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European companies facing CSRD obligations needed strategic content to communicate ESG performance to investors and regulators. I produced in-depth ESG reporting case studies and thought leadership covering CSRD/ESRS compliance, developed strategic guides for CFOs and Sustainability Officers on double materiality and digital reporting infrastructure, and created investor-facing content linking ESG KPIs to financial performance.
Results: Positioned clients as recognised thought leaders in CSRD compliance. Improved investor engagement through clearer ESG disclosures. Reduced internal review cycles by standardising ESG content frameworks.
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Designing the moments between money and trust.
A few screens from an ongoing fintech product we’re working on.
Financial products have a strange design challenge:
they need to feel simple enough to understand, but serious enough to trust.
For this product, we’ve been working across flows like subscriptions, account management, portfolio-related information, and customer support — with a focus on making every interaction feel intentional.
The goal isn’t to make fintech “look modern.”
It’s to make complex things feel obvious.
Clear hierarchy.
Less cognitive load.
Stronger interaction patterns.
And a visual system that can scale as the product grows.
Still a work in progress — but here’s a little glimpse at where we’re heading.
The screens strike a good balance between reassurance and personality—the trust cue is clear without making the flow feel sterile. The card hierarchy also reads well at a glance.
Google's AI cited my client's LinkedIn post 11 times last
month.
He wasn't writing for you. He was writing for ChatGPT.
Profile views tripled anyway. Inbound doubled.
If you're a consultant or founder posting three times a
week, getting likes, and still waiting on inbound, this is the ranking game
you're not playing.
AEO. Answer Engine Optimization.
Someone types a question into ChatGPT Search or Google AI
Overviews. The answer comes with sources. LinkedIn posts are on that list.
Semrush ran 325,000 prompts. LinkedIn showed up in 14% of
ChatGPT Search answers.
Most of those citations went to individual profiles, not
company pages. Half came from accounts under 10,000 followers.
Quotability beat follower count.
What gets quoted (steal this):
1. One question per post
→ Line one is the
exact question a buyer would type into ChatGPT.
2. A plain-English definition inside 3 lines
→ AI lifts clean
sentences. It can't quote a vibe.
3. Your own dated numbers
→ "11
citations in August" gets cited. "Great results" doesn't.
4. A headline + About section that claim the topic
→ The model checks
who's talking before it trusts the post.
Check yourself in 5 minutes: type your ideal client's
question into ChatGPT Search and scroll the sources. If a competitor's post is
there and yours isn't, that's your next topic.
The feed forgets your post in 5 days. An AI citation keeps
answering for you for months.
(I'll say the uncomfortable bit: I think AEO beats the feed
algorithm for inbound by 2027. Most coaches selling algorithm hacks won't like
that.)
Two years from now: does a ChatGPT citation beat LinkedIn
reach for inbound, or is AEO just SEO in a new hat? Pick a side.
-- M Aadil A.
Good CRM reporting is only as reliable as the data behind it.
When I started working with Momentum AMP, one of the biggest challenges was inconsistent HubSpot data, which made it difficult for the team to fully trust its reporting.
What initially started as a data analytics engagement developed into a much broader HubSpot development and operations partnership.
I introduced daily data-quality monitoring to identify and resolve issues before they could affect reporting, while also building and improving automation across the CRM.
The work expanded into sales commission workflows, weighted deal assignment, customer success processes, reporting improvements and wider operational automation. I also supported projects including Stripe data cleanup and a Gemini AI integration.
For the SCC team specifically, I automated processes around lead rotation, outreach, post-mortem tracking and email distribution — reducing the amount of manual work required across their day-to-day operations.
The engagement has now covered more than 390 CRM tasks, with data-quality checks running every working day since September 2024.
The result is a HubSpot environment with more reliable data, stronger automation and reporting the team can actually trust when making decisions.
For me, this project shows why CRM optimisation starts with the fundamentals. You can build sophisticated workflows and dashboards, but if the underlying data isn’t reliable, the rest of the system can’t deliver its full value.
