The history of C and TypeScript with Anders Hejlsberg GitHub (Category Software)
The history of C# and TypeScript with Anders Hejlsberg | GitHub (Rubric #Software)
Interesting. interview Anders Heilsberg, creator of C#, Delphi, Turbo Pascal and lead architect of TypeScript, which he gave to GitHub. Andreas examines how C# and TypeScript were created and what trade-offs were behind the solutions and what principles help languages and commands live long.
You can learn a lot from a half-hour interview. 1Fast feedback is more important than almost everything A short “wrote → immediately understood / checked” cycle determines speed and quality. Therefore, the value of TypeScript is not only in types, but also in tools: tips, verification, refactoring, fast compiler. 2Scale requires sacrificing a personal ideal When there are many users and scripts, pragmatism wins: language is successful if it fits into the real work of teams, not just the textbook. 3Evolution is stronger than revolution TypeScript has grown as an add-on to JavaScript: it improves the support of large projects without forcing them to “burn bridges” and change the ecosystem. 4Transparency accelerates open source Public PR/issue and deliberations shift priorities from “internal” to actual needs, and decisions become understandable and verifiable. 5Sometimes you need a breakthrough in the base without breaking an external contract Rewriting a critical component for the sake of performance makes sense unless the user pays the price of compatibility. 6The era of AI shifts the role of an engineer More code is being generated and the value of the tools is exactly the same: types, checks, tests, and refactoring as guards against plausible errors. 7Project Memory is an asset Background of discussions and decisions (Why did you do that and not that?) Reduces error repetition and facilitates onboarding.
If you turn these lessons into conclusions, they can be
For engineers. Invest in a fast cycle: local checks, quick tests, linters/types, convenient IDE tools. Write for collective ownership: readability, predictability, simple rules over personal elegance. Learn from the context of decisions: Issue/PR discussions often provide more than abstract best practices. When working with an AI code, strengthen insurance: typing + statistical analysis + tests, otherwise you just generate debt faster.
For technical managers
- Set the feedback rate in the KPI of the engineering system: CI, tests, statistical analysis, quick builds. Slow feedback gives rise to “crutches” processes. Balance your interests: Standards and compatibility are more important than the taste of individual strong engineers. Implement change through migration and compatibility: incremental improvement is usually cheaper and more reliable than total replacement. Build Institutional Memory: ADR/solutions, discussion links, understandable reasons for trade-offs – this reduces growth risk and turnover.
In general, long-lived technologies and teams benefit when they provide fast feedback, make pragmatic trade-offs, evolve backwards compatible, and lead a transparent decision history.
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