Why We Built TACT.md
Generative AI promised to change the way we work. For most people, it didn't. We built TACT.md so that anyone — not just developers — can turn their everyday workflows into autonomous, repeatable agentic AI systems using nothing more than a markdown file.
Gen AI tools failed to deliver
Despite the hype, generative AI tools fell short of actually automating the workflows that matter. Here's why.
Prompt & Pray
You still have to prompt. Every. Single. Time. You rely on out-of-date and incomplete training data, and the output leans toward a Western cultural lens that doesn't reflect your reality.
Data Confidentiality Risk
Want better results? You're told to “provide your own data.” But doing so means risking your confidential business information being exposed, stored, or used for model training.
No Safe Connections
There is currently no straightforward way to safely connect your tools — email, calendars, CRMs, ERPs — to generative AI. The integrations are either non-existent or dangerously opaque.
Agentic AI is the answer. But it's not enough on its own.
Agentic AI — where AI agents autonomously plan, reason, and act — is the real leap forward. But for most people, it's still too complicated. Building agents requires coding, infrastructure, and constant trial-and-error.
Platforms are emerging — Google Workspace Studio, Microsoft Copilot Studio, n8n, Claude Cowork, OpenClaw (NemoClaw) — but they all share one problem: they give you the engine without the road map. You get agents, but not agentic workflows.
That's the gap we fill. We developed the TACT™ Framework — Trigger, Agent, Connector, Tool — so that anyone can translate their existing processes into structured, deployable agentic AI workflows.
TACT.md is a product of Befinity AI. The TACT™ Framework was originally developed and documented on our Agentic AI Workflows blog, where we publish case studies, deconstructions, and deep dives into real-world agentic workflows.
“Agents on their own aren't worth much. What you need are agentic workflows.”
Why Markdown? Because it's the universal language of AI.
Markdown was created in 2004 by John Gruber with contributions from Aaron Swartz. Its goal was simple: a plain-text formatting syntax that's easy to read, easy to write, and converts cleanly to HTML. It was designed for writers, not programmers.
Today, Markdown is everywhere. Tools like Obsidian, iA Writer, and GitHub all use .md files as their native format.
And here's the fun fact: virtually every output created by AI — from ChatGPT to Claude to Gemini — is rendered in Markdown. It's the format AI thinks in. So when we say TACT.md, we mean it literally: your agentic AI workflows, defined in the one format that both humans and AI understand natively.
Your blueprint to build agentic workflows in minutes.
At TACT.md, we provide ready-made markdown blueprints. Simply download one and feed it to your AI tool of choice — Claude Cowork, Google Antigravity, OpenAI Codex, or any agent-capable system. The AI reads the blueprint and builds your workflow automatically. No code. No SDK. No friction.
Linear Workflows
Input → AI → Output — the simplest starting point.
Linear workflows are for people just getting started with AI automation. They are straight-forward, single-pass workflows: the user provides an input, the AI processes it, and delivers a perfectly structured output. Every. Single. Time. No back-and-forth, no prompt engineering, no inconsistency.
On-Brand Infographics
Provide your content and the blueprint generates a consistent, on-brand infographic — matching your colour scheme, typography, and layout — every single time.
Daily Intelligence Briefing
Tell the agent your areas of interest. Every morning at 8 AM, it scans multiple sources and delivers a curated intelligence briefing straight to your inbox.
Quotation Comparison Table
Upload 3–5 supplier quotations at once. The AI constructs a structured comparison table based on your requirements, and recommends which quotation to pick — with full rationale.
Reinforcing Loops
Feedback + Feedforward — workflows that get smarter over time.
Reinforcing loops are workflows that have both a feedback and a feedforward effect. Output from one workflow becomes input for the next, creating compound intelligence that grows with every cycle.
Email Drafting → Lead Intelligence
An agent drafts replies to customer emails. Simultaneously, it analyses the enquiries as lead indicators — informing your team on what customers care about and what to prioritise next.
Social Listening → Content Marketing
An agent posts content on social media as listening posts to gauge interest. It then uses the analytics and engagement signals to draft full-length articles for your website's content marketing engine.
Logistics Monitor → Auto-Reorder
A logistics agent monitors stock levels in real time. When thresholds are hit, it automatically recommends or triggers reorder actions — keeping your supply chain humming without manual checks.
Ecosystem Workflows
Your entire department — automated.
Ecosystem workflows are the endgame. Imagine an entire department — marketing, operations, client services — running on a coordinated network of agentic workflows. Multiple reinforcing loops working in concert as one intelligent system.
What an Ecosystem Looks Like in Practice
At Befinity AI, we run our own agent ecosystem — and we use it as the reference model for our TACT™ Ecosystem blueprints. Here's a glimpse of what that looks like:
Ready to turn your workflows into agentic workflows?
Download your first TACT™ blueprint. Feed it to your AI tool. Watch it build. It's that simple.