AI
pro AI in coding
- quickly solves a problem
- works in unfamiliar coding areas, concepts, languages
- suggests unknown functions and approaches
contra AI in coding
- doesn’t always follow best practices
- is hard to maintain and has security issues (see below)
- needs experienced senior developers to catch issues
- lowers debugging skills
- reduces learning to think in a structured manner (see below)
solution
- learn basic programming yourself
- develop good coding habits from the beginning
- make mistakes, debug, struggle, research, think, build problem solving skills
- implement AI-assisted code critically
- enjoy good employment perspectives
AI in learning
don’t bring a forklift to a fitness studio to lift weights
AI = amplified intelligence -> develop skills to be augmented
- Outsourcing work to AI hurts long-term growth of learning skills
- AI stunts intellectual development as engineer + reasoning about complex concepts
- Chatbots threaten critical thinking and cognitive development skills
- Students using AI lose critical skills and become dependent on unreliable tools
- LLM-assisted writing lowers cognitive activity, engagement, memory recall, ownership
detailed problems
(sorted by publication time, hoping that some of the older problems get solved over time)
note also the ever growing AI incident databases
- 2026-09 Agentic coding leads to slop, alienation, deskilling and team fallout
- 2026-09 openAI reveals yet more safety issues
- 2026-09 OpenAI disrespecting IP may cause damage to open science
- 2026-08 AI R&D progress may need pacing to be safe for humanity
- 2026-07 when OpenAI guardrails are circumvented, agents use zero-day-exploits
- 2026-07: developers have decreasing trust in AI coding tools output
- 2026-07 jailbreaking still is a problem and may remain one forever
- 2026-07 AI coding has not yet changed the world all that much
- 2026-06: AI has faulty medical reasoning and hallucinations, uses inappropriate shortcuts
- 2026-06: AI support system used to hijack over 20,000 accounts
- 2026-06: OpenAI and Anthropic do not trust their own AI and hire humans instead
- 2026-05: real business impact of AI is low but it de-skills engineers and erodes career growth
- 2026-05: autonomous agents are vulnerable to tool-chaining attacks
- 2026-05: AI code looks correct but isn’t, engineers don’t trust it but don’t check it either
- 2026-04: AI-generated code gets rewritten/reverted at higher rates than human code
- 2026-04: computer science skills remain a dominant predictor of vibe coding performance
- 2026-04: AI agents still destroy production databases and cannot be trusted
- 2026-04: incidents per pull request and bugs per developer are rising at increasing pace
- 2026-04: sycophantic AI reduces healthy skepticism, AI agents need clear specs
- 2026-04: as a society, we may forget how to code and have a hard time re-learning
- 2026-04: widespread AI usage creates additional maintenance load on senior developers
- 2026-04: Claude code itself has “corner-cutting and wilful blindness at scale”
- 2026-04: ChatGPT cannot reliably keep track of time
- 2026-03: AI code caused Amazon outage
- 2026-03: AI adoption decreases delivery speed and causes a drop in system stability
- 2026-03: Medical X-ray benchmark scores are worthless (top rank without using an image)
- 2026-03: measured productivity gains are lower than perceived
- 2026-03: Gen-AI-assisted changes cause outages, decrease maintainability
- 2026-02: AI adoption stalls, performance gains plateau, AI fails to deliver durable impact
- 2026-01: engineers who lean on AI to write code understand it less well
- 2025-12: AI-generated code contains more bugs and errors than human output
- 2025-11: With increasing complexity, it gets harder to check if AI output is correct
- 2025-11: AI output lowers skepticism during reviews, stunts junior devs knowledge gain
- 2025-11: LLMs are bad at conceptual programming
- 2025-10: AI-written code causes security breaches, hard to track down vulnerabilites
- 2025-09: 95% of companies see no return on AI investment (reasons why)
- 2025-09: AI assistants actually slow down software development (reproducible)
- 2025-08: prompt injection attacks remain a major concern
- 2025-08: Vibe coding without engineering discipline creates unmaintainable code
- 2025-08: Coding agents create cybersecurity vulnerabilities in numerous ways
- 2025-07: AI usage degrades our ability to catch bugs, creates a reliability problem
- 2025-07: AI coding tools chase phantom bugs and destroy real production databases
- 2025-05: With / despite AI tools, the number of software developers is still increasing
- 2024-12: AI coding collapses under real-world pressure, requires expertise for final 30%
- 2024-05: Coders with AI assistance write more security leaks (with less awareness of them)