标签：#SDK

This week's Java roundup for June 29th, 2026, features news highlighting: a new JEP candidate, Strict Field Initialization; point releases of GraalVM, JReleaser, RefactorFirst and Java Operator SDK; maintenance releases of GlassFish and Micronaut; the second milestone release of Grails 8.0; and the beta release of Open Liberty 26.0.0.7. By Michael Redlich

OpenAI Agents SDK 0.13 → 0.17: Three Breaking Changes You Will Hit The OpenAI Agents SDK moved from 0.13 to 0.17 in five weeks (April 9 – May 19, 2026). That's 19 releases, including three breaking changes. Two of them are silent — they change runtime behavior without raising an error at upgrade time. If you're running agents on 0.13.x, this is the migration guide you need before you upgrade. The Three Breaks Break #1: ModelRefusalError (v0.15.0) — Silent to Loud The change: Model refusals used to return empty-string output. Now they raise an exception. What this means: If your code treated refusals as output == "" or checked for empty responses, you were silent-failing gracefully. That behavior changed. A model refusal now raises ModelRefusalError and will crash your agent run unless you handle it. What you need to do: Register a "model_refusal" error handler before upgrading past 0.15.0: from openai.agents import Agent , RunConfig def handle_refusal ( error ): print ( f " Model refused: { error . reason } " ) return " Model refused to respond. Try rephrasing. " agent = Agent ( model = " gpt-4 " , tools = [...], ) config = RunConfig ( on_error = { " model_refusal " : handle_refusal , } ) response = agent . run ( " ... " , config = config ) Without the handler, you'll see: ModelRefusalError: model declined to process this request This is an intentional change — OpenAI wants refusals to be explicit, not silent. But it means your error handling has to change. Impact: Any agent that doesn't add a refusal handler will crash on a refusal. High-risk if your agents field user input directly. Break #2: Default Model Changed (v0.16.0) — Silent Model Switch The change: The default model switched from gpt-4.1 to gpt-5.4-mini . What this means: If you created an agent without explicitly setting model= , you were running on gpt-4.1. On upgrade to 0.16.0+, that same code silently switches to gpt-5.4-mini. This isn't just a version bump — gpt-5.4-mini ships with different defaults

Spencer Judge discusses the architectural pattern of building a shared core in Rust with language-specific layers on top. Drawing from his work on Temporal's SDKs, he shares lessons on navigating FFI boundaries, bridging async concepts, and managing memory safely. He explains the limitations of native extensions and how emerging tech like WebAssembly can streamline cross-language architecture. By Spencer Judge

This week's AI tooling news splits cleanly between infrastructure you can ship today and capability bets that require more careful evaluation. Anthropic dropped two significant releases—Fable 5 and Managed Agents updates—while the Workflow SDK landed a cancellation primitive that eliminates entire categories of homegrown plumbing. Underneath all of it, a sharp incident review from Anthropic is the most practically useful thing published this week if you're running multi-turn agents in production. Workflow SDK adds AbortController cancellation support The Workflow SDK now threads AbortSignal through workflow steps, using the same web-standard API you already use with fetch . Pass an AbortSignal into your workflow, inspect it inside steps, and you get cooperative cancellation that survives durable suspension and replay. This matters because cancellation in long-running workflows has historically required custom infrastructure—timeout flags passed through context, manual cleanup hooks, bespoke race logic. That's not interesting code to write or maintain. With AbortController support, you get timeout steps, request racing, and parallel work cancellation with patterns your team already knows. Two important caveats: this requires workflow@beta , and cancellation is cooperative. The runtime won't forcibly terminate a step—your step code needs to inspect the signal and respond. If you have steps with opaque third-party calls that don't accept signals, you're still writing wrapper logic. Verdict: Ship. If you're on Workflow SDK 5 and running long-horizon workflows with timeout or race requirements, upgrade and wire this in now. The pattern is standard, the boilerplate reduction is real, and there's no meaningful downside if your steps are already structured around explicit control flow. Anthropic adds dreaming, outcomes to Managed Agents Two distinct additions here. Outcomes let you define explicit success criteria enforced by a separate grader agent—replacing manual prompt

How a PHP SDK Can Save You Hundreds of Lines of API Integration Code Most APIs provide documentation, examples, and maybe even a Postman collection. That's usually enough to get started. But once your application grows, you'll quickly discover that working directly with HTTP requests introduces a surprising amount of repetitive code. You end up writing the same things over and over: Authentication headers Request serialization Response parsing Error handling Pagination logic DTO mapping This is exactly why SDKs exist. In this article, we'll look at how a PHP SDK can simplify API integrations and reduce maintenance costs over time. The Hidden Cost of Direct API Calls Let's imagine you're integrating a URL shortening API. A typical implementation might look like this: $client = new GuzzleHttp\Client (); $response = $client -> post ( 'https://example.com/api/links' , [ 'headers' => [ 'X-Api-Key' => $apiKey , 'Content-Type' => 'application/json' , ], 'json' => [ 'url' => 'https://example.com' ] ] ); $data = json_decode ( $response -> getBody () -> getContents (), true ); This doesn't seem bad. Now repeat it for: Create link Update link Delete link Get link List links Create group Update group Get profile Eventually your codebase becomes filled with API boilerplate. The business logic becomes harder to see because it's buried under HTTP implementation details. What a Good SDK Does A well-designed SDK abstracts repetitive tasks and exposes a clean programming interface. Instead of dealing with HTTP requests directly, developers work with resources and objects. For example: $link = $client -> links () -> create ([ 'url' => 'https://example.com' ]); This is easier to read and easier to maintain. The SDK becomes responsible for: Authentication Request building Validation Serialization Response mapping Exception handling Consistent Error Handling One common problem with raw API integrations is inconsistent error handling. Without an SDK, every request may need its own validat