Doug Slater

Generative AI keeps making software quality mistakes that experts for decades have known to avoid. Behavior verification is one of them.

Regretting that code you vibed? Learn when skipping human review is and isn't a smart move.

Learn how to respond when your CFO asks, "why are our devs still writing code?"

When you type code by hand, you get the best of LLMs without losing your coding skills.

Like electric vehicle range anxiety, context anxiety is that dread you feel when your LLM is almost out of context memory. Modules are your best tool for conserving LLM context.

The claim "software never fails" is cavalier and dangerous. It creates a mindset that itself leads to software failures.

While it's rare to see a sixty-year old car still running, COBOL is 65 years old and processes 95% of today's ATM transactions. The world is full of critical infrastructure running on ancient software, so it's important to understand how software can fail.

In a competitive landscape, LLMs, like supershoes, do not result in your benefit.

At work, saying no to someone higher on the org chart is safe if you first earn their trust and if it's for the good of the business.

Society restricts who can design bridges or prescribe medicine, but it lets anyone market their software. AI accelerates the problem. It's in everyone's interest that states require licensure of software engineers.

AI now lets anyone write software, but it has limits. People will call upon software practitioners to fix their AI-generated code. Learn how to decide when to take that gig.

LLMs are more like E-bikes. More assist makes you go faster, but provides less exercise.

LLM-generated code is like an oil spill. Real engineers will be there to mop up the mess - and collect the checks.

There are certain skills software engineers can practice to further differentiate themselves from LLMs.

In software engineering, over-reliance on LLMs accelerates incompetence. LLMs can't replace human critical thinking.

Tech risk is a business concern. Instead of vaguely bemoaning "tech debt" and hoping to "do things right", explain its potential costs with words the business understands.

Tech Debt becomes due swiftly and chaotically. Tech Risk is a better metaphor.

Programming isn't about programming, and it isn't about computers.

Anchor programming education in what the learner already knows.

The roundtrip from a design to code back to design is lossy.