Agentic Workflow: The SDC Loop for Better AI Output

You've pasted the same brand guidelines, audience notes, and "please don't sound like AI" instructions into Claude four times this week, and the output still reads like everyone else's. That's usually the sign of a missing agentic workflow: a defined sequence your AI follows from plan to finished deliverable, with judgment built in at the right points instead of patched on after. The fix doesn't have to be a longer prompt or a more elaborate chain. It's a tighter loop.

This article introduces the SDC Loop (Strategize, Draft, Critique), a simple agentic workflow you can run in Claude, ChatGPT, or any AI tool that supports connectors. You'll see how each stage works, examples for ad creative, blog outlines, and outbound sequences, a comparison with prompt chaining, and answers to the questions teams ask most.

What is an agentic workflow?

An agentic workflow is a process where an AI model works through multiple steps toward a goal, using tools, context, and its own intermediate output along the way, instead of answering a single prompt and stopping. You define the goal and the checkpoints. The AI does the work between them.

For operators and marketers, the useful version is practical. If you ask ChatGPT for a cold email and it gives you one, that's a single response. If you ask it to look at your offer, decide on an angle for a specific segment, write the email based on that angle, then review the email against the angle before handing it back, that's an agentic workflow. The AI is acting on a plan, producing something, and evaluating what it produced.

Most teams already run informal versions of this. Someone asks Claude for a plan, copies the plan into a new message, asks for a draft, then pastes the draft back and asks "what's wrong with this?" The steps are there. What's usually missing is consistency in the judgment applied at each step.

Why most AI agent workflows produce average output

Large language models are trained to produce the most likely answer. Ask for a LinkedIn post, a landing page, or a campaign plan, and you get something that resembles the average of everything the model has seen. It's competent and forgettable, and your competitors are getting the same output from the same models.

Teams try to push past this by adding context to every prompt. Brand voice docs, examples of past wins, a list of phrases to avoid. Each conversation starts with a wall of pasted text, and each new teammate builds their own version of that wall. Over time this turns into Prompt Debt: a growing pile of prompts, snippets, and workarounds that nobody fully maintains, that break when the model updates, and that still don't reliably produce the output you want.

Chaining prompts together doesn't fix the underlying problem either. If step one produces an average plan, step two drafts an average deliverable from it, and step three critiques that deliverable using average criteria, you've built a more complicated way to get the same result.

What actually changes the output is the quality of judgment applied at each step. That expertise is what we've called the Judgment Layer: the set of decisions and corrections an experienced person makes that a base model won't make on its own. An agentic workflow without a judgment layer automates the production of average work.

What is the SDC Loop?

The SDC Loop is Strategize → Draft → Critique: plan with an expert's priorities, produce the deliverable, then have the same expert critique it before you ship. Maps to Callstand's three calls.

The key word in that definition is "same." In most AI workflows, planning, drafting, and reviewing all happen with different context, or with no specific context at all. In the SDC Loop, a single expert's judgment governs the entire process.

On Callstand, each stage maps directly to a call you can make to an expert connector: strategize, draft, and critique. You don't rebuild the context between stages because the expert's judgment travels with every call.

The SDC Loop at a glance

You can run the loop once for a quick deliverable or several times for something high-stakes. A typical pattern is one strategize call, one draft call, a critique, and a second draft that applies the critique.

How to strategize in an agentic workflow

The strategize stage is where most of the quality gets decided, and it's the stage teams are most likely to rush. People jump straight to "write me a sequence" because drafting feels like progress. But a draft built on a weak plan just gives you something polished to throw away.

A good strategize call answers the questions an experienced strategist would ask before writing a word. Who exactly is this for, and what would make them care? What's the one angle worth testing first? What should this deliverable leave out?

To get a useful plan, give the AI the inputs once and give them well. Your business, your offer, your audience, what you've tried before, and what worked or didn't. This is the core of the Brief-Once Workflow: you write a single strong brief instead of re-explaining your situation across ten conversations. In the SDC Loop, that brief feeds the strategize call, and the plan that comes back becomes the backbone for everything after.

When you review the plan, look for decisions rather than descriptions. A plan that says "target marketing leaders with a value-focused message" hasn't decided anything. A plan that says "target heads of growth at Series A SaaS companies whose blogs post fewer than four times a month, and lead with their publishing cadence" has. If the plan doesn't tell you what to skip, push back before moving on.

How to draft with the same expert context

Drafting is the stage where AI is already strong, which is exactly why it causes so much trouble. The model will happily produce a full article or a five-email sequence in seconds. The question is whose judgment shaped it.

In the SDC Loop, the draft is written with the same expert context that produced the plan. That means the draft inherits the plan's priorities without you restating them. If the strategist decided a sequence should be three emails, the drafter doesn't produce six.

Practically, this is where connectors earn their place. When the expert's judgment lives inside the call, you aren't relying on the model to remember a plan from forty messages ago. You pass the plan and the original inputs to the draft call, and the output reflects both.

Check whether the draft follows the plan or drifted toward something generic, whether it's actually finished, and whether it sounds like a person in your field wrote it. If not, take that into the critique stage instead of rewriting by hand yet.

How to critique AI output before you ship

The critique stage is the one teams skip most often, and the one that pays back fastest. Asking a general-purpose model to critique its own output rarely helps. It tends to praise the draft or suggest cosmetic changes. A useful critique needs a standard, and that standard has to be the same one that shaped the plan.

In the SDC Loop, the same expert who set the priorities reviews the draft. So the critique catches the things that matter to that expert specifically: an email opener prospects ignore, a blog post that buries the answer, an ad headline that doesn't connect to the visual.

The critique stage also works on work that didn't come from the loop. If your team wrote a landing page by hand, or an agency delivered a campaign, you can run it through a critique call before it goes live. Once you have the critique, send it back into a second draft call. One pass of correction usually closes most of the distance.

Agentic workflow examples using the SDC Loop

Ad creative

Strategize: You describe the product, audience, platform, and goal. The plan returns a single core message, visual concept, headline direction, and a clear list of what the creative should not include.

Draft: Headline, supporting copy, and detailed art direction.

Critique: Checks whether headline and visual tell the same story, whether the message is obvious at a glance in a feed, and whether the prompt leaves room for the image model to invent unwanted details.

Blog outline

Strategize: Target keyword, audience, and business context. The plan identifies what searchers want and puts the answer early.

Draft: Headings that use the main keyword where it fits, an intro that answers intent quickly, and an FAQ built around real questions.

Critique: Flags sections that don't serve the searcher and spots where the outline delays the answer.

Outbound sequence

Strategize: Narrows the segment, defines the problem that segment feels, and sets sequence length and CTA.

Draft: Full sequence with subject lines and body copy in plain colleague-to-colleague language.

Critique: Catches mass-outreach openers, skeptical claims, repeated benefits, and needless length.

SDC Loop vs prompt chaining

Prompt chaining connects a series of prompts so the output of one becomes the input of the next. The SDC Loop uses a version of it. The difference is where the judgment comes from and whether it stays consistent across steps.

How to run the SDC Loop in Claude, ChatGPT, and other AI tools

You can run a manual version of the SDC Loop in any AI tool today. Write a strong brief, ask for a plan, ask for a draft based on that plan, then ask for a critique against the plan's priorities. Even done by hand, separating these stages will improve your output.

The limitation of the manual version is the judgment itself. You're still relying on the base model's idea of what good looks like. MCP (Model Context Protocol) connectors remove that ceiling. Claude, ChatGPT, and a growing number of AI tools can call external connectors directly from the conversation.

Callstand is a marketplace of expert connectors built around this loop. Each expert packages their judgment into the three calls the SDC Loop needs: strategize, draft, and critique. You add an expert to the AI tool you already use, give it your brief once, and run the loop with that expert's standards applied at every stage.

If your current agentic workflow involves re-pasting the same context into Claude every morning, browse the experts on Callstand and try running one deliverable through the full loop.

Frequently asked questions