93 posts tagged with "Consulting"

Enterprise AI solution engineering is not the practice of connecting a user interface to a large language model and calling the result production-ready. It is the discipline of converting a real business problem into an AI-enabled operating capability that is valuable, secure, reliable, measurable, governable and sustainable.

That requires much more than model knowledge. An AI solution engineer must work across business strategy, user experience, process design, data and knowledge architecture, AI engineering, cloud platforms, integration, cybersecurity, privacy, responsible AI, software delivery, evaluation, operations, FinOps and organizational change.

The central question is therefore not:

Which model should we use?

It is:

What business capability are we improving, what evidence will demonstrate success, what is the safest and simplest architecture that can deliver it, and how will the organization operate it responsibly at scale?

This article provides a complete reference for answering that question.

Version note: This article reflects public guidance available on 21 August 2026. Laws, standards, provider services and AI capabilities evolve quickly. Regulatory interpretations should be confirmed with qualified legal, privacy, risk and compliance specialists for the relevant jurisdiction and use case.

A financial institution should not treat AI adoption as a race to deploy the largest number of models. It should build a repeatable decision system that selects valuable use cases, supplies governed data, constrains autonomy, proves performance, assigns accountable humans, and retires systems when benefits or controls deteriorate.

An AI solution engineer is often expected to understand models, data, APIs, cloud platforms and system architecture. Those skills matter, but they are not enough to make someone a trusted adviser.

Leads are not the goal. Engaged leads—people who raise their hand because something valuable made your offer relevant—are the goal. $100M Leads is Hormozi’s operating manual for advertising without mystique: there are only four core ways to let anyone know about anything, then four ways to get other people to do it for you. Master the Core Four at enough skill and volume, and lead scarcity becomes a choice, not a sentence.

Most acquisition problems are misdiagnosed as “marketing” or “sales” problems. Hormozi’s blunt thesis in $100M Offers: if strangers do not feel stupid saying no, your offer is weak—and no amount of clever ads, CRM sequences or closing scripts will save a commodity package. The book is Volume I of an acquisition stack: before leads and money models, engineer an offer so differentiated that price comparison becomes irrational.

Most sales advice is folklore: hire “hunters,” run motivational Monday, blame marketing for lead quality. Mark Roberge—MIT-trained engineer turned HubSpot’s first head of sales—built a formulaic, inspectable system that helped take HubSpot from early startup to roughly $100M: hire with a scorecard, train to a methodology, coach from metrics, generate demand inbound, align sales and marketing with SLAs, and run experiments like an engineering org. The Sales Acceleration Formula is the field manual for that machine.

Most “hard talks” fail because people argue inside the wrong conversation. Stone, Patton and Heen’s Difficult Conversations (third edition) shows that every tough exchange is actually three conversations at once: What Happened?, Feelings, and Identity. Shift from a battle stance to a learning stance, begin from the third story, and jointly map contribution—not blame. This guide walks the full book structure for practitioners in consulting, leadership and complex delivery.

Like it or not, you are a negotiator. You discuss fees with procurement, align sponsors on AI programme scope, settle vendor SLAs, and navigate internal priority fights that look like zero-sum battles but rarely are. Most people default to positional bargaining: take a stance, defend it, concede in small steps, split the difference. Fisher, Ury and Patton’s Getting to Yes—developed at the Harvard Negotiation Project and refined across decades of diplomacy, law, labour and business—offers a third path: principled negotiation. Decide issues on their merits, not through a contest of wills. Be soft on people, hard on the problem. Focus on interests, invent options, insist on objective criteria, and protect yourself with a real BATNA.

Most negotiation books teach what to say. Malhotra and Bazerman teach how the mind fails—and how to build a repeatable system that claims value, creates value, survives bias, and knows when to walk away. Negotiation Genius sits between Fisher and Ury’s principled method and Voss’s tactical empathy: analytic rigour plus behavioural science for deals that are complex, emotional, asymmetric, or outright ugly.

Most startups fail from undisciplined guessing—shipping a product nobody needs, chasing every market, or scaling before the economics work. Bill Aulet’s Disciplined Entrepreneurship (Expanded / Updated) replaces folklore with a 24-step operating system: narrow the customer, prove value, design acquisition, lock unit economics, then build and scale with intent.