First AI

First AI is UK’s #1 AI Adoption company.

✅ For Businesses – Gain a competitive edge with Microsoft Copilot. We run adoption programs, train your staff, and build AI workflows tailored to your needs.

✅ For Microsoft Partners – White-label our Copilot readiness and adoption services to drive better customer ROI and retention.

✅ For Recruitment Companies – Access a ready-made AI talent pool. Our AI Adoption Academy produces certified AI Adoption Managers, equipped to deliver impact.

She Shapes AI

She Shapes AI is an international award celebrating female trailblazers in developing and using AI responsibly.

Expert Reviewer

Zzazz

Kunato uses deep learning algorithms and neural networks to dynamically price internet content in real-time. Our vision is to change the way people create, consume, buy and sell information online.

I'm on the executive team, building a world-class AI-first organization.

Advisor

DN Capital

DN Capital is a global early-stage venture firm, with an experienced team passionate about technology and working with exceptional entrepreneurs.

AI Advisor

RLDatix

Allocate Software, later acquired by RLDatix, is the leading provider of complex workforce management software. It has an international footprint serving 800 businesses and 2 million end users.

Scaling engineering, sales and entering into new markets.

Strategic Operations Director

HgCapital

Hg Capital is one of the leading private equity firms with $55bn AUM.
My specialisation was investments in growth-stage technology companies.
As the technical expert on the team, I led initiatives to elevate technical understanding of all the investment professionals at the fund.

Investor

Seed, Series A and growth stage investor in internet and software businesses. 

Award: Exit of the Year by Unquote / Mergermarket

Deutsche Bank

Advised blue-chip technology companies on M&A, IPO and fund raising.

Award: Renewable IPO of the Year by Euromoney

Investment Banking - Technology, Media & Telecoms

Microsoft

Software Engineer

Christina Chen is the results-driven CEO of First AI Group, who has taken on the mission to make Artificial Intelligence accessible. As a leader in enterprise AI adoption, she advises governments, businesses and educators on strategy, AI talent development and innovation.

Her background includes over 20 years of experience in technology, uniquely combining deep technical expertise as a former Microsoft software engineer with business leadership in scaling high-growth technology companies.

She founded First AI Group for her younger self—to create a pathway for young people, especially from underrepresented backgrounds, to access cutting-edge AI opportunities.

Championing a human-centred approach to AI adoption, she teaches that AI is only as powerful as the people who use it, which helps businesses move beyond AI hype to real-world AI application to ensure tangible results.

Christina Chen

Supporting Jeavio's startup portfolio with product and technology strategy. CTO at eCare Vault (via Jeavio). Previously CTO at SentiSum. 

I understand that technology is a competitive advantage and is key to reducing costs and increasing revenue while minimizing risk. I am conscientious, result-oriented and enjoy working in high-pressure and multicultural environments.

Rushi Luhar

I am excited to be back in #Vadodara and to host the next session of the Vadodara AI Meetup community. Come along to our offices on the the 31st (more details in the comments) as I talk about Jeavio's AI journey over the last 4 years. 

I will cover:
- Lessons learnt as we built and scaled our AI practice
- Some mental models that help us think about AI
- Risks, tradeoffs, and design decisions
- Bad dad jokes and terrible memes

Looking forward to seeing you there!

AI Strategy, Education, and Advisory | I help you build things | CTO @ Jeavio

I wanted to build QuietReads for twenty years. I built it in two weeks. I built it for me.

I love reading, and I got fed up of apps like GoodReads that push gamification, streaks, and social integrations. I wanted somewhere to track what I was reading, consolidate my notes, and go deeper in the topics that interested me. 

Every few years, I'd sketch out the features, maybe design a database schema, then abandon it when the scope of what I wanted to build overwhelmed the time I had to spare. I had a day job. I had kids. So, QuietReads stayed in the drawer.

Last summer, I tried building it with AI coding tools. Replit, Cursor, early Claude Code. The results were miserable (see comments). Buggy code, agents going off the rails, subtle breaks everywhere. I gave up.

Then came Thanksgiving. Anthropic ran a limited-time promotion giving Max subscribers $1000 in API credits for Claude Code. Opus 4.5 had just launched. I tried again.

Where earlier models required constant hand-holding, Opus 4.5 (via Claude Code) understood what I was building. It made architectural decisions that made sense. It found root causes instead of spinning its wheels. Two weeks later, the MVP for QuietReads was live.

I am not the only one who is having a "Claude Code" moment. 

Boris Cherny, the creator of Claude Code, recently shipped 259 pull requests in a month without opening an IDE. Every line written by Claude Code. Something is shifting in how software gets built. Assumptions we've made about timelines, team size, and what's worth building need to be revisited.

My experience building QuietReads (and working on client projects) over the last month has shifted my view of what's possible more than anything in my 20+ years of building software. 

I am excited and terrified about what comes next.

Longer post on my blog:

Open article: Building at the Speed of Thought by thinking.luhar.org

LLMs are changing the way I think about software. 

For most of my career, I've thought deterministically. Decision trees, test coverage for every branch, predictable paths through code. If the user asks X, fetch Y and so on. This works when you control the inputs. 

But conversational interfaces break this model. When I built an AI Assistant for my book tracking app QuietReads (see comments), I couldn't predict which context any question would need. "What should I read next?" requires the want-to-read list. "Something like my last book, but shorter" requires recently finished books and filtering by length. "What were my thoughts on that dystopian novel?" requires notes.

The traditional solution is routing logic that guesses what data to fetch. It gets unwieldy fast.

Tool calling offers an alternative: define well-described functions and let the model decide which to call. You're moving routing decisions from compile-time (hardcoded logic) to runtime (model inference). The model becomes the router. With good tool schemas and capable models, this behavior is predictable, and you can bound costs with max tool call limits.

The tool descriptions matter as much as the code. A phrase like "Always call this BEFORE recommending books" changes model behavior significantly. Tool schemas are a new API surface, with all the versioning and maintenance implications that come with it.

There are significant tradeoffs. Costs vary based on conversation complexity. Testing becomes more complex because you're evaluating model behavior, not just code paths. But you gain flexibility and a clean separation between what data exists and when to fetch it.

Tool calling is really a form of context engineering. You are trying to figure out what to give the LLM and navigate tradeoffs around token costs, accuracy, and performance. For an old backend developer like me, building AI-powered applications has required a change in mindset. 

More details, code examples, and a discussion on my tradeoffs can be found on my blog: https://lnkd.in/eskB9hf5

Open article: The Lego Model: How Tool Calling Changes the Way We Build AI Applications by thinking.luhar.org

The Lego Model: How Tool Calling Changes the Way We Build AI Applications

taplio

The Battle

Christina Chen

Rushi Luhar

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taplio

The Battle

Christina Chen

Rushi Luhar

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Rushi Luhar's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreRushi Luhar's LinkedIn Performance