# JIT JIT is a compilation process that translates code into machine or native code at runtime. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Postgres 19: How Our Advice Has Changed Since We Wrote It DevFeed: [Postgres 19: How Our Advice Has Changed Since We Wrote It]() Original publisher: [Read original article]() Author: Christopher Winslett Published: 2026-08-18T19:00:00Z Content type: article Language: en Sources: [CrunchyData Blog]() Topics: [data](), [JIT](), [Latency](), [Temporal data](), [Linux]() Tags: [advice](), [async](), [benchmarks](), [index](), [jit](), [latency](), [linux](), [maintenance](), [parallel](), [partitioning](), [postgres](), [postgres-19](), [production-postgres](), [release](), [storage](), [upgrade]() ### AI overview This article revisits earlier Crunchy Data guidance on loading, storage, indexes, and partitioning for the upcoming Postgres 19 release. It explains which changes in Postgres 18 and 19 affect that advice, including asynchronous I/O, parallel maintenance, BRIN and skip-scan behavior, partition operations, and JIT being disabled by default. The details are based on current betas and may change before general availability. ### Source excerpt Revisiting Crunchy posts on COPY, TOAST, BRIN, covering indexes, and partitioning: what we said then, which Postgres versions changed the story, and what we recommend on Postgres 19. ## Python 3.15.0 candidate 1 is here! DevFeed: [Python 3.15.0 candidate 1 is here!]() Original publisher: [Read original article]() Author: Hugo van Kemenade Published: 2026-08-04T00:00:00Z Content type: release Language: en Sources: [Python Insider]() Topics: [Python](), [releases](), [Maintainers](), [Compiler](), [JIT](), [Linux](), [macOS](), [Windows]() Tags: [documentation](), [jit](), [linux](), [macos](), [maintainers](), [performance](), [python](), [release](), [releases](), [windows]() ### AI overview Python 3.15.0rc1 is the first release candidate in the Python 3.15 series. The article asks third-party maintainers to test the release, publish compatible wheels, report issues, and complete documentation before the final release. ### Source excerpt Get those wheels rolling! ## 【eBPF 内核实现深度拆解】从验证器到 JIT，从 BTF 到调度器 DevFeed: [【eBPF 内核实现深度拆解】从验证器到 JIT，从 BTF 到调度器]() Original publisher: [Read original article]() Author: Liao Tonglang Published: 2026-06-12T00:00:00Z Content type: article Language: zh Sources: [土法炼钢 - 系统与基础设施]() Topics: [eBPF](), [Linux](), [JIT](), [Benchmark](), [clang](), [hash](), [benchmarking](), [RISC-V](), [ast-matchers]() Tags: [arm](), [array](), [benchmark](), [bpf-jit](), [bpf-maps](), [bpf-verifier](), [btf](), [clang](), [co-re](), [cpu](), [ebpf](), [fentry](), [hash](), [jit](), [kernel](), [libbpf](), [linux](), [linux-kernel](), [precision](), [risc-v](), [sched-ext](), [trampoline](), [x86](), [xdp]() ### AI overview This Chinese-language series systematically explains eBPF's Linux kernel implementation, covering the BPF instruction set and registers, verifier algorithms, JIT compilation, map data structures and concurrency, helper type checking, BTF and CO-RE relocation, libbpf loading, trampolines, and sched_ext interfaces. It is aimed at engineers who want to understand eBPF kernel source code and build production BPF programs. ### Source excerpt eBPF 内核虚拟机内部实现系统讲解：BPF 指令集与寄存器机器、验证器的抽象解释与状态裁剪、JIT 编译器后端、Map 各类型的并发与内存模型、helper 函数注册与类型检查、BTF 格式规范与 CO-RE 重定位引擎、libbpf 加载器工程、fentry/fexit 蹦床机制、sched_ext 调度器内核接口。面向想读懂 eBPF 内核源码、写生产级 BPF 程序的系统工程师。 ## Python 3.15.0 beta 2 is here! DevFeed: [Python 3.15.0 beta 2 is here!]() Original publisher: [Read original article]() Author: Hugo van Kemenade Published: 2026-06-02T00:00:00Z Content type: release Language: en Sources: [Python Insider]() Topics: [Python](), [releases](), [JIT](), [observability](), [Compiler]() Tags: [jit](), [maintainers](), [observability](), [performance](), [python](), [release](), [releases](), [testing]() ### AI overview Python 3.15.0b2 is the second of four planned beta releases. The preview includes new language and type-system features, profiling and observability improvements, a significantly upgraded JIT compiler, improved error messages, and updated Windows binaries. The article encourages maintainers to test the beta and report issues, while recommending that production releases wait until the first release candidate. ### Source excerpt The antepenultimate 3.15 beta is out! ## Python 3.14.5 is out! DevFeed: [Python 3.14.5 is out!]() Original publisher: [Read original article]() Author: Hugo van Kemenade Published: 2026-05-10T00:00:00Z Content type: release Language: en Sources: [Python Insider]() Topics: [Python 3.14](), [Python](), [Compression](), [JIT](), [Processes](), [Android](), [macOS](), [Windows]() Tags: [android](), [compression](), [features](), [jit](), [macos](), [memory](), [processes](), [python](), [python-3-14](), [release](), [releases](), [windows]() ### AI overview Python 3.14.5 is the fifth maintenance release in the Python 3.14 series, with approximately 154 bug fixes, build improvements, and documentation changes. It reverts the incremental garbage collector to the generational collector used in Python 3.13 because of reported production memory pressure. The release also updates Tcl/Tk on macOS and documents major Python 3.14 features, including free-threaded support, deferred annotation evaluation, template string literals, multiple interpreters, Zstandard support, debugging interfaces, an experimental JIT, and Android binaries. ### Source excerpt A special release with a new (old) garbage collector. ## Python 3.15's JIT is now back on track DevFeed: [Python 3.15's JIT is now back on track]() Original publisher: [Read original article]() Author: Ken Jin Published: 2026-03-23T00:00:00Z Content type: article Language: en Sources: [Python Insider]() Topics: [JIT](), [Python](), [Linux](), [macOS]() Tags: [article](), [blog](), [community](), [contributors](), [jit](), [linux](), [macos](), [performance](), [python]() ### AI overview Python's CPython JIT has met its performance goals ahead of schedule for macOS AArch64 and x86_64 Linux. The article discusses preliminary Python 3.15 alpha results, the JIT's recovery from earlier slowdowns, and the community-led work and contributors behind its progress. ### Source excerpt A look at Python's JIT in 3.15a7. ## Python 3.15.0 alpha 7 DevFeed: [Python 3.15.0 alpha 7]() Original publisher: [Read original article]() Author: Hugo van Kemenade Published: 2026-03-10T00:00:00Z Content type: release Language: en Sources: [Python Insider]() Topics: [Python](), [JIT](), [releases](), [Compiler](), [Linux](), [macOS]() Tags: [jit](), [linux](), [macos](), [python](), [release](), [releases]() ### AI overview Python 3.15.0a7 is the seventh of eight planned alpha releases and provides an early developer preview of the in-development Python 3.15 series. It introduces or advances features including explicit lazy imports, a statistical sampling profiler, unpacking in comprehensions, UTF-8 as the default encoding, improved typing support, a new C API for bytes objects, upgraded JIT compilation, and improved error messages. ### Source excerpt The penultimate 3.15 alpha is out! ## two mechanisms for dynamic type checks DevFeed: [two mechanisms for dynamic type checks]() Original publisher: [Read original article]() Author: Andy Wingo Published: 2026-02-18T16:21:10Z Content type: tutorial Language: en Sources: [wingolog]() Topics: [virtual machines](), [Inheritance](), [WebAssembly](), [JIT](), [Polymorphism]() Tags: [cardelli](), [cohen](), [dfs](), [display-hack](), [dybvig](), [scheme](), [vitek](), [wasm](), [webassembly]() ### AI overview This technical note explains two mechanisms for dynamic instance type checks in virtual machines with single inheritance. It describes DFS numbering when the type set is fixed and the display hack, based on per-type supertype arrays, when types can be added at run time. ### Source excerpt Today, a very quick note on dynamic instance type checks in virtual machines with single inheritance. The problem is that given an object o whose type is t, you want to check if o actually is of some more specific type u. To my knowledge, there are two sensible ways to implement these type checks. if the set of types is fixed: dfs numbering Consider a set of types T := {t, u, ...} and a set of edges S := {, ...} indicating that t is the direct supertype of u, or ε if u is a top type. S should not contain cycles and is thus a direct acyclic graph rooted at ε. First, compute a pre-order and post-order numbering for each t in the graph by doing a depth-first search over S from ε. Something like this: def visit(t, counter): t.pre_order = counter counter = counter + 1 for u in S[t]: counter = visit(u, counter) t.post_order = counter return counter Then at run-time, when making an object of type t, you arrange to store the type's pre-order number (its tag) in the object itself. To test if the object is of type u, you extract the tag from the object and check if tag-u.pre_order mod 2n < u.post_order-u.pre_order. Two notes, probably obvious but anyway: one, you know the numbering for u at compile-time and so can embed those variables as immediates. Also, if the type has no subtypes, it can be a simple equality check. Note that this approach applies only if the set of types T is fixed. This is the case when statically compiling a WebAssembly module in a system that doesn't allow modules to be instantiated at run-time, like Wastrel. Interestingly, it can also be the case in JIT compilers, when modeling types inside the optimizer. if the set of types is unbounded: the display hack If types may be added to a system at run-time, maintaining a sorted set of type tags may be too much to ask. In that case, the standard solution is something I learned of as the display hack, but whose name is apparently ungooglable. It is described in a 4-page technical note by Norman H. Coh ## Python 3.15.0 alpha 6 DevFeed: [Python 3.15.0 alpha 6]() Original publisher: [Read original article]() Author: Hugo van Kemenade Published: 2026-02-11T00:00:00Z Content type: release Language: en Sources: [Python Insider]() Topics: [Python](), [JIT](), [Compiler](), [GitHub]() Tags: [developer](), [features](), [github](), [jit](), [performance](), [python](), [release](), [release-schedule](), [releases]() ### AI overview Python 3.15.0a6 is an early developer preview and the sixth of eight planned alpha releases. It introduces or advances features including a statistical sampling profiler, unpacking in comprehensions, UTF-8 as the default encoding, a new C API for Python bytes objects, typed extra items, an upgraded JIT compiler, and improved error messages. ### Source excerpt This is an early developer preview of Python 3.15 www.python.org/downloads/release/python-3150a6/ Major new features of the 3.15 series, compared to 3.14 Pyt... ## Python 3.14.3 and 3.13.12 are now available! DevFeed: [Python 3.14.3 and 3.13.12 are now available!]() Original publisher: [Read original article]() Author: Thomas Wouters Published: 2026-02-03T00:00:00Z Content type: release Language: en Sources: [Python Insider]() Topics: [Python 3.14](), [Python](), [releases](), [Compression](), [JIT](), [Syntax Highlighting](), [Process]() Tags: [compression](), [jit](), [performance](), [process](), [python](), [python-3-14](), [release](), [releases]() ### AI overview Python 3.14.3 is the third maintenance release in the Python 3.14 series, with around 299 bug fixes, build improvements, and documentation changes since Python 3.14.2. The article also highlights major Python 3.14 features, including free-threaded support, deferred annotation evaluation, template string literals, multiple interpreters, Zstandard support, improved debugging, an experimental JIT in official macOS and Windows binaries, and official Android binary releases. ### Source excerpt Python 3.14.3 is now available! This is third maintenance release of Python 3.14 Python 3.14.3 is the third maintenance release of 3.14, containing around ... ## Python 3.15.0 alpha 5 (yes, another alpha!) DevFeed: [Python 3.15.0 alpha 5 (yes, another alpha!)]() Original publisher: [Read original article]() Author: Hugo van Kemenade Published: 2026-01-14T00:00:00Z Content type: release Language: en Sources: [Python Insider]() Topics: [Python](), [releases](), [JIT](), [Compiler](), [Linux](), [macOS]() Tags: [community](), [documentation](), [feature](), [jit](), [linux](), [macos](), [performance](), [python](), [release](), [releases]() ### AI overview Python 3.15.0 alpha 5 is an extra early developer preview release, issued after an earlier alpha was built against the wrong date. The article outlines planned and implemented changes, including a new statistical sampling profiler, UTF-8 as the default encoding, a new C API for creating Python bytes objects, JIT compiler upgrades, improved error messages, and the upcoming alpha release schedule. ### Source excerpt Note: 3.15.0a4 was accidentally built against from 2025-12-23 instead of 2026-01-13, so this 3.15.0a5 is an extra release correctly built against 2026-01-14... ## How Just-in-Time Access Reduces Engineering Access Bottlenecks and Shared-Credential Risk DevFeed: [How Just-in-Time Access Reduces Engineering Access Bottlenecks and Shared-Credential Risk]() Original publisher: [Read original article]() Author: jack@goteleport.com (Jack Pitts) Published: 2026-01-14T00:00:00Z Content type: article Language: en Sources: [Teleport]() Topics: [JIT](), [Security](), [Authorization]() Tags: [audit](), [credentials](), [how-to](), [legacy](), [permissions](), [productivity](), [security](), [vpn]() ### AI overview This article explains how just-in-time (JIT) access can reduce engineering access delays and the risks associated with shared credentials. It describes the effects of ticket-based workflows, VPN or jump-host requirements, broad permissions, unclear attribution, and manual platform-team work. ### Source excerpt Learn how to eliminate access bottlenecks (and shared credential risk) from day-to-day engineering work with just-in-time (JIT) access. ## Python 3.15.0 alpha 4 DevFeed: [Python 3.15.0 alpha 4]() Original publisher: [Read original article]() Author: Hugo van Kemenade Published: 2026-01-13T00:00:00Z Content type: release Language: en Sources: [Python Insider]() Topics: [Python](), [JIT](), [Compiler](), [releases]() Tags: [jit](), [python](), [release](), [release-schedule](), [releases]() ### AI overview Python 3.15.0 alpha 4 is an early developer preview and the fourth of seven planned alpha releases. It introduces or advances features including a statistical sampling profiler, UTF-8 as the default encoding, a new C API for creating Python bytes objects, an upgraded JIT compiler, and improved error messages. The release is not recommended for production use. ### Source excerpt Edit: This 3.15.0a4 was accidentally built against \ from 2025-12-23 instead of 2026-01-13, so 3.15.0a5 is an extra release correctly built against 2026-01-1... ## Using Ahead-of-Time Cache Optimizations in Recent JDK Releases DevFeed: [Using Ahead-of-Time Cache Optimizations in Recent JDK Releases]() Original publisher: [Read original article]() Author: Ana-Maria Mihalceanu Published: 2025-12-17T03:03:45Z Content type: tutorial Language: en Sources: [Java Advent Calendar]() Topics: [Java](), [Caching](), [JIT](), [Memory safety verification]() Tags: [2025](), [cache](), [guides](), [java](), [java-advent](), [jdk](), [jdk25](), [jit](), [jvm](), [openjdk](), [performance](), [project-leyden](), [startup]() ### AI overview This tutorial explains how to use Ahead-of-Time cache features in recent JDK releases to improve Java application startup time and warm-up performance. It covers the train, assemble, and run workflow introduced in JDK 24 and method profiling improvements in JDK 25. ### Source excerpt As the year comes to a close, turn your focus to boosting your Java application performance by applying Ahead-of-Time (AOT) cache features in recent JDK releases. This article guides you through using AOT cache optimizations in your application, thereby minimizing startup time and achieving faster peak performance. What is the Ahead-of-time cache in the jdk [...] The post Run Into the New Year with Java's Ahead-of-Time Cache Features appeared first on JVM Advent. ## Java Hello World, LLVM Edition DevFeed: [Java Hello World, LLVM Edition]() Original publisher: [Read original article]() Author: James Hamilton Published: 2025-12-07T02:02:37Z Content type: tutorial Language: en Sources: [Java Advent Calendar]() Topics: [Java](), [LLVM](), [API](), [JIT]() Tags: [2025](), [api](), [assembly](), [bytecode](), [compilers](), [java](), [java-advent](), [jdk](), [jit](), [jvm](), [llvm]() ### AI overview This tutorial shows how to use Java's Foreign Function & Memory API to call the LLVM C API, generate LLVM IR for a Hello World program, and JIT-compile it to native code. It also introduces LLVM, its IR representations, and local installation on Ubuntu or Debian. ### Source excerpt After exploring Java bytecode in previous years (2022, 2023, 2024), this year we'll take an unexpected detour for a Java advent: instead of generating Java bytecode, we'll use Java to build and execute LLVM IR, the intermediate language behind compilers like clang. Using Java's Foreign Function & Memory (FFM) API, we'll call the LLVM C [...] The post Java Hello World, LLVM Edition appeared first on JVM Advent. ## Compiling Ruby To Machine Language DevFeed: [Compiling Ruby To Machine Language]() Original publisher: [Read original article]() Author: Pat Shaughnessy Published: 2025-11-17T00:00:00Z Content type: article Language: en Sources: [Pat Shaughnessy]() Topics: [Ruby](), [JIT](), [Compiler](), [Assembly](), [Code]() Tags: [compiler](), [jit](), [machine](), [performance](), [ruby](), [rust](), [updating-ruby-under-a-microscope]() ### AI overview This excerpt explains how Ruby's YJIT compiler identifies frequently called functions and blocks, counts executions, and compiles hot YARV instruction sequences into machine language. It also describes thresholds used for small Ruby programs and Ruby on Rails web applications, along with YJIT blocks. ### Source excerpt I've started working on a new edition of Ruby Under a Microscope that covers Ruby 3.x. I'm working on this in my spare time, so it will take a while. Leave a comment or drop me a line and I'll email you when it's finished. Here's an excerpt ## Node.js 25.0.0 (Current) DevFeed: [Node.js 25.0.0 (Current)]() Original publisher: [Read original article]() Published: 2025-10-15T17:12:18Z Content type: release Language: en Sources: [Node.js Blog]() Topics: [Node.js](), [V8](), [JavaScript](), [JIT](), [WebAssembly]() Tags: [command-line](), [cross-platform](), [javascript](), [jit](), [node-js](), [open-source](), [v8](), [web-apps](), [webassembly]() ### AI overview Node.js 25.0.0 is a current release that upgrades V8 to 14.1, adds performance and WebAssembly/JIT improvements, and expands secure-by-default and web-standard APIs. It also finalizes or removes several long-deprecated APIs and introduces features including portable compile cache and JSPI for WebAssembly. ### Source excerpt Node.js® is a free, open-source, cross-platform JavaScript runtime environment that lets developers create servers, web apps, command line tools and scripts. ## Python 3.14.0 (final) is here! DevFeed: [Python 3.14.0 (final) is here!]() Original publisher: [Read original article]() Author: Hugo van Kemenade Published: 2025-10-07T00:00:00Z Content type: release Language: en Sources: [Python Insider]() Topics: [Python 3.14](), [Python](), [releases](), [Compression](), [JIT](), [Command-line interface](), [Processes]() Tags: [command-line](), [compression](), [jit](), [macos](), [new-features](), [optimisations](), [performance](), [processes](), [python-3-13](), [python-3-14](), [release](), [releases](), [windows]() ### AI overview Python 3.14.0 is the stable release of Python's newest major version, introducing free-threaded support, deferred annotation evaluation, template string literals, multiple interpreters, Zstandard compression support, improved debugging and error messages, and other language and runtime changes. ### Source excerpt !Two snakes enjoying a pie with 3.14 on the top and π crimping Python 3.14.0 is now available python.org/downloads/release/python-3140/ This is the stable re... ## Immediate, Automated, Compliant Access Enforcement with Teleport JIT Watcher DevFeed: [Immediate, Automated, Compliant Access Enforcement with Teleport JIT Watcher]() Original publisher: [Read original article]() Author: dan.johns@goteleport.com (Dan Johns) Published: 2025-08-29T00:00:00Z Content type: tutorial Language: en Sources: [Teleport]() Topics: [JIT](), [Security](), [Monitoring](), [DevOps](), [API](), [Go]() Tags: [api](), [devops](), [go](), [jit](), [least-privilege](), [monitoring](), [policies](), [security]() ### AI overview This article presents a Go-based Teleport JIT Watcher that continuously enforces just-in-time access policies. It connects to Teleport's gRPC API using Machine ID, reviews access requests every 30 seconds, automatically approves compliant requests, denies policy violations, and locks old requests to limit access accumulation. ### Source excerpt Immediate, Automated, Compliant Access Enforcement with Teleport JIT Watcher A common request we hear at Teleport is for immediate Just-in-Time (JIT) access. Users shouldn't have standing access to resources, but they do need an audited escalation and approval process they can personally execute when access is required. This raises an important challenge: how do we ensure users only access the resources they truly need, without creating access sprawl or slowing teams down? ## 5 Ways to Keep AWS Fast with Just-in-Time Access DevFeed: [5 Ways to Keep AWS Fast with Just-in-Time Access]() Original publisher: [Read original article]() Author: jpitts@goteleport.com (Jack Pitts) Published: 2025-08-27T00:00:00Z Content type: article Language: en Sources: [Teleport]() Topics: [Amazon Web Services](), [JIT](), [Amazon Elastic Kubernetes Service](), [AWS IAM](), [audit trail](), [Security](), [Amazon EC2](), [AI Agent](), [Amazon Bedrock](), [CI/CD](), [Amazon DocumentDB](), [PostgreSQL]() Tags: [ai-agent](), [amazon-bedrock](), [amazon-rds](), [audit-trail](), [aws](), [aws-iam](), [ci-cd](), [jit](), [least-privilege](), [postgresql](), [security]() ### AI overview This article explains how Teleport's just-in-time access model can help govern fast-moving AWS environments. It describes ephemeral, policy-defined privileges for humans, machines, and AI agents, with least-privilege controls, approvals, expirations, and audit visibility across use cases including EKS, EC2, AWS Console, CI/CD, and AI access. ### Source excerpt Learn how just-in-time access accelerates EKS, EC2, AWS Console, CI/CD, and AI access while eliminating standing privileges and ensuring full audit visibility. ## Building production-ready agentic systems: Lessons from Shopify Sidekick DevFeed: [Building production-ready agentic systems: Lessons from Shopify Sidekick]() Original publisher: [Read original article]() Author: Andrew McNamara Published: 2025-08-26T10:00:00Z Content type: article Language: en Sources: [Shopify Engineering](), [Shopify Engineering - Shopify Engineering]() Topics: [AI Engineering](), [Shopify](), [Artificial Intelligence](), [Architecture & Design](), [Large Language Model](), [grpo](), [JIT](), [data]() Tags: [ai](), [ai-engineering](), [architecture-design](), [evaluation](), [grpo](), [jit](), [llm](), [platform](), [production](), [shopify]() ### AI overview This article describes how Shopify evolved Sidekick from a tool-calling system into a production-oriented agentic platform. It discusses the agentic loop, scaling challenges caused by a growing tool inventory, architecture design, evaluation, GRPO training, and the use of just-in-time instructions to reduce system-prompt complexity. ### Source excerpt Learn how we evolved our AI assistant architecture and built robust evaluation frameworks for real-world deployment. ## Speculative Optimizations for WebAssembly using Deopts and Inlining DevFeed: [Speculative Optimizations for WebAssembly using Deopts and Inlining]() Original publisher: [Read original article]() Author: Daniel Lehmann and Matthias Liedtke Published: 2025-06-24T00:00:00Z Content type: article Language: en Sources: [V8]() Topics: [WebAssembly](), [V8](), [JIT](), [Google Chrome](), [Compiler](), [JavaScript](), [Dart]() Tags: [benchmarks](), [code](), [compiler](), [dart](), [google-chrome](), [internals](), [javascript](), [jit](), [webassembly]() ### AI overview This V8 blog post describes speculative call_indirect inlining and deoptimization support for WebAssembly, shipped with Google Chrome M137. The optimizations use runtime feedback to generate better machine code, improving WebAssembly execution, especially for WasmGC programs. Dart microbenchmarks showed average speedups above 50%, while larger applications and benchmarks improved by 1% to 8%. ### Source excerpt In this blog post, we explain two optimizations for WebAssembly that we recently implemented in V8 and that shipped with Google Chrome M137, namely speculative call_indirect inlining and deoptimization support for WebAssembly. In combination, they allow us to generate better machine code by making assumptions based on runtime feedback. This speeds up WebAssembly execution, in particular for WasmGC programs. On a set of Dart microbenchmarks for example, the speedup by the combination of both optimizations is more than 50% on average, and on larger, realistic applications and benchmarks shown below the speedup is between 1% and 8%. Deoptimizations are also an important building block for further optimizations in the future. Background # Fast execution of JavaScript relies heavily on speculative optimizations. That is, JIT-compilers make assumptions when generating machine code based on feedback that was collected during earlier executions. For example, given the expression a + b, the compiler can generate machine code for an integer addition if past feedback indicates that a and b are integers (and not strings, floating point numbers, or other objects). Without making such assumptions, the compiler would have to emit generic code that handles the full behavior of the + operator in JavaScript, which is complex and thus much slower. If the program later behaves differently and thus violates assumptions made when generating the optimized code, V8 performs a deoptimization (or deopt, for short). That means throwing away the optimized code and continuing execution in unoptimized code (and collecting more feedback to possibly tier-up again later). In contrast to JavaScript, fast execution of WebAssembly hasn't required speculative optimizations and deopts. One reason is that WebAssembly programs can already be optimized quite well because more information is statically available as e.g., functions, instructions, and variables are all statically typed. Another reason is that ## CPython Performance Evolution: From Specialization to JIT DevFeed: [CPython Performance Evolution: From Specialization to JIT]() Original publisher: [Read original article]() Author: Abhimanyu Saharan Published: 2025-05-24T00:00:00Z Content type: article Language: en Sources: [Abhimanyu Saharan]() Topics: [JIT]() Tags: [3](), [adaptive](), [bytecode](), [evolution](), [jit](), [performance](), [python](), [python-3-14]() ### AI overview This article explains CPython's performance evolution from adaptive bytecode in version 3.11 to JIT execution in version 3.14, improving performance without requiring an interpreter rewrite. ### Source excerpt Explore how CPython evolved from adaptive bytecode in 3.11 to JIT execution in 3.14, boosting performance without rewriting the interpreter. ## How Teleport Simplifies Just-in-Time Access DevFeed: [How Teleport Simplifies Just-in-Time Access]() Original publisher: [Read original article]() Author: jack@goteleport.com (Jack Pitts) Published: 2025-04-23T00:00:00Z Content type: tutorial Language: en Sources: [Teleport]() Topics: [JIT](), [Access Control](), [resiliency](), [API](), [Single sign-on (SSO)](), [Command-line interface]() Tags: [access-control](), [api](), [authorization](), [cli](), [condition](), [jit](), [least-privilege](), [policy](), [regex](), [resiliency](), [sso]() ### AI overview This article explains how Teleport integrates just-in-time access with identity, policy, and workflows. It describes role-based access controls, request restrictions, automated approvals, and requirements such as reasons, approval thresholds, regex validation, session moderation, and dual authorization. ### Source excerpt Just-in-time access isn't always easy. Explore how Teleport tackles JIT challenges by simplifying least privilege, streamlining requests, and strengthening resiliency. [Next page]()