Every agency founder I talk to has hit the same wall. They started with ChatGPT. Then added Jasper for copywriting. Picked up Midjourney for client visuals. Installed Notion AI, Otter.ai for transcripts, Gamma for decks, and three other tools they tested for a weekend and forgot to cancel. The category has exploded — there are thousands of AI wrappers competing for your card details. By the last bank statement, most agency operators are paying for fifteen subscriptions and still producing average output.
The problem is not the tools. It is the lack of a minimalist AI tech stack. Most agencies have a pile of subscriptions with no logic connecting them.
According to Readless’s 2026 Subscription Fatigue Statistics report, the average person paying for AI services subscribes to four separate tools at about $66 per month — with 53% canceling and restarting tools in cycles. Most agency operators I know are well past that number. If this sounds familiar, the answer is not finding better tools. It is building a better stack.
What this post covers: How to build a minimalist AI tech stack in 2026 using three tools that actually connect. Written for B2B agency operators and creative directors who are already using AI and want to cut the subscriptions that drain money without producing results. By the end, you will know which tools to keep, which to drop, and exactly how they work together.
Table of Contents
Why Most Agency Stacks Are Broken
Most agencies build their tool stack the same way they accumulate SaaS subscriptions: one layer at a time, in response to a YouTube recommendation, a founder’s tweet, or a free trial that auto-renewed without anyone noticing.
The result is a collection of tools where each one gets used at about 30% of its capacity — because no one has time to master twelve platforms while also running client work. Tool bloat kills adoption. It also kills margin. Analysis of agency AI adoption patterns in 2026 consistently shows the same finding: agencies adopting five or more AI tools simultaneously show shallow usage across all of them, and the output per dollar spent drops with each additional subscription.
More tools do not produce better work. Better-connected tools do.
According to gend.co’s 2026 review of AI tools for marketing agencies, the winning principle is direct: “buy for function, not for hype, and the stack stays small, coherent, and cheap.” That applies to every B2B agency regardless of size or client roster.
What most agencies actually need is not a bigger stack. It is a leaner one with clear roles assigned to each tool — which is the entire premise of AI orchestration as a practice. When your tools each own a specific function and connect to each other, the stack stops being a collection of subscriptions and starts being a system.
The Minimalist AI Tech Stack in 2026 (The 3 Tools I Use)
These are the three tools that run client work at ByHarshal. Each owns exactly one function. None of them overlap with the others.
Tool 1: Claude (Anthropic) — The Thinking Layer
Claude handles everything that requires reasoning, long-form writing, and context retention: client strategy documents, creative direction briefs, long-form content, competitor analysis summaries, and presentation scripts. Claude’s context window is large enough to process an entire brand guide and produce copy that actually matches the client’s voice.
Where most agencies use ChatGPT as a generic prompt-and-paste machine, Claude works better as a structured thinking partner. Feed it a complete brief, a set of research notes, and a target persona, and the output needs minimal editing. The difference is context: Claude holds more of it, and uses it more reliably across a long piece of work.
Cost: Claude Pro runs at $20 per month.
Tool 2: Perplexity — The Research Layer
Before any client work begins, you need current, cited intelligence. What are competitors publishing? What are analysts saying about this space right now? What questions are prospects actually asking? Perplexity answers all of this with traceable source links, in real time.
The difference between Perplexity and a standard search is synthesis. Instead of scanning twelve tabs for competitive data, you get one structured answer you can act on. For B2B agencies, this cuts research time from three hours to under thirty minutes on most briefs. And unlike many AI tools that hallucinate sources, Perplexity shows its citations — which matters when you are building client deliverables.
Cost: Perplexity Pro is $20 per month. Running total: $40.
Tool 3: Make (formerly Integromat) — The Automation Layer
Make is where orchestration happens. It connects Claude outputs, Perplexity research, client CRMs, email platforms, Notion databases, and any other platform your agency uses. Without Make (or an equivalent like n8n), you spend the day manually copying data between tools. That is not automation. That is busywork with extra steps.
One setup from my own workflow: a client brief submitted through a Typeform triggers a Make scenario that pulls Perplexity research on the topic, passes it to Claude with a structured prompt, and drops the finished draft into a Notion client workspace — all without me touching anything until the draft is ready for review. The pipeline runs itself.
Cost: Make’s Core plan starts at $9 per month. Total stack spend: $49 per month.
How the Three Tools Connect in Practice
Most guides list tools and leave you to figure out the connections. Here is the exact pipeline for B2B content production using this three-tool stack.
Step 1. The client brief arrives — through Typeform, email, or a Notion intake form. It does not matter which. Make picks it up from any source.
Step 2. Make triggers Perplexity research on the topic. The output — current industry data, competitor angles, commonly asked questions — is structured and passed forward as a research block.
Step 3. Claude receives the research summary alongside the client’s brand brief and content objective. It produces an outline and a full draft. No context switching. No copy-paste between windows.
Step 4. Make takes the Claude output and routes it: creates a Notion page tagged by client, status, and deadline; fires a Slack notification to the client contact; logs the task in the project tracker.
Step 5. The draft sits in the client’s workspace, ready for review. The pipeline took four hours including review time. The manual version of this process took two days.
This is not theory. This is the live setup. For a broader look at how AI orchestration connects into a full client delivery system, the ByHarshal blog covers the underlying workflow logic across multiple posts.
What Gets Cut From the Stack and Why
When I say three tools, the first question is always: “But what about X?” Here is exactly where I stand on the tools people ask about most.
Jasper or Copy.ai. These are Claude with a subscription markup and a template library you will use twice. Claude does everything they do, and it does it with better context retention and no ceiling on output quality. There is no function Jasper owns that Claude does not cover. Cut them.
Zapier. Make covers every Zapier use case at a lower monthly cost, with more control over complex multi-step workflows. If you are on Zapier’s free tier and it is genuinely working, stay. If you are paying for Zapier’s higher plans, switch to Make and redirect the savings.
SurferSEO, Frase, or dedicated AI writing tools with SEO scoring. For research and content optimization, Perplexity plus Claude handles 80% of what these tools deliver. Reserve a specialist SEO platform only if you are running a high-volume SEO retainer service and need SERP tracking at scale. For most B2B agencies, it is a subscription for 20% of the value.
Notion AI, Microsoft Copilot, or any in-app AI shortcut. These add convenience inside a single tool. They do not replace a structured orchestration workflow. Make does more, across all your tools simultaneously, for less money. In-app AI adds a layer on top of the same problem.
The rule I follow: if a tool does not own a specific function that none of the three core tools can cover, it does not belong in the stack. Every tool that survives this test earns its cost. Everything else is a drain on margin and attention.
The full reasoning behind this stack philosophy is laid out in the AI Orchestra Workflow — which also covers how to structure client handoffs when you are running multiple accounts through this system.
Key Takeaways
- The average person paying for AI services subscribes to four tools at $66 per month and cycles through cancellations. Most agencies pay significantly more and get proportionally less.
- A three-tool minimalist AI tech stack covers the three functions that matter in a B2B agency: research (Perplexity), thinking and writing (Claude), and automation (Make).
- The total monthly cost for this stack is $49, less than a single seat on most enterprise AI platforms.
- Adoption rate per tool rises as stack size falls. Agencies running three well-connected tools consistently produce better output per dollar than agencies running twelve loosely related ones.
- Orchestration is the skill, not prompting. The Make scenarios that connect the three tools are what turn three subscriptions into a client delivery system.
- Every tool that cannot clearly answer “what specific function does only this tool own?” should not be in the stack.
- Switching to this stack is not about giving up capability. It is about recovering the margin, focus, and output quality you are currently losing to tool sprawl.
Frequently Asked Questions
Can a three-tool stack handle enterprise B2B clients?
Yes, with the right Make scenarios. Enterprise work usually adds complexity at the reporting and approval layer. You can add Looker Studio (free) for reporting dashboards without disrupting the core three. The three tools remain the production engine. Reporting is a separate layer. Most enterprise requirements fit inside this model with a few additional Make scenarios.
What if I am already deep into a different set of tools?
Audit your current stack by writing down the specific function each tool serves. If two tools serve the same function, cut the more expensive one. Start by identifying your research layer, your writing layer, and your automation layer. Consolidate toward one tool per function. You do not need to switch everything at once — run the transition across 30 days to avoid disrupting active client work.
Is Make harder to learn than Zapier?
Make has a learning curve of about two to three focused sessions. The visual workflow builder is more intuitive than Zapier for anything beyond a basic three-step automation. Most agencies have their first working scenario live within a day. YouTube tutorials for Make are current and detailed as of 2026. For teams already on Zapier, the logic transfers directly — Make uses the same trigger-action model.
What about visual tools like Midjourney or Canva for creative work?
Visual production tools sit outside the content and strategy pipeline this stack is built for. If your agency handles creative design, Canva Pro or Adobe Firefly can run alongside the three core tools without disrupting the logic. They serve production, not orchestration. Add them only when the creative production function has no overlap with what Claude or Perplexity already handle.
Does Perplexity actually replace a human researcher?
For competitive intelligence, trend tracking, and citation-backed summaries, Perplexity replaces the majority of what a junior researcher does in a B2B agency context. It does not replace strategic interpretation or client relationship context. Use it for information gathering, and apply your own judgment to what the data means for the client’s specific situation. The tool handles the research. You handle the insight.
Harshal Saraf is a Creative Director and AI Workflow Consultant based in Indore, India. Under his practice ByHarshal, he sets up AI workflows for founders, agencies, and brands across India. Where Creative Direction Meets AI Orchestration. He has led creative direction for brands and small and medium scale B2B businesses, and currently works as Creative Director and AI Strategist at Square Root SEO. He writes Oh, So AI, a Tuesday and Friday newsletter on AI tools, workflows, and productivity for founders and creatives.
