AInews: Gemini 3.6 Flash quietly becomes Antigravity’s new default engine

Nic Reeve11:58 29.08.20267 min read

On July 21, 2026, Google rolled out Gemini 3.6 Flash across its developer stack, and the AInews community spotted the new model running inside the Antigravity IDE days before the company fully documented the change. The rollout turns 3.6 Flash into the default engine for Google’s agentic coding tools.

What exactly is Gemini 3.6 Flash and when did it arrive?

Gemini 3.6 Flash is Google’s latest “fast-and-cheap” large language model tier, released on July 21, 2026 as a general-availability upgrade to Gemini 3.5 Flash. It focuses on cutting token costs and latency while improving coding, knowledge work and multimodal tasks, and it launched the same day across Antigravity, the Gemini API and related developer products.

Key release facts gathered from Google documentation and independent technical blogs paint a clear timeline:

Release date: According to Google’s Gemini Enterprise model catalog, Gemini 3.6 Flash reached GA on 21 July 2026.
Coverage: A developer-focused blog reports the model went live simultaneously in the Gemini app, Google Antigravity, AI Studio and Android Studio on the same day.
Knowledge window: That blog notes the knowledge cutoff advanced from January 2025 to March 2026, a 14‑month jump, giving the model fresher technical and product data.
Context length: The same source cites a context window of over 1 million tokens, with maximum output around 65,536 tokens.

Google’s own API changelog describes 3.6 Flash as a “workhorse” tuned for more efficient reasoning and tool calls, targeting long-running coding and agent workflows rather than short chat prompts.

How did Gemini 3.6 Flash first appear inside Antigravity?

Gemini 3.6 Flash surfaced in Antigravity before most users saw formal documentation, after testers noticed a new model ID in the interface and shared screenshots on social media. Those early sightings triggered days of informal testing while Google iterated on the backend and finalized public release notes.

Evidence of this staggered emergence comes from several independent sources:

A leak-focused blog reports that a model identifier “gemini-3.6-flash-tiered” appeared inside Antigravity in the early hours of July 21, 2026, spotted by a tester working in a pre‑release environment.
A developer on X (formerly Twitter) posted that “Gemini 3.6 Flash, ID ‘gemini-3.6-flash-tiered’, appeared in Antigravity a few minutes ago,” confirming that the model showed up in the tool before Google announced pricing and capabilities.
Another technical article describes Google Antigravity 2.0 receiving Gemini 3.6 Flash as part of a broader update, while warning that rollout was staged: some accounts saw the new model immediately, others after a delay attributed to region and account configuration.

Official Google guidance later clarified that Gemini 3.6 Flash powers the default Antigravity agent in “Gemini Managed Agents,” although developers can override the model setting through the API.

What has Google changed under the hood compared with Gemini 3.5 Flash?

Gemini 3.6 Flash mainly targets developers’ complaints about verbosity, token usage and slow workflows in 3.5 Flash. Google documentation and independent tests show lower token consumption, updated pricing and a more aggressive reasoning mode aimed at complex coding tasks.

When placed side by side, the changes look like this:

Token efficiency: A Google blog on Antigravity reports that 3.6 Flash consumes up to 17% fewer output tokens than 3.5 Flash on the Artificial Analysis Index, a synthetic benchmark designed to mimic real coding workflows.
Pricing: Ars Technica’s coverage of the launch notes API pricing of $1.50 per 1 million input tokens and $7.50 per 1 million output tokens, down from $9 per million output tokens in the 3.5 Flash tier.
Reasoning: A technical guide explains that “thinking mode” is enabled by default and can be given an unlimited budget, letting the model run more internal reasoning steps for hard tasks without forcing developers to manage that complexity manually.
Variants: The same guide describes a “3.6 Flash Low” variant aimed at well‑scoped edits, test generation and single‑file changes, with the full 3.6 Flash reserved for heavier agentic workflows.

Google’s changelog stresses that these optimizations target end‑to‑end workflows, not just single responses, by reducing tool calls and iteration loops inside agents built on top of the model.

How does Gemini 3.6 Flash behave inside Antigravity for developers right now?

Inside Antigravity 2.0, Gemini 3.6 Flash sits at the center of Google’s agent-first IDE. It powers code migration, refactoring and multi-user simulations while exposing configuration options to switch models or limit the agent’s reasoning budget for safety and cost control.

From Google examples and third‑party write‑ups, current Antigravity behaviors include:

Code migration: Google’s Antigravity blog shows 3.6 Flash handling legacy software modernization, moving old code to newer frameworks with lower latency and higher quality compared with 3.5 Flash.
Interactive canvases: A Mandarin-language analysis describes Antigravity demos where 3.6 Flash builds interactive canvases and orchestrates SDK workflows, coordinating multiple tools and files from within the IDE.
Multi-user simulations: The same source reports Google using Antigravity and 3.6 Flash to simulate several users editing an offline Markdown editor, stressing long-context coordination.
Agent defaults: A Google AI Studio post states that Gemini 3.6 Flash is now the default engine for the Antigravity agent inside Gemini Managed Agents, with a specific agent version string linked to the preview configuration.

Developers who want to stay on older models can still change the Antigravity model picker, but some community posts describe the 3.6 Flash rollout as a “forced upgrade for IDE holdouts,” reflecting frustration with changing defaults.

How are early users reacting to Gemini 3.6 Flash in Antigravity?

Feedback from Antigravity users is sharply mixed. Many welcome the faster backend and lower token bills. Others complain that the user-facing experience has regressed and that the model sometimes feels less precise than 3.5 Flash despite the architectural improvements.

Public reactions collected across forums and blogs show the spread:

An article on an AI-focused site calls Gemini 3.6 Flash a “blazing-fast backend beast” but “a frontend disaster,” citing confusing UI changes and hard-to-discover configuration options in the updated Antigravity interface.
In a Google developer forum thread from late July 2026, one user warns: “Don’t use 3.6 Flash, it is faster but more dumb and stupid than 3.5 Flash,” complaining that code suggestions became more shallow while latency improved.
The same forum discussion notes intermittent errors where Antigravity fails to run tasks with 3.6 Flash selected, prompting some users to roll back to previous models while Google patches issues.
By contrast, multiple developers on X highlight smoother multi-file refactors and fewer tool calls, with one head‑to‑head demo from Antigravity’s official account showing 3.6 Flash modernizing legacy code faster than 3.5 Flash.

The gap between backend metrics and frontend experience has become a core theme of early coverage. Google’s documentation focuses on token and latency numbers, while community testers concentrate on how those changes feel inside everyday IDE workflows.

What comes next for Gemini 3.6 Flash and Antigravity users?

Gemini 3.6 Flash is now a general-availability model with no announced deprecation date, and Google is treating it as the standard engine for agentic coding in the near term. Developers can expect incremental updates to Antigravity and the Gemini API rather than another immediate model replacement.

Signals from Google and ecosystem coverage suggest several near-term developments:

Support horizon: Google’s deprecation page lists Gemini 3.6 Flash with a launch date of July 21, 2026 and notes that no shutdown date has been set, implying multi‑year support.
Rollout stability: A regional rollout explanation from a third‑party blog tells users that missing 3.6 Flash entries in the Antigravity model menu are likely due to staggered availability, not cancellation.
Evaluation guidance: The same guide urges teams to run side‑by‑side comparisons, switching non‑critical projects to 3.6 Flash and diffing results against existing defaults over at least a week of real work.
Enterprise integration: Google states that enterprises can access 3.6 Flash through the Gemini Enterprise Agent Platform and the Gemini Enterprise app, extending Antigravity-style workflows into corporate environments.

For now, Antigravity remains Google’s main test bed for agentic coding, and Gemini 3.6 Flash is the model under scrutiny. Developers are being encouraged to measure actual workflow costs and output quality, not just headline benchmarks, before committing fully to the new default.

Sources

AI & Tech

AInews: Grok Bot gains deep integration with X social platform

AInews: Grok Bot gains deep integration with X social platform On August 29, 2026, xAI announced that Grok Bot now connects directly to user accounts on X, marking a new phase in AInews coverage and interaction inside the social network through native access to timelines, posts, mentions and developer tools. How does Grok Bot now work with X day to day? Grok Bot can link to an X account, read timelines and mentions, search public posts and act on live social data from inside its chat interface. Paid Grok Bot users receive free X API credits once connected, turning the assistant into a working agent inside the social platform rather than a separate chatbot. According to xAI’s product update on August 29, 2026, the new integration lets users: Connect an X account directly inside Grok Bot via an official X connector. Have xAI automatically create a developer account on X for users who do not already have one. Receive free API credits on X if they are paying Grok Bot subscribers, allowing immediate programmatic access. Ask Grok Bot to search posts, read the personal timeline, check mentions or assemble summaries of what is happening on X in real time. The integration runs on a dedicated cloud execution environment that combines real‑time X data, browser‑level UI control and the Grok model family. This makes Grok Bot more than a chat interface. It becomes an autonomous teammate designed to operate persistently against social data streams. What changed for Grok Bot users with this rollout? The August rollout opened X integration to Grok Bot subscribers and broadened access across multiple paid plans. Users on SuperGrok, Cursor Pro tiers and Cursor Teams can now attach X accounts, use bundled API credits and run bots that watch and respond to activity across X without building their own infrastructure. According to SpaceXAI’s August 11 and August 26, 2026 announcements, Grok Bot availability expanded in two steps: On August 11, Grok Bot launched in beta for higher‑end plans such as SuperGrok Heavy, Cursor Ultra and Cursor Teams Premium, on desktop and iOS. On August 26, Grok Bot was “now included with all” SuperGrok, Cursor Pro and Cursor Teams plans, bringing the bot to a broader subscriber base. These subscriptions sit on top of xAI’s Grok model series. AI Wiki reports that as of August 2026 the flagship engine is Grok 4.6, released via the xAI API on August 12, 2026. That model powers Grok Bot’s reasoning, long‑context analysis and live search, while the August 29 connector turns those capabilities directly onto X’s data. What exactly can Grok Bot see and do inside X? Grok Bot operates as an AI assistant embedded in the X environment. It can read user timelines, track mentions, search public posts and pull together context about trending topics or specific accounts. It also performs web searches when needed, combining X content with broader internet data in its responses. According to a technical guide distributed through X, Grok on X behaves as an in‑platform assistant that can: Answer questions by searching public X posts and cross‑checking with real‑time web results. Solve analytical problems, brainstorm and interact with information, all within the X interface. Run persistent routines as a “durable AI teammate” using the cloud computer backing Grok Bot. Use connectors to reach other services while keeping X as the primary data stream. AI Wiki notes that Grok’s architecture supports context windows up to around 2 million tokens, allowing the assistant to ingest very large volumes of posts and replies when forming an answer. Combined with real‑time X access, this lets Grok Bot analyze conversations, cross‑reference historical threads and surface older posts that remain relevant to current debates. How does this integration fit into Grok’s broader relationship with X? Grok has been tied to X since its initial launch, but the August 2026 Grok Bot connector deepens that relationship. Earlier integrations exposed the Grok chatbot inside X’s interface. The new update turns Grok Bot into a developer‑level agent with API access, shifting the focus from human chat to automated work on the platform. Historical context shows how this has evolved: Grok first arrived in November 2023 as a conversational AI with real‑time X data access, pitched by xAI as a “truth‑seeking” assistant. By late 2024, xAI rolled Grok out to all users on X, with text and vision features and a “draw me” tool linked to profile data, according to company statements from December 12, 2024. In March 2025, X executives signalled plans to integrate Grok into the feed recommendation algorithm, moving away from pure engagement metrics toward AI‑driven ranking. In August 2026, SpaceXAI launched Grok Bot as an autonomous assistant with live X and web integration, described as going “beyond traditional chatbots” through automation. The August 29 connection to X developer accounts sits on top of these steps. It links Grok Bot’s autonomous routines and app‑building features, such as Grok Build on web and mobile, directly to X’s APIs so bots generated inside Grok can immediately read and act on social data. Who can access Grok Bot on X, and on which devices? Access today is tied to subscription tiers and supported platforms. Grok Bot runs on desktop and mobile, with integration aimed at users of SuperGrok and Cursor plans, and at X subscribers who gain Grok features inside the social app. The assistant’s behaviour is consistent across devices, with X providing the data layer. Current availability, based on product and documentation pages updated in August 2026, includes: Desktop apps on macOS (Apple silicon and Intel) and Windows (x64 and Arm64), where Grok Bot operates as a standalone interface linked to X. Mobile apps on iOS 18 and above, offering the same bot controls and X connector as desktop. Web access through Grok’s browser interface, which can also attach an X account. Integration with the X social app itself, where Grok chat and related tools appear for X Premium and higher tiers, according to AI Wiki and earlier rollout reports. AI Wiki’s plan comparison shows Grok reachable through X Premium and Premium+ subscriptions, with Grok access bundled into those social tiers. SpaceXAI’s August announcements then layered Grok Bot on top of xAI’s own paid plans, aimed at developers, teams and power users. What does this mean for developers and power users on X? For developers and advanced users, Grok Bot’s new X integration removes much of the friction involved in using the social platform as data. The connector can bootstrap a developer account, grant initial API credits and attach an autonomous agent that understands both X’s content and external web information in long contexts. The workflow described by xAI now looks like this: Open Grok Bot through web, desktop or mobile and authenticate using the X connector. Let the system create the X developer account where necessary, avoiding manual setup. Use bundled X API credits attached to the paid Grok Bot subscription to start experimentation. Describe routines, dashboards or monitoring tasks in natural language and have Grok Build generate working apps wired into X. Run those agents continuously, watching mentions or topics, compiling summaries and responding to conditions using Grok’s reasoning. This effectively turns X into one of Grok Bot’s default data sources and target environments. Developers can prototype social tools from inside an AI chat window rather than stitching together separate APIs, model endpoints and hosting environments. How does Grok Bot’s integration with X compare with other AI platforms? Grok’s integration with X stands out for its deep access to live social data, very large context window and direct bundling with both social and developer subscriptions. Competing models such as ChatGPT or Gemini offer web search and social plugins, but they do not operate as native agents inside a single major social network at the same level described by xAI. According to AI Wiki and coverage from late 2024, Grok differs in three main ways: Live X platform data is a core feature, not an optional plugin, letting the assistant analyse timelines and conversations as they unfold. Context capacity reaching into millions of tokens allows Grok to handle very long threads, archives and multi‑source documents when building responses. Aggressive API pricing and bundled credits through Grok Bot subscriptions reduce the entry cost for automated agents on X. Other AI chatbots integrate with social media mainly through unofficial tools or limited first‑party features, while Grok Bot is positioned by xAI as a built‑in teammate for X itself. The August 29 connector reinforces that positioning by making Grok part of the default developer stack on the platform. What comes next for Grok Bot and X users? xAI describes the August 29 release as the “first version” of the integration and signals that it intends to make it easier for Grok Bot to “do real work on X.” The company is likely to expand the types of tasks bots can perform, deepen ties to recommendation systems and expose more controls to teams managing brand and community accounts. Future directions, based on public statements and prior roadmaps, include: Closer integration with X’s feed ranking algorithm, building on hints that Grok will power major changes to content recommendations. More advanced app‑building features within Grok Build so agents can publish, share and update X‑connected tools in real time. Expansion of supported plans beyond current SuperGrok and Cursor tiers if adoption grows among regular X users. Refinement of safety controls and approval workflows for autonomous bots acting on public timelines and mentions. For people and organisations relying on X for news, customer support or activism, the new Grok Bot connector means AI‑driven monitoring and response can be set up in minutes. How widely this is adopted, and how visible AI‑driven activity becomes on the social network, will shape the next chapter in the relationship between xAI, Grok and X.

Nic Reeve·14:00 30.08.2026

AI & Tech

AInews: Microsoft board faces derivative suit over AI copyright and disclosure claims

AInews: Microsoft board faces derivative suit over AI copyright and disclosure claims On June 30, 2026, a shareholder derivative complaint filed in the Western District of Washington accused Microsoft directors and officers of misleading investors about the company’s AI strategy and exposing it to copyright and biometric privacy liabilities, a case that legal analysts say could reshape boardroom risk for AI-focused firms and is already being tracked under the label AInews. What does the new lawsuit against Microsoft’s leadership claim? The derivative complaint, Anderson v. Nadella, alleges that Microsoft’s top executives and directors breached fiduciary duties by approving public statements that misrepresented how its AI products were trained and deployed, while the company allegedly relied on copyrighted works and voice data without lawful licenses. The core allegations focus on how Microsoft framed its artificial intelligence roadmap to investors from January 1, 2022 onward. The plaintiff, shareholder Eric Anderson, sues on behalf of the company rather than on his own behalf, a structure that seeks to recover damages for Microsoft itself. The complaint names senior figures including: Satya Nadella – Chairman and CEO of Microsoft, responsible for championing the company’s AI-first vision. Amy Hood – Chief Financial Officer, who signed off on AI-related financial disclosures and projections. Jared Spataro – executive overseeing Copilot and AI at Work marketing. Rajesh Jha – Executive Vice President for Experiences and Devices, linked to Copilot integration across products. Other Microsoft directors who approved proxy statements and public filings. According to a summary by Bloomberg Law on July 1, 2026, the suit alleges that Microsoft’s executives and board "misled shareholders in statements concealing its artificial intelligence tools were trained on copyrighted material." A policy tracker from Mishcon de Reya describes the case as targeting "false and misleading statements about its AI strategy, the Copilot family of products, and financial results". How is copyright and data use at the center of the complaint? The lawsuit claims Microsoft’s directors endorsed an AI strategy that depended on training models on unlicensed copyrighted works and commercialising voiceprints, while telling investors the company complied with global copyright and intellectual property rules. The complaint cites several areas of alleged unlawful data use and exposure: Training AI software, including Copilot and other generative models, on copyrighted books and texts without licensing agreements, such as works included in the Books3 dataset used by OpenAI and related projects. Using copyrighted news and publishing content within Copilot/Bing Chat, subject of suits by publishers including a June 2026 complaint that accuses Microsoft of "direct infringement" through generative output. Collecting and commercialising voiceprints through certain AI services in ways that allegedly conflict with state biometric privacy laws. A July 5, 2026 analysis on The D&O Diary describes the theory of the case as one where Microsoft “told its shareholders and the market that it did not violate federal copyright laws with respect to development and training of AI software, AI generative models, and products,” while facing lawsuits from authors and publishers claiming unlicensed copying to train models. Mishcon de Reya’s August 17 tracker echoes that the complaint accuses officers and directors of causing Microsoft to "violate copyright and IP laws" by training on works and voiceprints without licenses. What timeline of events led to the derivative suit? The filing follows a two‑year run of AI investments, product launches and related litigation, beginning in 2022 and intensifying with author, publisher and biometric privacy claims from 2023 through mid‑2026. Key dates and filings include: January 1, 2022 – present: The derivative complaint defines this period as the relevant timeframe when Microsoft’s statements about AI strategy and compliance were allegedly misleading. September 2023: According to The D&O Diary, Microsoft and collaborators began facing lawsuits by authors, publishers and other copyright holders, alleging that copyrighted material was copied without licenses to train large language models. 2023–2024: The long-running Doe v. GitHub Copilot litigation accuses GitHub, Microsoft and OpenAI of using developers’ code without permission to build Codex and Copilot, adding to the copyright risk context that the new complaint references. February 5, 2026: The derivative complaint notes that Microsoft was sued for alleged violations of Illinois’ Biometric Information Privacy Act (BIPA), beginning with Basich v. Microsoft Corp., docketed as No. 2:26-cv-00422 in the Western District of Washington. June 12, 2026: A separate securities class action was filed in the same court, accusing Microsoft and key executives of misrepresenting the performance and adoption of Copilot AI products. June 30, 2026: Eric Anderson filed his shareholder derivative complaint, Anderson v. Nadella, No. 2:26‑cv‑02281, in the Western District of Washington. July 1, 2026: Bloomberg Law reported on the case, calling it a suit where “Microsoft Corp.'s executives and board directors misled shareholders” about AI tools trained on copyrighted material. August 13–17, 2026: Legal and policy briefings from CCH and Mishcon de Reya added the case to broader trackers of AI copyright risk and shareholder litigation. How does this derivative lawsuit interact with the separate securities class action? The derivative case runs alongside a securities class action in the same district that targets similar alleged misstatements about Copilot and AI investments, but the suits differ in who they claim was harmed and who stands to recover. According to plaintiff-side firm Levi & Korsinsky, the June 2026 securities class action alleges that Microsoft and certain executives "made materially false statements about the Company's AI initiatives while concealing serious operational problems with its Copilot products," including issues with brand positioning, data siloing and computational capacity. The class action is brought on behalf of investors who purchased Microsoft shares and allegedly suffered losses when details about AI infrastructure spending and product challenges emerged. By contrast, the Anderson derivative suit seeks reimbursement to Microsoft itself for harm that the company allegedly suffered when it pursued an AI strategy that exposed it to copyright suits and regulatory risk. A CCH analysis published August 13 explains that Anderson’s derivative action asks the court to hold officers and directors responsible "for breaching their fiduciary duties, causing the company to engage in widespread violation of copyright laws, and approving false and misleading statements". A Substack commentary describes the derivative claim as turning "AI copyright risk into boardroom and securities risk" by linking data sourcing and licensing decisions to shareholder disclosures. What specific misstatements and omissions are alleged? The complaint challenges Microsoft’s proxy statements, financial filings and public remarks that, according to the plaintiff, portrayed Copilot and other AI tools as lawfully trained and fully compliant with copyright rules, while omitting ongoing legal exposure and contested data practices. Alleged misrepresentations, drawn from summaries of the complaint, include: Statements that Microsoft "fully complied with global copyright laws" in the development and training of its AI software, even as the company faced suits from authors and publishers over unlicensed copying. Disclosures that emphasised the success, adoption and capabilities of Copilot across Office, Windows and cloud products, without highlighting technical limitations such as data siloing and computational capacity constraints described in the securities class action materials. Descriptions of Microsoft’s partnership with OpenAI and use of Azure infrastructure that, according to the complaint, failed to reveal alleged reliance on datasets like Books3 containing copyrighted books copied at scale. Financial results and projections premised on rapid AI adoption, presented without detailed discussion of potential liabilities from BIPA lawsuits over voiceprints and facial data. A July 1 Substack analysis summarises the theory as Microsoft’s leadership "built and promoted an AI strategy while misleading shareholders about lawful data sourcing, Copilot performance and legal exposure". The D&O Diary notes that the derivative suit specifically criticises "Silent AI" risks, where training and infrastructure decisions remained opaque to investors while creating copyright exposure. Who is affected by the case and what could happen next? The suit directly targets Microsoft’s directors and senior executives, but its outcome could shape disclosure expectations for AI strategies across the technology sector and influence how boards oversee data sourcing and licensing in machine‑learning projects. The immediate stakeholders include: Microsoft board and executives: Facing claims of breach of fiduciary duty, possible damages, and demands for governance reforms or changes in oversight of AI initiatives. Shareholders: In the derivative suit, shareholders are indirectly affected as any recovery would go to the company; in the securities class action, investors could receive compensation if they prove losses tied to alleged misstatements. Authors, publishers and developers: Their copyright and licensing disputes provide the factual backdrop that the complaint says should have been disclosed more fully. Other AI-focused companies: Legal trackers point to Anderson v. Nadella as part of a "new wave" of derivative cases that extend copyright and data risk into board-level duties, signalling similar exposure for firms using large datasets to train models. Legal commentators expect several possible paths: The court could allow the derivative case to proceed past motions to dismiss, opening discovery on how Microsoft evaluated copyright and biometric risks in its AI programs. Defendants might seek dismissal by arguing that their statements were accurate or protected forward-looking assertions, and that boards relied on expert advice regarding licensing. The case could resolve through settlement, potentially involving changes to governance practices, internal controls around AI training data, and enhanced disclosure of copyright and privacy risks. Whatever the outcome, the combination of derivative and class actions in the Western District of Washington marks a new phase in how courts and investors scrutinise AI business models. As one policy tracker notes, these suits treat AI copyright and privacy questions not only as technical and regulatory issues, but as matters of securities law and board accountability for technology strategy.

Nic Reeve·14:00 10.09.2026

Politics & Elections

Gillibrand and Welch Set Fall Senate Hearing Schedule For Tariff Repeal Bill

Gillibrand and Welch Set Fall Senate Hearing Schedule For Tariff Repeal Bill On August 27, 2026, Senators Kirsten Gillibrand of New York and Peter Welch of Vermont announced the Banning Antiquated Duties and Delivering Equitable American Levies Act, while outlining a tentative senate hearing schedule aimed at repealing tariffs imposed under Section 338 of the Tariff Act of 1930. What did New York and Vermont Senate Democrats propose? New York Senator Kirsten Gillibrand and Vermont Senator Peter Welch proposed the BAD DEAL Act, a bill that would repeal Section 338 of the Tariff Act of 1930, cancel related presidential tariff proclamations, and refund duties already collected from U.S. importers, including newly announced 50% tariffs on Canadian goods. The proposal is formally titled the Banning Antiquated Duties and Delivering Equitable American Levies Act , or BAD DEAL Act. According to the draft bill text published by Senator Welch’s office on August 27, 2026, the measure would: "Repeal Section 338 of the Tariff Act of 1930 (19 U.S.C. 1338)." Void "any Presidential proclamation promulgated in whole or in part pursuant to such section." Require federal agencies to provide refunds of each tariff or duty imposed under Section 338. CPA Practice Advisor reported on August 31, 2026, that the bill is a direct response to new tariffs on Canadian imports, including a 50% duty rate announced by President Donald Trump over the preceding weekend. A press release from Representative Brad Schneider’s office, dated August 29, 2026, describes the BAD DEAL Act as designed to "repeal Section 338 and refund all duties paid under this authority." Why are the senators targeting Section 338 tariffs now? Senators Gillibrand and Welch are targeting Section 338 tariffs because President Trump recently used this long‑dormant law to impose sweeping duties on Canadian imports, including a 50% tariff that Democrats say is hurting American families and businesses and reviving trade tensions with a key U.S. ally. According to WAMC’s report on August 28, 2026, the BAD DEAL Act aims to reverse "Trump administration tariffs on Canada" by repealing tariffs levied under Section 338 and refunding Americans who have been paying the higher prices. CPA Practice Advisor notes that the tariffs apply broadly to Canadian imports and followed a presidential announcement of a 50% tariff rate. Gillibrand’s Senate office framed the move squarely as a consumer issue. In an August 27, 2026 press notice, her office stated that "New York families have spent over $5,000 more due to President Trump’s tariff chaos and other reckless policies," citing the cumulative cost of recent trade measures and inflation pressures. That figure reflects Gillibrand’s internal analysis and is presented as an impact estimate rather than official federal data. The BAD DEAL Act also fits into a wider pattern of congressional resistance to Trump‑era tariff policies. On February 24, 2026, Senator Ron Wyden introduced the Tariff Refund Act of 2026, a separate proposal to refund certain duties after court rulings against earlier tariffs. In October 2025, Senator Welch joined a bipartisan group praising Senate passage of a different measure to repeal Trump’s global tariffs imposed under emergency authorities. These earlier efforts created a legislative backdrop for the targeted repeal of Section 338 in late August 2026. How would the BAD DEAL Act change current tariffs and refund payments? The BAD DEAL Act would repeal the legal authority for Section 338 tariffs, cancel any related presidential proclamations, and order federal agencies to issue refunds to importers for all duties collected under that section, including the recent 50% tariffs on Canadian products. The bill text from Senator Welch’s office lays out the mechanics clearly. Key implementation provisions include: Repeal of Section 338 itself, removing the statutory basis for retaliation‑style tariffs originally crafted in 1930. Termination of any presidential proclamation that invoked Section 338, meaning the tariffs become legally void once the act takes effect. A directive that relevant agencies "take such actions as may be necessary to provide for the refund of each tariff or other duty imposed and collected" under Section 338. Inside U.S. Trade reported on August 28, 2026 that Democrats on both the House Ways and Means Committee and the Senate Finance Committee are backing the measure, viewing refunds as central to the bill’s design. Representative Brad Schneider’s press release underscores that point, saying the BAD DEAL Act would "refund all duties paid under this authority" and thus return money to U.S. businesses that import from Canada. While precise refund totals have not been published, Gillibrand’s office argues that families and firms in New York and other states face higher costs on everyday goods sourced from Canada. By canceling the tariffs and ordering refunds, the sponsors say they aim to ease price pressures and send a message that Congress will not accept unilateral tariff hikes launched under obscure provisions of trade law. What is the planned Senate process and timetable for the tariff repeal bill? The sponsors expect the BAD DEAL Act to enter the Senate Finance Committee when lawmakers return from their August recess, with hearings anticipated in September and potential floor consideration before year‑end, mirroring timelines used for other tariff‑related bills introduced in the 2025‑2026 Congress. CPA Practice Advisor reports that Gillibrand and Welch "signaled their intent to introduce the bill when the Senate returns to session next month," referencing the early‑September reconvening after the summer break. Under standard Senate procedure, tariff legislation is referred to the Finance Committee, which is already handling related measures such as Wyden’s Tariff Refund Act of 2026. The expected steps, based on the sponsors’ statements and usual Senate practice, are: Formal introduction of the BAD DEAL Act in early September 2026, with Gillibrand as the lead Senate sponsor and Welch as co‑sponsor. Referral to the Senate Finance Committee, where staff have experience with tariff repeal and refund proposals. Potential hearings in the fall focusing on Section 338’s history, Trump’s recent tariffs on Canada, and the impact on U.S. businesses. Committee markup followed by a possible floor vote before the end of the 2026 session, depending on broader negotiations over trade and tax legislation. Representative Schneider has already filed the House companion, positioning it in the Ways and Means Committee’s trade subcommittee. That parallel track means House hearings and markups could run close to the Senate’s fall calendar, raising the possibility of a coordinated push to move the repeal through both chambers within months. How does this effort relate to previous congressional actions on Canada tariffs? The BAD DEAL Act builds on earlier federal and state‑level moves opposing Trump’s tariffs on Canada, including a Vermont Senate resolution urging the removal of all Canada‑related tariffs and a 2025 bipartisan Senate vote to roll back other Trump global tariffs. On the state side, the Vermont Legislature adopted S.R.11 in the 2025‑2026 session, a resolution honoring historic ties with Canada and Quebec and calling on Congress to reassert its trade policy role. The text urged President Trump to "remove all tariffs he has imposed on Canada since January 20, 2025," including those outside the United States‑Mexico‑Canada Agreement. That resolution, though symbolic, signaled deep concern in Welch’s home state about the direction of trade relations. At the federal level, Senator Welch has already worked on broader tariff rollbacks. In October 2025, he joined a bipartisan group—including Senators Ron Wyden, Chuck Schumer, Rand Paul, Tim Kaine, Jeanne Shaheen and Elizabeth Warren—in supporting a measure that would repeal Trump’s global tariffs enacted under emergency powers. The resolution passed the Senate on a 51‑47 vote, then moved to the House, setting a precedent for challenging presidential tariff actions. WAMC’s coverage links Gillibrand and Welch’s new proposal directly to those earlier fights over tariffs on Canadian products. Their offices portray the BAD DEAL Act not as a standalone event but as part of a broader effort to restore congressional control over trade and to protect cross‑border economic ties that are central to communities in northern New York and Vermont. Who would be most affected if Section 338 tariffs are repealed? If Congress passes the BAD DEAL Act, importers that pay duties on Canadian goods would see direct financial relief through refunds, while consumers in border states such as New York and Vermont could face lower prices on products sourced from Canadian suppliers. The sectors most exposed to Canada‑focused tariffs include manufacturers and retailers that rely on Canadian inputs, cross‑border wholesalers, and small businesses near the border that import consumer goods. While precise trade volumes tied to Section 338 tariffs have not been released, the sponsors highlight several categories affected by Trump’s latest actions: Household products imported from Canada that now carry a 50% tariff. Industrial inputs and components sourced by manufacturers in New York and New England. Food and agricultural products moving through established cross‑border supply chains. Gillibrand’s office estimated that "New York families have spent over $5,000 more" due to a combination of tariffs and other policies, framing the repeal as part of a strategy to reduce living costs. While that figure aggregates various economic pressures, tariffs on Canada are among the components cited in the senator’s argument for relief. Businesses that paid duties under Section 338 would stand to receive refunds. Inside U.S. Trade notes that Democrats backing the BAD DEAL Act see these refunds as a way to restore competitiveness and cash flow in sectors hit by sudden tariff hikes. Schneider’s press release stresses that the bill is intended to "refund all duties paid", signaling that the sponsors view repayment as a central promise to affected companies. What happens next in Congress and in U.S.-Canada trade relations? The BAD DEAL Act faces negotiations within the Senate Finance and House Ways and Means committees, but it enters the fall session with visible Democratic support and fits broader efforts to ease tensions with Canada, a key trading partner for New York and Vermont. In the near term, the key milestones will be: Formal Senate introduction and committee referral when lawmakers return from recess in early September 2026. Committee work on testimony from business groups, trade experts and possibly Canadian officials or consular representatives. Potential bundling of the BAD DEAL Act with other tariff refund bills such as Wyden’s Tariff Refund Act of 2026, to create a broader package. House hearings under the Ways and Means trade subcommittee on Schneider’s companion bill. If Congress ultimately repeals Section 338 tariffs and orders refunds, the decision would mark a reset of the most recent clash over U.S.-Canada trade triggered by Trump’s 2026 tariff announcement. Vermont’s S.R.11 and past Senate votes against wider Trump tariffs show that concerns about Canada trade are already part of the legislative record. For New York and Vermont, where cross‑border flows of goods and tourism play a visible role in local economies, the outcome of this tariff repeal push will shape prices, business planning and political narratives heading into the 2026 election cycle.

Marcus Feld·14:00 01.09.2026