Bun 1.4 includes a rewrite of Bun from Zig to Rust, adding more than 1 million lines of Rust code. Bun creator Jarred Sumner reportedly used a pre-release model called Fable 5, an agent framework that could work in parallel, and an effectively unlimited token budget to complete the initial translation in 11 days. The effort generated 6,778 commits and would have cost about $165,000 at API pricing, according to the account. Agents then continued refining the code for months before the supported release, which Paul Dix says is running on millions of developer machines. Dix argues that AI agents will increasingly write, test and improve software while people specify requirements, build verification systems and assess end results rather than review every line of code. He reports using Fable to build unshipped InfluxDB prototypes: an Iceberg integration in 14 hours and an edge-data replication system in 28 hours, followed by testing and bug fixes. Dix says neither project is production-ready or supported, but both reached end-to-end working implementations. Dix predicts that cheaper, faster frontier models and larger token budgets could make this workflow widely accessible by the end of the following year. He expects organizational inertia to preserve manual programming and code review at many companies, while more productive teams rely on AI-directed software factories and automated verification.

Emacs 31.1 has been released with incremental usability, completion, window-management and terminal improvements rather than a single flagship feature. The release permanently removes the legacy unexec dumper, deprecated since Emacs 27, leaving the portable dumper as the supported mechanism for preloading Emacs Lisp state. It also stops building and installing Emacs’s old ctags program, directing users to Universal Ctags or to `etags --ctags` for compatible behavior. A planned new garbage collector was postponed to Emacs 32. A new User Lisp Directory feature automatically processes Lisp files under `user-lisp/` in an Emacs configuration directory, including recursive byte compilation, autoload generation and load-path setup. Tree-sitter modes can now offer to install their required language grammars. Completion gains configurable eager display and live updating of the *Completions* buffer, while the rewritten flex completion style is intended to be faster and rank matches more accurately. New commands rotate, flip and transpose window layouts, and a setting controls preferred split direction. Compatible terminals now enable `xterm-mouse-mode` by default, and TTY frames gain child-frame support. Emacs 31.1 also adds built-in controls for collapsing minor-mode indicators, hiding a buffer’s mode line, extending selections with Shift-click, and preventing asynchronous native compilation on battery power. It includes Org 9.8 and supports Unicode Standard 17.0.

Thinking in Python is a Bruce Eckel book covering Python insights, idioms, and patterns. The site provides the book for online reading and links to example code and exercise solutions hosted on GitHub. The material is copyrighted © 2026 by Bruce Eckel and licensed under CC BY-NC-ND 4.0. The site states that the book is freely readable online and that reproduction requires permission.

Racket is a descendant of Scheme designed for education and programming-language research that can also be used to create domain-specific languages. PLT Scheme, created by Matthias Felleisen’s group in 1995, was renamed Racket in 2010. DrRacket includes an editor and a read-eval-print loop, while the racket command opens a terminal REPL and raco provides package-management and tooling commands. Racket programs use parenthesized expressions in operator-first form, such as (+ 1 2), and define values and functions with define. Lists are central data structures: quoting with ' prevents evaluation, while first, rest, and cons access or construct lists. Functions are first-class values, enabling operations such as map, filter, and foldl; recursive functions can express repeated computation through base cases and self-calls. Racket also ships with libraries including 2htdp/image for graphics. Because Lisp-family code can be represented as lists, quoted expressions can be manipulated as data and evaluated as code. Racket macros can transform syntax before runtime; define-syntax-rule can define constructs such as a while loop. Lisp originated at MIT in 1958 under John McCarthy, Scheme was created by Gerald Sussman and Guy Steele in 1975, and Lisp introduced or popularized concepts including garbage collection, first-class functions, REPLs, and code-as-data representation.

Rust Glancer is an alternative Rust language server built over four months to reduce memory use and preserve workspace indexes across editor restarts. It targets less than 100 MB of RAM for reasonable projects by storing analysis results on the filesystem and loading data only when a query needs it. Its VS Code extension is available now, although the server remains incomplete and has known bugs. Rust Glancer performs full workspace indexing with type inference and the Chalk trait solver, and supports common Rust syntax and LSP functions including go-to-definition, hover information, inlay hints, and completions. On a MacBook Pro M4 Max with 36 GB RAM, its reported base and full indexing times were five and eight seconds, versus six and 13 seconds for rust-analyzer. On a 2020 M1 MacBook Pro with 8 GB RAM, the reported times were six and nine seconds, versus seven and 14 seconds for rust-analyzer. Unlike rust-analyzer’s incremental in-memory model, Rust Glancer invalidates frozen analysis on save. It uses shallow analysis while typing and reuses the previous complete index, so new imports, structs, and traits are not fully indexed until a document is saved. The developer expects rust-analyzer to remain preferable for feature completeness and per-keystroke accuracy, while Rust Glancer targets lower-memory machines and workflows with many external code changes.

The Go team released Go 1.27, adding language features, toolchain updates, runtime profiling, performance work, and new standard-library packages. The release supports generic methods, allowing methods such as math/rand/v2.Rand.N to work across integer types. Struct literals can now initialize nested or embedded fields through valid field selectors, and generalized function type inference now covers all assignment contexts, including composite literals, type conversions, and channel sends. Go 1.27 adds go fix modernizers for atomic types, embedded literals, backward slices, and unsafe functions. The go doc command supports package@version queries, while go mod tidy consolidates multiple require blocks into direct and indirect blocks. Size-specialized allocation reduces costs for objects smaller than 80 bytes by up to 30%, with roughly 1% overall improvement claimed for allocation-heavy programs. The runtime/pprof goroutineleak profile is generally available for detecting permanently blocked goroutines. Standard-library additions include encoding/json/v2, post-quantum ML-DSA signatures through crypto/mldsa, UUID support, experimental SIMD packages, and an in-memory HTTP test server for testing/synctest.

Modular has released the full source code for the Mojo programming language under the Apache 2.0 license with LLVM exceptions. The Modular GitHub repository now includes the Mojo compiler, tooling and components needed to build the language. Mojo is a general-purpose language designed to apply modern compiler and programming-language research to GPUs, AI accelerators and other advanced computing hardware. Mojo 1.0 recently reached source stability, following four years of development in which the language had an open community but a closed compiler. Modular had previously open-sourced Mojo’s standard library, kernel code, tools and support components. The Apache 2.0 license permits broad use, while the LLVM license exceptions expand permissions for building and distributing binaries compiled from Mojo. Developers can clone the Modular repository and use Bazel to build the compiler and standard library locally. The `--config=build-mojo` setting compiles the toolchain from local source, and developers can run standard-library tests through Bazel. The `--config=prebuilt-mojo` setting downloads a nightly compiler binary instead, although Modular says a prebuilt compiler remains necessary for customizing MAX kernels or models. Mojo’s standard library has accepted outside contributions since 2024, but Modular is not yet accepting contributions to the compiler or tooling and aims to do so by the end of the year.

Rhombus version 1.1 is now available for download at https://rhombus-lang.org/. This release introduces new features, including the ability to define annotations without writing meta-time code and a new binding form for improved readability.

Common Lisp is chosen for code generation due to its unique features and capabilities that may not be present in mainstream languages like Python, TypeScript, or Java. The use of Common Lisp allows for more specialized and nuanced coding practices despite the larger training sets available for more popular languages.

Go is an ideal programming language for AI-assisted software engineering due to its simplicity and efficiency, allowing developers to easily read, clean, and verify AI-generated code. The language's strong support for concurrency and scalability makes it well-suited for building complex systems that AI can help develop.