El stack de IA para agencias en 2026: lo que realmente usamos en Geek Vibes — Geek Vibes Blog
Strategy & Business · 6 min · May 25, 2026
The AI stack for agencies in 2026: what we actually use at Geek Vibes
After testing dozens of tools, this is the real stack that powers operations at Geek Vibes Agency: coding, design, marketing, sales, content, and analytics. It's not the "30 best tools" list — it's what survived daily use and the KPIs we use to measure if it adds or subtracts value.
Practical close of the content pack. After literally testing dozens of tools over the last year (and cutting the ones that didn't deliver enough speed or quality), this is the stack that powers Geek Vibes Agency's operations in 2026. It's not the "30 best tools" list you see on LinkedIn — it's what survived daily use with real clients, real teams, and real budgets.
If you run an agency, an in-house marketing team, or a digital product, this will serve as a benchmark.
For coding and product
Claude Code + Cursor (combo)
I expanded on this in another post on this blog, but in short: Cursor for day-to-day IDE-first development, Claude Code for large refactors and autonomous tasks. It's not a binary choice — it's a complementary stack. We pay for both.
Claude API (Sonnet 4.6 as default)
Generation engine behind internal products. In GV Proposals, for example, it generates drafts of commercial proposals from client briefs. We use it with prompt caching (90% discount on cached input) to keep costs low on repetitive loads.
Locofy.ai
Design-to-code for Figma components. Not perfect, but it significantly accelerates converting mockups to JSX/React. Works best when design respects auto-layout and design tokens.
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Vercel for frontend (Next.js, mainly), Railway for backend + databases. Zero deploy friction, automatic scaling, decent observability. For a team of 4-8 devs, it's the sweet spot of cost vs capacity.
For design
Figma + Figma Make
Foundation of all UX/UI work. Figma Make specifically for early drafts and quick variant exploration. The State of the Designer 2026 confirms 72% of designers already integrated Figma AI into their workflow — we're included.
Galileo AI / UX Pilot
Galileo AI for quick UI component generation with brand consistency. UX Pilot for drafts and especially for predictive heatmaps that let us validate visual hierarchy before testing with real users.
Canva
Don't underestimate it. For internal commercial proposal templates (not final client-facing), Canva is brutal. Branded templates, quick generation, smooth collaboration with non-technical clients. We use it especially in the pitch and onboarding phase.
The complete outbound stack. Sales Navigator for identifying prospects with advanced filters. Apollo for enriching data and getting emails. Clay for enrichment and scoring workflows. Dripify for LinkedIn sequences. Each does one thing well — together they work better than any "all-in-one."
Zapier + Make
Glue layer between everything. When one tool doesn't integrate natively with another, Zapier or Make solve it in 20 minutes. Yes, there are recurring costs, but the savings in custom development more than offset it.
Claude API for mass personalization
For outbound at scale, we use Claude API in batch mode to generate personalized M2 messages (message 2 in outbound sequences) for each prospect's profile. 1,000 prospects, 1,000 unique messages relevant to their specific context. What used to take a junior SDR 2 weeks now executes in 1 day with quality human review.
For content
Claude (drafts and refinement)
For blog drafts, landing copy, video scripts. Claude has better tone handling and iterative refinement. ChatGPT works too — we use both depending on context and the team's personal preference.
Gemini Image / Nano Banana
Visuals for social and blog. Especially useful for hero images and editorial assets. Combined with good prompt engineering (see the prompts in other posts in this content pack), quality already rivals stock photography.
ElevenLabs
Voiceover for video and podcast when needed. Quality of synthetic voices good enough for professional production, especially in Spanish. We use it for internal pieces and some clients with tight budgets.
For analytics
Looker / Tableau / Internal BI Studio
Client dashboards. Looker for enterprise clients on Google Cloud, Tableau for clients on Microsoft stack or multi-cloud, Internal BI Studio (with PostgreSQL base) for projects where we want full control without additional licenses.
GA4 + Mixpanel
Product tracking. GA4 for traffic and attribution, Mixpanel for product events and funnel analysis. The combination covers 95% of needs without paying for enterprise plans.
Sentiment monitoring with Gumloop
When the client has high public exposure (consumer brands especially), we monitor sentiment on social and reviews. Alerts within 1-3 hours of a spike, which allows tactical response instead of damage control.
What we removed from the stack
For transparency, tools we tested and didn't keep:
Notion AI: we use it, but the AI-specific doesn't add up vs Claude/GPT.
Jasper: good for companies that need easy onboarding, but as an agency that already masters prompt engineering, the abstraction limited us.
Copilot for Microsoft 365: decent, but the team works in Google Workspace.
Synthesia and similar: generated videos still feel uncanny — we prefer real voiceover or ElevenLabs over slides.
The insight no listicle gives
The tool matters less than the workflow around the tool. Having Claude Code doesn't make you a better dev. Having Figma Make doesn't make you a better designer. Having Apollo doesn't make you a better SDR.
What matters is:
1. How you integrate it into your process.
A tool that doesn't connect to your flow is noise. Better 5 integrated tools than 20 disconnected ones.
2. What human decisions you preserve.
AI amplifies judgment. If judgment is weak, it amplifies weakness. If it's good, it scales it. Explicitly define which decisions stay with humans and why.
3. What KPIs you use to measure if it's adding or subtracting.
Speed without quality is speed to a bad output faster. Speed with maintained or improved quality is real gain. Measure both sides.
4. How you train your team.
Buy a tool without training, and it goes underutilized. Intensive workshops + supervised practice the first few days are non-negotiable. Without training, the most expensive tools can have negative ROI.
How much this stack costs
To dimension it: the complete stack described above, for a team of 12 people (mix of dev, design, marketing, ops), costs us approximately $2,500-$3,500 USD per month in aggregated licenses. Doesn't include API consumption (Claude, OpenAI, Gemini), which varies by project volume but typically adds another $1,000-$2,500 USD per month.
Versus what we save in human time, productivity, and competitive differentiation, the math is obvious. But only when the workflow is well-designed. If not, it's waste.
How we started (recommendation for small to mid-size agencies)
If you have a team of 3-8 people and want to build your AI stack, don't buy everything at once. This is the sequence we recommend:
Month 1: Claude/ChatGPT + Cursor for everyone. Get familiar with basic prompt engineering.
Month 2-3: Add Figma AI features for design, Claude API for internal automation.
Month 4-6: Outbound stack (Apollo + Clay + automation) if you sell B2B.
Month 7+: Advanced analytics and observability.
The curve is real but short when there's discipline and constant review.
Conclusion
If you want us to help you audit your current stack and design the right workflow for your agency or product, this is exactly what we do: comercial@geekvibes.agency.
And if you made it this far reading the full post, you already know more than 90% of agencies that are "thinking about starting to use AI." The best time to start was two years ago. The second best time is now.
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