Agentic Automation
Knowledge & Tools
Agentic Automation
The rigid rules of the past gave way to an agent that understands context and decides. We wire it into your site.
Our agentic stack
Claude Code
The terminal coding agent. Understands a whole codebase, edits multiple files, runs commands, connects via MCP. 88.6% on SWE-bench.
- Multi-file edits
- MCP tooling
- git workflows
OpenAI Codex
A fast coding agent from the terminal and in VS Code. #1 on Terminal-Bench (83.4%) for long tasks.
- CLI & IDE
- Long tasks
- Build automation
Google Antigravity
A multi-agent suite with desktop and CLI. A manager agent splits a task into subtasks that run in parallel, with scheduled tasks.
- Multi-agent architecture
- Parallel execution
- Background tasks
The connective layer
n8n, webhooks, and APIs wire the agents to CRM, forms, and the site. Here Make and n8n are still worth their weight.
- n8n & webhooks
- CRM hookup
- API integration
From idea to self-running workflow
Idea
Define what the process must do and where a human must stay in the loop.
Step 1
Build the agent
Build the agent with the right tools and access, and test it on real cases.
Step 2
Wire to the site
Connect to Next.js, CRM, and forms via webhooks. Everything flows to one place.
Step 3
Schedule & measure
Scheduled tasks run in the background, and we measure and tune.
Ongoing
The state of play (2026)
Codex (GPT-5.5) · Terminal-Bench #1
Claude Code (Opus 4.8) · SWE-bench
shorter process cycle time
hours a day — an agent doesn't sleep
Smart lead routing
Lead in → the agent reads intent and quality → classifies → sends to sales with a ready profile. No more forms falling through the cracks.
- Intent analysis
- Auto routing
Content operations
The agent drafts, updates meta, and prepares drafts on the site. You approve. The bottleneck moves from 'writing' to 'reviewing'.
- Auto drafts
- Meta updates
Scheduled tasks
Daily reports, CRM sync, monitoring, and alerts — running in the background without anyone needing to remember.
- Daily reports
- Background sync
Questions about agentic automation
Make, Zapier, and n8n run fixed rules: if X then Y. That's great for connecting systems, but they don't 'understand' anything. Agentic automation adds an AI agent that reads context and decides what to do — even in cases no rule was written for. In practice we combine both: the agent is the brain, and the connective tools execute.
They're very relevant — as a connective layer. When you need to link a form to a CRM or move a value between two systems, they're simple and they work. What changed is that the 'thinking' part moved to an AI agent. We don't replace them, we place them correctly.
That's why you set boundaries. We define where the agent acts alone and where a human must approve — money, deletions, and customer messages always go through sign-off. Good automation is also knowing what not to automate.
Which of your processes still runs on rigid rules?
Tell us, and we'll build an agent that understands context and wire it into your site and systems.
Build automation