Instrument x Seth Akkerman
Projects Custom GPT for Creative Agency

Custom GPT for Creative Agency

A custom ChatGPT bot built for Instrument that answers questions about the agency's culture, leadership, values, and case studies — pulling live data from internal Google Docs via a custom function.

What if a creative agency had its own AI that actually knew the place — the culture, the clients, the case studies? That’s the idea behind this v1 build: a custom GPT tuned specifically for Instrument, designed to help anyone quickly get up to speed on who the agency is and what they’ve made.

How it works

The bot is configured with a few layers of knowledge. First, PDF files covering culture, leadership, and about pages are uploaded directly as GPT knowledge — so it can answer questions like “who leads Instrument?” or “tell me about the culture” without needing to browse the web. Second, and more interestingly, a custom function connects to a Google Doc that aggregates case study summaries. When someone asks about client work — say, Nike — the bot calls that function, pulls the relevant summaries, and synthesizes a response on the fly.

This same Google Doc pipeline already powers an internal Brief Buddy tool used by the business development team, so the infrastructure was already trusted and maintained. Plugging the GPT into that same source means case study answers stay current without any extra maintenance work.

The guardrails

One thing worth noting: the instructions explicitly tell the bot not to search the broader internet. It only references uploaded knowledge files and the connected case study doc, and it’s prompted to clearly say when it doesn’t have specific information. That kind of scoping is important — you want an agency bot to be accurate and on-brand, not confidently hallucinating project credits.

Why it matters

This is a pattern that scales. Most agencies, studios, and product teams are sitting on a goldmine of internal documentation that’s hard to navigate. A tuned GPT with the right knowledge files and a live data function becomes a low-friction onboarding tool, a pitch prep assistant, or a culture reference for new hires. The personality layer isn’t fully baked in this v1 — that’s the obvious next step — but the infrastructure for a genuinely useful internal AI agent is already there.

Applying this to your project

  1. Start from the GPT Builder “Configure” tab, not a code repo — there’s no repository to clone here. Open a new Custom GPT in ChatGPT and treat the Instructions field as the one thing you’re really “copying”: the wording that tells the bot its scope, tone, and what it should refuse to do.
  2. Set up your own data connection before touching Actions. This bot’s Action points at a specific Google Doc URL (the same one behind the internal “Brief Buddy” tool). You’ll need your own Google account with edit/view access to whatever doc or sheet you want to pull from, and you’ll need to authorize that account inside the Action’s Authentication settings — this is the step most likely to silently fail if permissions aren’t right.
  3. Swap the PDF knowledge files entirely. The “culture, leadership, and about” PDFs are specific to Instrument — replace them with your own org’s equivalent docs (about page, leadership bios, culture deck). Keep them short and clean; the GPT reads them verbatim, so messy formatting shows up in messy answers.
  4. The critical integration point is the Actions schema, not the PDFs. The OpenAPI-style schema you paste into the Actions tab defines exactly what fields the GPT can request from your doc (e.g. client name, summary text). If your source doc’s structure doesn’t match what you describe in that schema, the function call will return nothing useful — test it with a few real queries before considering it done.
  5. Keep the “don’t browse the internet” guardrail language in your Instructions. It’s what stops the bot from confidently hallucinating case studies or facts it wasn’t given. If you drop this line when adapting the prompt, you lose the main thing that makes this trustworthy for agency-facing use.
  6. Don’t expect a personality layer for free. As shipped, this is v1 — functional but plain-spoken. If your use case wants a distinct voice, that’s an explicit follow-up pass on the Instructions field, not something the knowledge files or Actions setup will give you automatically.

Other ways to repurpose this

Product Design

Web Design

Marketing

Branding

Dependencies

OpenAI Custom GPTs (GPT Builder) n/a — no-code platform, not a versioned package The host environment the bot is built and configured in; provides the chat interface, the Instructions field, and the knowledge-file upload used to give the bot its Instrument-specific context.
OpenAI GPT Actions n/a — no-code platform The custom function layer that lets the GPT call out to an external API mid-conversation, used here to fetch live case study summaries instead of relying on static text alone.
Google Docs API n/a — no-code platform Backing data source queried by the custom Action to pull aggregated case study summaries — the same Google Doc that already feeds the internal Brief Buddy tool used by business development.
PDF Knowledge Files n/a — static uploaded documents, not a package Uploaded reference PDFs (culture, leadership, about) the GPT reads directly so it can answer static questions without needing an API call or internet access.
Role
Creative Technologist
Tools
ChatGPT OpenAI GPTs Google Docs API PDF Knowledge Files
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