Compare · Claude Code / DIY AI

Claude Code makes you the developer. We already did that part.

Advisors are building their own deliverables with Claude Code — raw context in, polished output out. It genuinely works. It's also a slower, riskier version of the workflow PREZENTD already runs. (Using Claude to design slides instead? See PREZENTD vs Claude Design.)

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Should advisors build their own AI deliverable workflow with Claude Code?

Some do, and it works — raw notes in, polished output out. But the DIY loop means re-prompting per client, files in desktop folders, no versioning, no firm brand system, and often no data-processing agreement under the client data being pasted in. PREZENTD is that same workflow productized: templates, one-click refills, firm voice, controlled sharing, and enterprise-grade AI data handling on every plan, from $149 per month.

Here's what's actually happening: advisors are taking raw context — notes, numbers, a rough idea — and telling Claude Code to "build me this." And it does. Michael Kitces has written about exactly this shift: domain experts building their own tools instead of waiting on vendors. The demand is real, and the DIY route proves it. (If you're reaching for Claude to design slide decks rather than to code, see our PREZENTD vs Claude Design comparison.)

But look at the loop these advisors end up running. The output gets saved to a folder on the desktop. Next client, they prompt Claude again to redo the whole thing. Want to change one number or one sentence? You ask the chat and wait — slow, costly, and different every time. There's no brand system, no firm voice, no reuse, no versioning. And because most of this happens on consumer or Pro plans, there's typically no data-processing agreement and no zero-data-retention guarantee underneath the sensitive client information being pasted in.

That loop can work for a very small independent practice with time to spare. For everyone else, it's a worse version of a workflow that already exists. PREZENTD is the productized version: the same idea — your context, your expertise, AI doing the heavy lifting — with templates, firm voice, one-click refills, controlled sharing, and enterprise-grade AI data handling built in for every plan.

Side by side
 Claude Code / DIYPREZENTD
Sales intelligenceProspect context lives in scattered prompt files you maintain and re-paste by hand.A sales intelligence layer carries each prospect's pains, objections, and blockers into every build — no re-prompting.
The loopPrompt from raw context, save the output to a folder, re-prompt the whole thing for the next client.Build once, save it as a firm template, refill it for the next client in minutes.
Changing one valueAsk the chat to redo it and wait — slow, costly, and slightly different every time.Edit the field directly. No AI run, no waiting, no drift.
ReuseA desktop folder and a prompt you hope behaves the same way twice.A shared template library with versions linked to each client.
Brand & voiceWhatever the model produced that day, unless you re-specify everything per prompt.Firm voice and brand applied from settings on every build — they can't drift.
Client dataConsumer and Pro tiers typically lack the data-processing agreements and zero-data-retention that enterprise buyers get.Enterprise-grade handling on every plan: zero-data-retention routing, no model training, a SOC 2 Type II audited platform.
Across the firmEvery advisor's homegrown setup produces different output — consistency is luck.One workflow and one library; every advisor produces the firm's standard.
Who maintains itYou do. The prompts, the folder, the fixes — you're the developer now.It's software. We maintain it; you advise clients.
Real costPer-user AI subscriptions plus the hours you spend being your own engineer.About $28 per seat per month on Team — workflow, templates, and sharing included.
The DIY loop

Save to a folder. Re-prompt for the next client. Repeat forever.

The DIY route has a shape, and every advisor doing it knows the shape: generate something good, save it to the desktop, then re-prompt the entire thing when the next client needs one — and hope it comes out consistent. It's real work product, which is why people put up with it. But nothing persists, nothing compounds, and the person maintaining the whole contraption is you. That's time a very small practice might have. Most firms don't.

  • Every new client restarts the loop from scratch — output never becomes an asset.
  • PREZENTD keeps the idea and removes the loop: refill, don't rebuild.
It's not software

When editing one number means asking an AI and waiting, you don't have a tool — you have a chat.

A deliverable built in a chat can only be changed through the chat: re-prompt, wait, re-check, pay again. PREZENTD's output is software-grade — named fields you edit directly, versions linked to each household, templates your whole team refills, and shared links that stay fixed at exactly what the client saw. Fast, free to change, identical every time.

  • Edit values directly — no AI round-trip for a number, a name, or a sentence.
  • Versions, history, and snapshot-stable client links come standard.
The security gap

Sensitive client data deserves better than a consumer AI plan.

The uncomfortable part of the DIY route: client financials are being pasted into tools where consumer and Pro tiers typically don't carry the data-processing agreements or zero-data-retention guarantees that enterprise buyers negotiate. PREZENTD routes every customer AI request through enterprise, zero-data-retention endpoints — no model training on your data, built on a SOC 2 Type II audited platform, with a public Trust Center — on every plan, not just the biggest one.

  • Zero-data-retention AI routing and no model training, standard for all plans.
  • Built on a SOC 2 Type II audited platform, encrypted in transit and at rest, public Trust Center.

The wrong comparison is PREZENTD vs the Claude plan you're DIY-ing on.

Almost nobody runs the DIY loop on an enterprise agreement — it happens on Pro and Max, the plans on a personal card. That's the wrong benchmark. The guarantees a compliance officer asks about — no training, zero-data-retention, negotiated deletion and breach terms — are what enterprise buyers get, not what consumer plans ship with.

PREZENTD's benchmark is that enterprise tier. Everything in our column below ships on every plan, including the trial.

 Claude Free / Pro / MaxClaude for Work / EnterprisePREZENTD — every plan
Model training on your dataOn Free, Pro, and Max, chats can be used to train Claude unless you turn the setting off.Commercial plans don't train on your data by default.Never — no model training on your data, on every plan.
AI data retentionConsumer retention can run up to five years.Zero-data-retention is an arrangement Enterprise accounts make — not a plan default.ZDR-only routing — model providers do not retain your prompts or outputs.
Sensitive-data screeningClient data you paste reaches the model exactly as you pasted it.The same general-purpose pipeline — nothing screens advisor-specific data.Prompt-injection detection and sensitive-data redaction (SSNs, card numbers) before content reaches a model.
Platform & isolationA personal account and a desktop folder — no firm workspace, no tenant boundary.Workspace admin controls at the team tiers and above.SOC 2 Type II audited platform, encryption in transit and at rest, org-scoped tenant isolation.
Client-facing sharingOutputs saved to the desktop and emailed as files you can't pull back.Same — workspace controls govern chats, not the file you exported.Encrypted, time-bound, revocable links backed by versioned records.
Exit & incident termsStandard consumer terms — no negotiated deletion or breach commitments.Negotiated per enterprise agreement.Deletion on cancellation and 72-hour breach notification, on every plan.

General-AI columns reflect Anthropic's published plan documentation as of July 2026. Tiers and capabilities change — check vendor pages for current terms.

FAQ

Questions advisors actually ask

Are advisors really building deliverables with Claude Code?

Yes — it's one of the clearest trends in the space, and Michael Kitces has written about advisors building their own tools this way. It proves the demand is real. PREZENTD exists because that workflow deserves to be actual software: the same idea, without the prompting loop, the desktop folder, or the maintenance burden.

What's actually wrong with saving outputs to a folder and re-prompting per client?

Nothing persists. The next client means regenerating the whole deliverable and hoping it comes out consistent. Editing one value means another AI round-trip — slow, costly, and slightly different each time. And the brand, voice, and structure only hold if you re-specify them in every prompt. PREZENTD replaces that loop with a template you refill and fields you edit directly.

Is my client data safe in Claude Code?

It depends entirely on your plan, and that's the problem. Consumer and Pro tiers typically don't include the data-processing agreements or zero-data-retention guarantees that enterprise agreements provide. PREZENTD routes all customer AI requests through enterprise zero-data-retention endpoints, never trains models on your data, and runs on a SOC 2 Type II audited platform — on every plan.

Isn't the DIY route cheaper than PREZENTD?

On the subscription line, maybe. In reality you're paying per-user AI subscriptions plus your own hours as the builder and maintainer — and re-prompting full regenerations isn't free either. PREZENTD's Team plan works out to roughly $28 per seat per month with the workflow, template library, brand system, and secure sharing included, and nobody at your firm has to play developer.

What can I hand to my compliance department or OSJ?

A one-page compliance summary built for exactly that, at /security/compliance-summary: SOC 2 Type II audited platform, US data residency, no model training on your data, ZDR-only AI routing, 72-hour breach notification, and deletion on cancellation — in plain English, with the full detail on our security page.

Do I have to stop using Claude or Claude Code to use PREZENTD?

No. Keep them for research, drafting, and actual coding projects. PREZENTD is where client deliverables get built, branded, reused, and shared — the workflow piece the DIY route was approximating.

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Built on a SOC 2 Type II audited platform · No model training on your data · Security →