2026 Tech Trends: Boring Tech, AI Advocacy, and Job Market Insights
Published on 05.01.2026
2026 Tech Stack: Boring as Hell (And That is the Point)
TLDR: A senior engineer advocates for choosing simple, proven technology over complex, trendy solutions, moving from microservices and Kubernetes to a monolithic architecture running on a single VPS with SQLite or Postgres.
Summary: The article challenges the common trend of adopting complex, distributed systems for most applications. The author argues that most applications don't need the complexity of microservices and Kubernetes, and instead advocates for simpler, more maintainable solutions. The approach involves using monolithic architecture running on a single VPS with SQLite or Postgres, which significantly reduces operational overhead while maintaining reliability. This "boring technology" approach prioritizes developer productivity and system stability over the allure of cutting-edge tech. For teams and architects, this suggests reevaluating whether complex distributed systems are truly necessary for their use cases, potentially saving significant time and resources on operational complexity.
Key takeaways:
- Most applications don't require the complexity of distributed systems
- Simple monolithic architectures can be more maintainable and reliable
- Operational overhead is significantly reduced with simpler tech stacks
- Focus on proven technology rather than trendy solutions
Tradeoffs: Gain operational simplicity and reduced complexity but sacrifice potential scalability benefits of distributed systems.
Link: My 2026 Tech Stack is Boring as Hell (And That is the Point) | daily.dev
Fear is not advocacy
TLDR: AI advocates often use fear-based messaging, warning developers they'll lose their jobs if they don't immediately master AI technology, which is counterproductive and false.
Summary: The article critiques the fear-based approach often used in AI advocacy, where developers are warned they'll lose their jobs if they don't immediately master AI technology. The author argues this approach is counterproductive and false, comparing it to how developers don't need to be Linux experts to use containers - they don't need to become AI experts overnight. The piece emphasizes that as the industry naturally adopts AI tools, developers should approach them with a balanced perspective rather than fear. For teams and architects, this suggests implementing AI tools gradually and thoughtfully, focusing on how they enhance productivity rather than replacing human expertise.
Key takeaways:
- Fear-based messaging about AI adoption is counterproductive
- Developers don't need to become AI experts overnight
- AI tools should enhance rather than replace human expertise
- Balanced perspective is more effective than fear-driven adoption
Tradeoffs: Gain gradual, thoughtful AI adoption but sacrifice the potential for rapid transformation that fear-based messaging might drive.
Link: Fear is not advocacy | daily.dev
Software Engineering Job Market Outlook for 2026
TLDR: The software engineering job market in 2026 shows signs of stabilization after the 2021-2022 hiring boom and subsequent correction, with entry-level positions remaining scarce.
Summary: The article discusses the current state of the software engineering job market in 2026, noting signs of stabilization after the dramatic hiring boom and correction of 2021-2022. While entry-level positions remain scarce with 40% fewer junior roles than pre-2022, overall developer jobs are still projected to grow 15% according to BLS data. The crisis stems from pandemic-era hiring practices, but the market is showing signs of recovery. For teams and architects, this suggests being strategic about hiring practices and potentially investing more in training and development to bridge skill gaps in the tighter talent market.
Key takeaways:
- Entry-level positions remain scarce with 40% fewer junior roles than pre-2022
- Overall developer jobs still projected to grow 15% according to BLS data
- Market is stabilizing after pandemic-era hiring boom and correction
- Strategic hiring and training investments may be necessary
Tradeoffs: Gain more experienced candidates in a tighter market but sacrifice access to entry-level talent and potential for growth from junior developers.
Link: Software Engineering Job Market Outlook for 2026 | daily.dev
My LLM coding workflow going into 2026
TLDR: A comprehensive workflow for using LLM coding assistants effectively in 2026, emphasizing detailed planning, small iterative chunks, and human oversight.
Summary: The article outlines a comprehensive workflow for using LLM coding assistants effectively in 2026. The approach starts with detailed planning and specs before coding, breaking work into small iterative chunks, providing extensive context to the AI, choosing appropriate models for each task, and maintaining human oversight through rigorous testing and code review. The workflow emphasizes that LLMs should augment rather than replace human judgment in the development process. For teams and architects, this suggests establishing clear processes for LLM integration that maintain quality standards while leveraging AI capabilities for productivity gains.
Key takeaways:
- Start with detailed planning and specs before coding with LLMs
- Break work into small iterative chunks for better AI assistance
- Provide extensive context to the AI for better results
- Maintain human oversight through rigorous testing and code review
Tradeoffs: Gain productivity and efficiency from LLM assistance but sacrifice some autonomy and require additional oversight processes.