Tag: AI agents

  • Anthropic Message Threads: Faster Claude Agents (2026)

    Anthropic Message Threads: Faster Claude Agents (2026)

    Takeaway: Anthropic’s Messages API now has message threads in public beta (noted in the Claude Platform release notes for Nov 2, 2026). Agents send the full conversation once with thread: {type: "create"}, then only new messages plus the previous response id with thread: {type: "continue", previous_message_id}. Anthropic reports median time to first token (TTFT) about 35% lower on 500k–1M token Claude Code sessions, with threads on by default for most Claude Code users. Smaller requests cut latency — not token cost. Claude still reads the full conversation; pricing and rate limits are unchanged. This is an API/runtime story for long agent loops, distinct from this morning’s ChatGPT Chat/Work tabs merge and from Claude Managed Agents session threads.

    Primary sources: Anthropic’s message threads product article and Messages API message-threads docs; optional press corroboration from The Next Web.

    Why long agent loops were paying a resend tax

    A coding or computer-use agent can make hundreds of Messages API turns in one session. Without threads, every turn re-uploads every earlier user message, assistant reply, tool result, screenshot, and file blob. Once the history sits at hundreds of thousands of tokens, the client spends real time shipping and the API spends real time validating and tokenizing that payload before Claude starts answering.

    Message threads keep a short-lived server-side conversation so most of that work covers only the new turn. Your app still owns the durable transcript: Anthropic’s docs are explicit that the application is the source of truth and must be ready to replay on a 404.

    How create, continue, and replay work

    Send the beta header anthropic-beta: message-threads-2026-08-12 on every request in the thread. The SDK thread helper adds it for you.

    • Create. Call Messages as usual with the full conversation, system, and tools, and add "thread": {"type": "create"}. The API stores the conversation (including Claude’s reply) under the response id.
    • Continue. Send only messages since the previous response, with "thread": {"type": "continue", "previous_message_id": "<prior response id>"}. Leave system and tools out — the thread keeps the create-request values. Keep fixed fields such as model identical or you get thread_fingerprint_mismatch.
    • Replay. Threads are best-effort. A thread expires 5 minutes after its last request and is deleted ≤1 hour after last use. If continue returns 404 (thread_not_found), resend the full conversation in a new create and continue from that new response id. The SDK helper does this replay for you.

    There is no list/read/delete API for threads. Each response id can be continued once; always continue from the latest id. To edit or branch earlier turns, start a new create. Compaction-on-demand is not available with threads — summarize in your code and create a new thread from the summary.

    What the ~35% TTFT claim means (and what it does not)

    Anthropic’s article states that with message threads on by default for most Claude Code users, requests with 500k to 1M tokens see median TTFT drop by about 35%. That is a latency win from smaller uploads and less re-validation/tokenization of the prior history.

    It is not a cost cut. Claude still reads the full conversation on every turn. Token usage, standard Claude token rates, and existing rate limits stay the same. Do not budget “35% cheaper agents” — budget “snappier first token on huge sessions.” Prompt caching still needs explicit cache_control; a thread does not cache the prompt for you.

    Best use cases

    • Long-running coding agents — each tool result or file edit grows the conversation; Claude Code is already leaning on threads by default for most users.
    • Computer-use agents — screenshots can stay with the thread instead of being re-uploaded every turn (see also our note on Vercel Labs agent-desktop accessibility computer use).
    • Document- and image-heavy workflows — large multimodal payloads benefit most when only the delta ships after create.
    • Active sessions where latency matters — threads help most when turns keep coming inside the 5-minute idle window.

    For adjacent agent product patterns outside Anthropic, see GitHub Copilot connected cloud sessions and MCP connectors and DeepSeek’s open-source coding agent prototype. OpenAI’s product UX merge of Chat and Work is a different layer — UI consolidation, not Messages API request shaping — covered in our morning ChatGPT Chat/Work merge post. Capacity stories such as ChatGPT + Codex shared December usage limits are likewise separate from Anthropic’s thread latency feature.

    Message threads vs full-resend Messages API

    DimensionFull-resend Messages APIMessage threads (beta)
    What you send after turn 1Entire conversation every turnOnly new messages + previous_message_id
    system / tools on later turnsTypically re-sentCreate-only; sending them on continue → 400
    TTFT on huge sessionsGrows with history upload/validate workAnthropic: ~35% median TTFT drop at 500k–1M (Claude Code)
    Token cost / rate limitsStandardUnchanged — Claude still reads full history
    Server storageNone for your historyIn-memory, encrypted; never durable disk
    ExpiryN/AExpire 5 min after last request; deleted ≤1 hour after last use
    Client responsibilityOwn the transcriptOwn the transcript + replay on 404
    Beta headerNone for classic Messagesmessage-threads-2026-08-12
    ZDR / HIPAA readinessPer existing org featuresThreads not ZDR or HIPAA eligible

    Limits, data retention, and availability

    • Memory only: threads are held encrypted in memory under a server-managed key, never written to durable storage, and deleted no more than 1 hour after last use.
    • Not ZDR / HIPAA eligible for the thread feature itself. Using threads does not strip ZDR eligibility from other features you use without threads.
    • Not supported with: Message Batches, token counting requests that include thread, compaction-on-demand, most context editing (except limited clear_thinking keep-all), orgs with HIPAA readiness enabled, orgs with Inference hooks turned on.
    • Distinct from Claude Managed Agents session threads — different product surface.
    • Available (beta) on all models via Claude API, Claude Platform on AWS, Claude Models on Google Cloud (Anthropic managed), and Claude in Microsoft Foundry.

    Publisher / developer checklist

    1. Add the beta header message-threads-2026-08-12 on every create and continue (or use the SDK thread helper).
    2. Keep your own conversation copy from day one; design the 404 → full create replay path before production traffic.
    3. Omit system and tools on continue; keep fixed fields identical to create.
    4. Expect idle expiry — if your agent pauses >5 minutes, plan for recreate/replay.
    5. Do not assume cost savings — measure TTFT and request size, not “free tokens.”
    6. Combine with prompt caching deliberately if you want cache hits; top-level cache_control is a fixed field when used.
    7. Skip threads for ZDR/HIPAA-ready orgs that cannot use this beta, or fall back to full-resend without thread.
    8. Do not confuse with Managed Agents session threads or with ChatGPT UI tab merges — different problems.

    FAQ: Anthropic message threads

    Do message threads reduce my Claude token bill?

    No. Anthropic is clear that Claude still reads the full conversation each turn. Pricing and rate limits are unchanged. Threads primarily reduce request size and time to first token.

    What beta header do I need?

    Send anthropic-beta: message-threads-2026-08-12 on every request that uses thread. The official SDKs’ thread helpers attach it for you.

    What happens if I get a 404 on continue?

    Treat it as thread_not_found (confirm via error.details.error_code). Replay by sending the full conversation again with thread: {type: "create"}, then continue from the new response id. Causes include expiry, a turn the API did not store, fallback-model replies, ownership/key mismatch, and more.

    Are threads durable chat history?

    No. Contents live in encrypted memory, are never written to durable disk, expire 5 minutes after the last request, and are deleted within an hour of last use. Your application must keep the durable copy.

    Is this the same as Claude Managed Agents session threads?

    No. Anthropic’s docs call out that Messages API message threads are different from session threads in Claude Managed Agents. Message threads are a Messages API request-shape optimization for agent loops.

    Does this replace OpenAI’s Chat/Work merge story?

    No. OpenAI’s Chat and Work tabs merge is a ChatGPT product/UI change. Anthropic message threads are a Claude Messages API beta that shrinks later-turn payloads for long agents. Cover both as complementary industry moves toward smoother agent loops — not the same feature.


    Bottom line: Anthropic’s public-beta message threads let long-running Claude agents create once and continue with deltas, cutting median TTFT roughly 35% on huge Claude Code sessions without changing token pricing. Build for short-lived in-memory threads, own your transcript, and replay on 404 — then cite the official docs when you ship. For the parallel OpenAI UX consolidation story from this morning, see ChatGPT Chat/Work tabs merge.

  • ChatGPT Merges Chat and Work Tabs: What Changes (2026)

    ChatGPT Merges Chat and Work Tabs: What Changes (2026)

    Takeaway: OpenAI is merging ChatGPT’s separate Chat and Work tabs into one ChatGPT experience so you can explore an idea and then have ChatGPT carry the work through — files, plugins, websites, presentations, and guided web tasks — without jumping tabs. The change starts with select users for feedback, then a wider rollout; OpenAI has not announced a wide-release date. Codex stays a separate section in the ChatGPT desktop app. This is a product/UI story, distinct from the December shared ChatGPT + Codex token/usage pool we already covered.

    Reporting: TechCrunch (Ivan Mehta, Nov 2, 2026), with corroboration from Digital Trends, The Verge, and Financial News Asia coverage (Nov 3).

    Why Chat and Work felt confusing

    On the ChatGPT desktop app, users already juggle a high-level split between ChatGPT and Codex. Inside ChatGPT itself, a second split — Chat versus Work — made it easy to lose track of where a project lived. TechCrunch summarized the UX problem plainly: with so many options, it is sometimes easy to forget where you are working and where a project actually sits.

    In practice, Chat handled everyday conversation, Q&A, and brainstorming. Work was the lane for heavier, multistep jobs — research, presentations, website builds, and similar deliverables. Switching tabs mid-flow broke context and made “agentic” work feel bolted on rather than continuous.

    What OpenAI told users about the merge

    According to an email OpenAI sent to users (as reported by TechCrunch), the company is combining Chat and Work within the ChatGPT experience. The merge will first go to select users for feedback before a broader rollout.

    Paraphrasing the email’s stated intent: the goal is to let you move from exploring an idea to having ChatGPT carry it through in one place. You can bring in files and plugins and ask ChatGPT to build a website, create a presentation, or do things on the web while you review and guide the work. Codex remains a separate experience in the ChatGPT desktop app.

    The Verge noted that OpenAI’s Thibault Sottiaux posted on X that the company is working on this but that it is not rolling out just yet — useful framing if you have not seen the merged UI yet: select-user feedback does not equal a global flip.

    Chat vs Work vs merged ChatGPT vs Codex

    SurfaceWhat it is forWhat changes with the merge
    Chat (today)Conversation, Q&A, brainstormingFolds into one ChatGPT workspace with Work capabilities
    Work (today)Heavier tasks: research, decks, sites, multistep jobsSame capabilities, reachable without a separate tab
    Merged ChatGPT (incoming)Idea → execution in one place; files/plugins; guided agentic workSelect users first, then wider; no public wide-release date yet
    Codex (desktop)Specialized coding experienceStays separate in the desktop app — not merged into Chat/Work

    Digital Trends’ framing matches that table: start a conversation, then ask ChatGPT to execute from the same place, keep files and plugins in play, and monitor progress instead of hopping tabs to find the “agent mode.”

    Usage limits: shared pool note (not the same story as this UI change)

    OpenAI also said that with this transition, ChatGPT and Codex will draw tokens from the same allowance pool. Most users should be unaffected; depending on usage and model, some people may wait for resets more often.

    Treat that as a related capacity note, not the headline of this article. We already published a dedicated explainer on the December shared ChatGPT + Codex usage limits for eligible plans. Do not confuse the tab merge with card/device paid-account limits (“Device limit reached”), which gate which paid accounts you can run on a device — a separate control layer.

    Why the industry is collapsing chat and agent modes

    Anthropic merged Claude’s chat and Cowork into one screen around September 2026 (per TechCrunch). OpenAI’s move follows that pattern: conversation and agentic execution stop being rival “apps” inside the same product.

    Financial News’ Asia write-up frames the strategic angle: erasing the boundary between Q&A chat and agent workflows (web tasks, analysis, documents, presentations) is meant to lower the barrier to everyday agent use — assign work inside a normal conversation instead of hunting for a separate agent tab.

    That same industry wave shows up outside OpenAI: cloud coding sessions and computer-use surfaces keep pushing agents into the main workflow rather than a side panel. See our recent notes on GitHub Copilot connected cloud sessions and MCP connectors and Vercel Labs agent-desktop accessibility computer use for adjacent product patterns.

    What stays the same for power users

    • Codex remains separate in the ChatGPT desktop app — coding-focused workflows are not being folded into the Chat/Work merge.
    • No announced wide-release date — expect a staged select-user period, then broader availability.
    • Guidance and review still matter — OpenAI’s email language emphasizes reviewing and guiding ChatGPT’s work, not fire-and-forget automation.
    • Shared token allowance between ChatGPT and Codex is a capacity change that can affect heavy users even when the UI looks cleaner — details in our December shared-pool article.

    Publisher and power-user checklist

    1. If you train teammates on ChatGPT desktop, update screenshots and SOPs: Chat vs Work may disappear for select users first.
    2. Keep Codex docs separate — coding still lives in its own desktop section.
    3. Watch usage meters after the transition language around a shared ChatGPT/Codex allowance; heavy agent + coding days may hit resets sooner.
    4. Do not equate “select users” with GA — Sottiaux’s public note underscores that a full rollout is not live for everyone yet.
    5. Separate this UI story from account eligibility — card/device limits and “Device limit reached” are covered in our paid account caps explainer.
    6. For agentic competitor context, skim Copilot cloud sessions and Vercel agent-desktop coverage linked above when comparing how vendors place agents in the primary UI.

    FAQ: ChatGPT Chat and Work merge

    Is OpenAI deleting Work features?

    No. Reporting describes a merge into one ChatGPT experience so Work-style capabilities (files, plugins, building sites, presentations, guided web tasks) sit in the same place as conversation — not a removal of those capabilities.

    When does the merged Chat and Work UI ship to everyone?

    OpenAI has not announced a wide-release date. The email, as reported by TechCrunch, says select users first for feedback, then a wider rollout. The Verge also cited Thibault Sottiaux saying the company is working on it but it is not rolling out just yet.

    Does the merge include Codex?

    No. OpenAI’s email states Codex remains a separate experience in the ChatGPT desktop app.

    Will this change my ChatGPT usage limits?

    OpenAI said that with the transition, ChatGPT and Codex draw from the same token allowance. Most users should not notice; some may wait for resets more often depending on usage and model. For the broader December shared-pool product story, see our dedicated shared usage limits article.

    How is this different from Anthropic’s Claude change?

    Directionally similar: Anthropic merged Claude chat and Cowork into one screen around September 2026. OpenAI is now combining ChatGPT’s Chat and Work tabs along the same “conversation + agent work in one place” pattern.

    Is this the same as ChatGPT device limit reached?

    No. Device and card limits control paid-account purchase and device eligibility. The Chat/Work merge is a product UI change. See our Device limit reached explainer if you are hitting account-eligibility warnings.


    Bottom line: OpenAI is collapsing ChatGPT’s Chat and Work tabs into one place so brainstorming and agentic execution share a single surface, starting with select users and expanding later — with no public GA date yet and Codex still separate on desktop. Read the capacity angle in our December shared ChatGPT + Codex usage pool post, and keep account-eligibility issues on the separate device-limit track.