol Analytics replaces legacy tracking bloat and complex database clusters with a single cookieless binary, a universal ingestion API, and 94+ native AI agent tools over MCP.

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StrategyPart 3AI AgentsDeepSeekProduct DesignUX

7 min readAugust 18, 2026

Flat vector illustration of a modern split-pane AI workspace layout with modular interface panels and dynamic canvases in warm cream, charcoal, and blue.

Designing the UI & UX for a Centralized Business AI Hub

A plain chat box is fine for Q&A, but terrible for real business execution. Here is the product and UX blueprint for a dual-pane AI workspace that turns modular agent workflows into an intuitive daily power tool.

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IndustryPart 1AI AgentsDeepSeekOpen Source

7 min readAugust 18, 2026

DeepSeek Harness: Why the Future of AI Coding Isn't a Black Box

Most AI coding assistants are closed appliances, with everything hardwired into a single box. DeepSeek Harness treats every capability as an interchangeable plugin on a shared baseplate. Here's why modular architecture matters for growing teams.

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StrategyPart 2AI AgentsDeepSeekSoftware Architecture

10 min readAugust 18, 2026

Flat vector illustration of a central AI switchboard connecting to diverse business apps and isolated data trays in cream, charcoal, and blue.

How to Build a Centralized AI Hub for Your Business (Without the App Sprawl)

Building separate apps for every AI feature leads to subscription chaos and fragmented data. Here is how the DeepSeek Harness blueprint lets you power your company's entire AI stack from one centralized, adaptable platform.

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Build LogAnalyticsAI AgentsNext.jsSelf-HostingOpen Source

7 min readAugust 14, 2026

The AI-Native Analytics Stack with Smol Analytics and MCP integration

The AI-Native Analytics Stack: Why We Switched to Smol Analytics (and How to Set It Up)

Why we moved away from bloated analytics trackers to a self-hosted, cookieless single binary that interfaces directly with AI coding assistants over MCP, along with the complete step-by-step setup guide.

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