LLMs are in the process of completely reshaping the software industry. Understanding how we fit in will be essential. According to the view through my kaleidoscope, it's Enterprise or bust for the next 10 years. Enterprise problems (and their budgets) will reliably hover above a fog of small projects so thick that each click of the internet will surface another micro-project that is here today and gone tomorrow. It's going to be insane. VC funded startups will unsuccessfully compete for paid clicks, influencers, and annoyingly formulaic content with a special fervor of desperate and tragically ineffective Capitalist bloodlust.
Let's start by identifying one member of our community that will be mostly extinct in 12 months: the solo app developer. The solo app developer will certainly still exist, but generally without the perks of high revenue. Unless someone is a unique generational talent and/or Genius Coder, the ease of vibe-coded competition, combined with the complete destruction of marketing efficiency and trusted social channels by AI Slop will make growing a solo project prohibitively annoying. Of course a few builders will hit gold with the perfect product offering at the perfect time, but this will be exceedingly rare. Everyone will be building modules and tools and micro apps, dramatically flattening the small SaaS market…
Let's try to cover the AI-enabled software industry in brief with the following personas:
- Genius Coder
- Good Coder
- Data Scientist
- Technology Synthesizer
- Sales
Genius Coder
Our Genius Coders are our 140+ IQ software architects and engineers. They will be building AI innovation tooling and solving mega-scale platform problems. These people are already our backbone for software innovation. Their daily operation is innovation, period. They're migrating their open source projects to Rust. They're building new AI harnesses. They're reshaping our entire landscape of dev and process tooling in their free time. They're weighting models. The innovations from our Genius Coders will trickle down to every level of development.
If they work on SaaS apps, they will be founding members of highly financed startups at the cutting edge of AI and computing. There is no shortage of problems for them to solve, and LLMs have unleashed another dimension to their creativity.
Take a look at these projects and startups for reference:
Good Coder
Our Good Coders are very different from our Genius Coders. Our Good Coders are solid full stack engineers with real production experience. They will be supportive sidekicks to our Genius Coders, or leading orgs together with our Technology Synthesizers.
Good Coders will be the multi-tools of the AI ecosystem. They are quick experts with the latest models and harnesses. Their background of solving real problems prior to the AI revolution will position them perfectly to contribute to almost any new technical project.
They are leadership caliber, depending on the innovation scope of the project.
With the leading LLMs and a few Diet Cokes, the Good Coder can now build pretty much anything they set their mind to. They will be leading members for Small SaaS and Mega SaaS projects.
They will excel in the Forward Deployed Engineer or Applied AI Engineer positions for AI services consulting.
Data Scientist
Data Scientists are our traditional math, research, and data modeling folks. They run our regressions, score algorithms, forecast, segment, and build our recommendation engines.
Data Scientists are often confused with AI or ML Engineers. Some of our Data Scientists will merge into AI or ML Engineers easily.
Our Data Scientists will just keep being smart and stable, like always. A good Data Scientist is like a Genius Coder with less horsepower and a more stable personality. Our Data Scientists will contribute to Tooling, Mega SaaS, and service consulting. Because of their solid backgrounds with Python, they are highly desirable and fluid in their future placements.
Technology Synthesizer
Technology Synthesizers are our engineering, product, and strategy folks who easily visualize the end-to-end software stack and how it interacts with customers, business stakeholders, internal personnel and technology systems. Technology Synthesizers are deeply technical people and should have an "under the hood" understanding of the latest AI developments: tools, prompting, capabilities, processes, automations, and harnesses.
Technology Synthesizers can talk to and understand any part of a business. They can easily compare notes with C-level executives. Synthesizers have a core ability to technically empathize with their audience and quickly merge business nodes, interests, and directional strategy within a single brief conversation.
With the AI revolution just starting to simmer, Technology Synthesizers can provide outsized value when visualizing existing technology organizations and how they will merge with a new set of AI tooling and process.
Our Technology Synthesizers will be best positioned to deliver futuristic strategy at the intersection of a curious customer and technology innovation problems.
Sales
Our Sales people are experiencing the full weight of the LLM revolution. Every enterprise on earth needs to get involved with AI, and only a small percentage of them are ready. It's not as simple as giving each of our developers a Claude account.
Our big orgs need to solve huge problems, with huge teams, huge liability risk, huge data context problems, and legacy codebases.
For technical sales people, there will be huge opportunities to feast on Enterprise budgets, they will be delicious.
That's all for now.