People think that AI will accelerate software development by generating code. Coding is only a tiny part of the story. So much of software development precedes code, and these activities are usually the blockers that impede technology acceleration.
Before any code can be written, there is the question of what needs to be built. No work can begin until there is a purpose. Work requires time and resources, which necessitates investment. An investment needs a business case. This means getting to know what customers (users) want, what they are willing to pay for, and whether it would be worth building. You are not an AI accelerated software developer, if you have no purpose, if you don’t know what your customers want, or if you can’t justify the investment.
Traditionally, coders working in a commercial setting have relied on product managers, business analysts, and executives to acquire such knowledge and make such decisions. Usually the coders are not subject matter experts. Coders are always asking “what is the requirement?” Coders are paralyzed waiting for answers.
They don’t know the problem domain (the customer’s business) and the terms of art. They don’t have a mental model of the problem space. They don’t know what the actors do (journeys, use cases) and how they collaborate to accomplish their business objectives. They don’t know how these actors do their work, how they need to see their information, and what tasks they perform in certain contexts. They don’t know scale (how many users, how many transactions per hour, how much information of each type). They don’t know cost. They don’t know availability. They don’t know regulatory compliance. They don’t know their customer’s products, pricing, and business policies. There is so much they don’t know about the world, because all they know is how to code.
Coding is always blocked waiting for these responsibilities to be fulfilled by roles who don’t code. The decision makers don’t know the technical side of how to code. The coders don’t know the business side of why or what to code. The collaboration is always impaired by this mismatch in skills and knowledge.
For AI to accelerate software development, the business-focused roles must be elided with the technically-focused role. AI tools must be built to fill the skills and knowledge gap for whomever is in the driver’s seat. Human jobs need to be lost and replaced by AI. Not clear is whether coders will learn to use AI to drive the business; or whether product managers will learn to use AI to code. My bet is on the latter, even though my sympathies and bias are with the former. I don’t see AI gaining the necessary competencies to become entrepreneurial, visionary, and business savvy.
On the other hand, very few people in the business-focused roles are any good at it. We need only look at the lack of success that Tim Cook, CEO of Apple, is having in introducing innovative new products relative to what Apple has done in the past under the leadership of Steve Jobs, a true visionary and a genius in designing desirable products. All lower-ranked roles are responsible for a lesser subset of Tim Cook’s decision-making. It is a rare gem who can achieve 1% the success of a Steve Jobs, when it comes to product vision and design. Coders who have this kind of talent would have become founders. Perhaps, AI can help accelerate this more for coders who have such an inclination. By the sounds of how Tom Bilyeu applies AI for exploring business ideas, this is not as far fetched as I imagine (because of my own ignorance in applying AI in this way).
In the near-term, the quality of vibe code generated by AI is hit-or-miss. A great deal of human supervision is needed to make it work. With the progress we are seeing in AI advances and the cadence accelerating, we should not dismiss the possibility that vibe coding without a heavy human burden for supervision will become routine. Since this is a goal that many people are pursuing, this outcome is pretty much guaranteed. There is virtually no chance it will NOT happen.
Until recently, I did not think that AI would have good taste and judgement to produce good designs. Then, I was introduced to Cline. It is a coding assistant. You guide it by writing a project brief, which documents your project’s purpose, structure, standards, guidelines, constraints, technology selections, style preferences, and rules. You write these in exactly the manner that you normally would in concise English for human team mates. Amazingly, Cline understands and complies perfectly. Through this experience, I am now confident that an AI can be guided to do good design by documenting design principles, archetypes, patterns, and trade-offs. AI may not be there yet today. There is virtually no chance it will NOT happen.