Taking ownership of your AI coding history
AI coding assistant history is becoming valuable development memory. Developers should be able to export it, inspect it, archive it, and reuse it responsibly.
AI coding assistant history is becoming valuable development memory. Developers should be able to export it, inspect it, archive it, and reuse it responsibly.
Chat is useful, but the next layer of AI interfaces may be dynamic workspaces that adapt to the task.
A small experiment comparing English and Norwegian Bokmål token counts for the same official government text.
AI can multiply a capable builder, but serious products still need judgment, architecture, QA, customer feedback, and maintenance.
Chat is a useful command layer for AI agents, but it is probably not the final interface. Real work needs state, structure, and rollback.
Some of the best agent work may be the boring cleanup: stale bugs, duplicate issues, old PRs, and half-finished ideas.
The next practical gain in AI-assisted development is moving from one AI helper per developer to shared, issue-driven delivery workflows.
AI can help with classification, mapping, and exception handling in migrations, but code and process must keep control over safety and quality.
Agentic development makes impressive demos cheap, but real products still need architecture, ownership, tests, review, and operational discipline.
A small bug fix felt like an early glimpse of software that can help correct itself, with a human still in the loop.