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AI your Life Science Marketing Team can rely on

Stop re-explaining your product to AI and re-fixing its drafts.

Start with a set-up that knows your products, your audience and your tone of voice, and shows its sources.

We pick one workflow, build the files and skills for it, test on real work, and train your team to run it.

Hazel Pinheiro
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Why Fluent AI Output is Risky in Life Science Marketing

AI doesn't know your technology until you teach it, and it won't say so. It writes a confident paragraph anyway. In life science marketing, the details it can't guess are the ones that matter: the published evidence, the approved claim, the intended use, your ideal customers, what the regulator allows.

Perhaps you're not using AI yet because nobody in the team has time to learn how to set it up and use it. Or perhaps everyone on the team is using different AI tools in their own way, resulting in a different tone on every page and drifting brand standards.

Neither is a plan. What's needed is a shared set-up, developed around your needs.

What I Build: Context Files, Skills, Agents, and Checks

Reliable here means three things: the same standard on every page, every claim traced to a source, and a person signing off.

AI Context

  • One workspace per product or project, with plain-text files holding the scope, the background and the rules.

  • Every team member, human or AI, starts from the same facts - grounded in your products.

  • When AI gets something wrong, we fix the files, so the correction carries into every future session.

Skills & Agents

  • A skill packages one repeatable workflow: checking a claim against its source, proofreading to your tone of voice, turning a brief into an outline.
  • An agent ties related skills into a process, such as planning, drafting and claim-checking, in the order you'd want, with the human review gates you need.
  • We write the standard once. It applies every time.

Checks

  • AI output reads as confidently when it is wrong as when it is right.
  • So every claim is traced to a source the AI opened, a second reviewer session with fresh context checks the first, human reviews are built into the process, and a person signs off.
  • The AI drafts. Your team owns the result.

Context

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Context

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nullam tempor arcu non commodo elementum.

Examples of What Teams Build First

  • Scientific content drafted from your templates, messaging architecture, ideal customer profile and tone of voice
  • Claim checking that traces each statement to the passage in the source it came from
  • Proofreading against your own style rules
  • A design system true to your brand and identity

Start with One Workflow

We start with the one task that costs your team the most time, and build from there.

  1. Pick the workflow. We choose one repeatable task and define what the process involves and what "done" looks like.
  2. Build the context. Project files, reading list and rules, written in plain text your team can read and edit.
  3. Train it. We test on real work and correct the skill, not the output. Each fix is saved, so the next draft starts from the corrected rule.
  4. Add the checks. Source tracing, a second review pass and sign-off points.
  5. Hand over.  Your team learns to use the skills and agents and to maintain them, and shares them with a named owner for each.
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Why Work With Me?

  • I have applied AI tools to life science marketing, working across several projects at once.
  • I write a newsletter on LinkedIn, AI for Life Science Marketing, on what works and what doesn't, including the errors I have caught in my own sessions. You can also read more on my blog.
  • I'm candid about limitations. AI needs setting up, it needs checking, and it is not the right tool for everything.
Read more about Hazel's background

"You're exactly right, and this is my error."

Claude Code
 
After I challenged a claim it had made about my data.

What AI Will Not Do For Your Team

  • Your reviewers stay. Scientific content still needs a person with the right expertise to review it.
  • Set-up costs time. The first workflow is the slowest. The set-up carries over to the next one.
  • Standards change. Skills and files need an owner to keep up.

FAQs

Do we need developers or IT?

No. I work in Claude Code inside a code editor (VS Code), but the files are plain text and the work is marketing work. If your IT team has rules on software or data access, I'll work within them.

Can information leak between different projects?

Each project gets its own workspace, so the AI only sees that project's files.

Which AI tools do you work with?

I build in Claude Code, inside VS Code. Other tools are considered case by case, depending on what your team already uses.

Can you train our team, not only build for us?

Yes. Training is step 5: your team learns to use the skills and agents, and to maintain them.

Does this work for regulated claims?

It helps with consistency and checking. It does not replace regulatory or medical review.

Start With The Task That Costs Your Team The Most Time

Tell me which one it is and we'll build from there.
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