2025 will go down as the year code became cheap and programming changed forever. With agentic development tools—Claude Code, Codex CLI, Gemini CLI—engineers can produce far more code than ever before: prototypes, analysis scripts, migrations, refactors, bug fixes, tests, docs, and glue. But that doesn’t automatically translate into shipped value. In 2026 we’ll see the split: organizations that can adapt their processes and tooling to validate and deploy this new flood of changes will compound their advantage, while everyone else bottlenecks in review, testing, and release.
The reason is simple: once coding speed jumps, everything around it becomes the constraint. Your throughput gets capped by whatever is slowest—clarifying requirements, reviewing changes, validating correctness and performance, getting to production safely, and operating what you shipped. In 2026, the great engineering divergence will be determined by who raises that ceiling end-to-end.
Based on the pace of the last year, it’s reasonable to expect a few more major capability jumps from each lab in 2026: better tool use, more reliable instruction following, and longer usable context. I used most of the different models and agentic tools as they shipped, and I felt the shift firsthand—less “I’m writing code” and more “I’m directing work.” At this point, I expect most new code in many orgs to be AI-generated, with humans increasingly setting intent and validating outcomes.
The most effective software teams at the end of 2026 will be wildly more productive than even the most effective software teams from the beginning of 2025. In less than 24 calendar months we'll have gone from one paradigm for software development to a new one that yields vastly more software than before. A single developer with multiple agents running in parallel paired with a software delivery process optimized for agentic development will run circles around everyone else.
Although the rise in team productivity inequality will be driven in some small part by variance in individual adoption and effectiveness with AI, it will mostly be driven by the organization's ability to take advantage of every developer suddenly getting the ability to produce 10x to 1,000x more code than at any point before. Individuals may slowly adopt the tools, but by the middle of next year the cacophony of voices exclaiming how they're able to do so much more than before will be impossible to ignore.
Amdahl's Law rules everything around me
Amdahl's Law states that “the overall performance improvement gained by optimizing a single part of a system is limited by the fraction of time that the improved part is actually used.” For those of us working on performance improvements in software systems (like InfluxDB), we're intimately familiar with this concept and use it to prioritize what optimizations to work on.