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Agentic workflow comparison

ChatGPT Work or Claude Cowork: delegate the process without losing control

A detailed guide to longer AI work across files, apps, research and finished deliverables, with practical permission boundaries, approval points and recurring workflow examples.

Written for: People considering an AI agent for multi step knowledge work, finished files or recurring preparation rather than a single conversational answer

Apply this to my workAll comparisons

Read this before comparing

An agent is not simply a stronger chatbot. It receives an outcome, decides intermediate steps and may read files, use applications, browse, run code or create and change material. The key design question is therefore not which agent can do more. It is which one can complete this particular job with the smallest useful permission set, visible progress, reversible outputs and a clear human review point.

What each option is really for

These are starting orientations. The workflow and review still decide.

Longer work inside ChatGPT

ChatGPT Work

An agentic ChatGPT mode for research, analysis and finished documents, spreadsheets, presentations, reports or Sites, with Projects, connected apps and Scheduled Tasks available around the workflow.

Strong starting point for

  • A longer task that begins in an existing ChatGPT Project with approved files and instructions
  • Work that must end as an editable office file, report, presentation, spreadsheet or Site
  • A process that combines research, connected apps, analysis and deliverable creation
  • Recurring or monitored work where the output can wait for a named reviewer

Poor fit when

  • A quick question or small edit that normal Chat can complete faster
  • A task with broad connected app access and no reason for each source or action
  • A process that cannot define approval points, stopping conditions or what a correct deliverable looks like

Bounded work across files and tools

Claude Cowork

An agentic Claude mode that can work across selected projects, files, connectors, browser and computer tools, create finished outputs and run scheduled tasks with capability depending on the surface.

Strong starting point for

  • File centred work inside a deliberately selected folder or Claude project
  • Long tasks that need careful source reading before creating documents, spreadsheets, presentations or organised files
  • Workflows using Claude Skills, plugins, connectors or Live Artifacts
  • Recurring reports or briefings that can run remotely and wait for human review

Poor fit when

  • A task granted access to a whole drive, home folder, inbox or application when one bounded source would do
  • Scheduled work that sends, deletes, purchases or changes systems without review
  • A process whose owner expects to validate every low level command instead of defining task level boundaries and watching for scope drift

Compare the parts that change the work

Each row ends with the decision rule and the human check that prevents a feature list from becoming a recommendation.

QuestionChatGPT WorkClaude CoworkChoose byHuman checkpoint
When to leave chatOpenAI describes Chat for quick questions and conversation, and Work for longer multi step tasks and finished deliverables. Work is unnecessary overhead for a small reversible request.Cowork is useful when Claude must carry out a process across files or tools rather than merely explain it. Ordinary Claude chat remains the simpler route for a contained answer or draft.Use an agent only when planning, tool use, file creation or repeated steps are a material part of the job. More autonomy is not a reward for an important sounding task.What work must happen between the request and the final result that ordinary chat cannot complete cleanly?
Starting contextWork can start from a ChatGPT Project, using its related chats, files and instructions as context, or from a fresh task with uploaded and connected material.Cowork can start from projects, account files, connectors or selected local folders. Local folder access and some local tools depend on Claude Desktop being available.Choose the environment where the authoritative context can be made clear and kept current without exposing unrelated material.Which version is authoritative, which files are irrelevant or stale, and who owns keeping the project context accurate after this run?
Files on your computerDesktop Work can use local folders and desktop apps with permission. Local chats remain on that computer, while cloud Work behaves differently across web, mobile and desktop.Cowork can reach selected local folders through Claude Desktop. Remote sessions can only use those local files while the desktop app is open and within the permissions already granted.Prefer a dedicated working folder containing copies of only the material needed for the task, regardless of product.Would an accidental read, overwrite or deletion inside the granted folder be acceptable and recoverable?
Connected appsWork can use connected apps and files as part of a longer process, subject to plan, workspace and connection settings.Cowork can use connectors, Skills and plugins, and may use the browser or computer when a direct connector is not available.Use the most precise reliable integration first. Screen control should not replace a supported connector merely because it looks more autonomous.Does every connected system contribute to the outcome, and can the agent move information between systems in a way the affected people did not expect?
Finished outputsWork is explicitly designed to create editable documents, spreadsheets, presentations, reports and Sites from instructions, templates and source material.Cowork can create finished files and organise outputs, while Claude also supports Office file creation and Live Artifacts on supported surfaces.Compare the editable result in its final application. File generation is useful only when the content, calculations, layout and handover survive outside the agent interface.Who checks formulas, links, source notes, accessibility, branding and the assumptions that the file now makes look final?
Progress and steeringWork lets the user follow progress, answer questions, change direction and approve important actions as the task runs.Cowork sessions can be started, steered and reviewed across supported surfaces, with notifications when work finishes or needs input.Choose the route whose progress view helps you catch a wrong plan early and whose questions arrive before a consequential action, not after it.What signal tells you the agent misunderstood the task, and at what point does continuing become more expensive than restarting?
Permissions and approvalsWork should receive only the files, apps and actions the task needs, with important actions held for approval. Product and workspace controls determine what is available.Cowork distinguishes read and write tools and recommends human oversight for high stakes work. Approval modes change how much can happen before the user intervenes, while permanent deletion still requires permission.Select the narrowest permission mode that can complete the task. Write access, browser control and automatic approvals need a stronger reason than read only preparation.List every action the agent may take without asking and decide whether each is reversible, observable and appropriate for this material.
Scheduled workWork can use Scheduled Tasks that run once, on a schedule or trigger, or monitor for changes. Exact access and active task limits depend on plan and workspace.Cowork scheduled tasks can run remotely, use approved connectors and account files, and return reports or summaries even when the computer is off. They cannot use a local computer folder while running remotely.Start with low risk information preparation, keep the result waiting for review and choose by approved source access and run history visibility.Who reviews every run, what missing source must be reported, and which condition automatically pauses the schedule?
Security and prompt injectionAny agent using connected material or the open web can encounter instructions embedded in content. Broad tools and permissions increase the possible impact of following them.Anthropic explicitly warns that malicious content can steer Cowork and that risk depends on what it can see and do. Manually approve higher stakes tasks and use dedicated folders.Treat all external content as untrusted input. Keep access narrow, prevent irreversible action and design the workflow so a hostile instruction cannot silently become authority.Could a document, email or webpage tell the agent to access another system, reveal information or take an action outside the user's stated goal?
Choosing the model inside the agentEligible Work users can choose among GPT-5.6 Sol, Terra and Luna and set effort. Use a lighter model for stable routine work and Sol when complexity earns it.Cowork can use Claude models within the product experience. Sonnet is a practical default and Opus should be reserved for tasks whose complexity or failure rate justifies it.First choose the agent workflow, sources and permissions. Then use the least expensive model and effort level that repeatedly passes the output review.Is the agent failing because the model needs more capability, or because the task, source pack and approval boundary were never made clear?
Review and auditThe finished output, progress history, cited sources and connected context should support a reviewer in understanding what happened and correcting the result.Cowork exposes session progress and scheduled run history, but the user should monitor task level patterns rather than assume every command can be individually validated.Choose the route that leaves enough evidence for the accountable person to verify the result without replaying the entire job from memory.Can a reviewer identify the sources, transformations, exceptions, approvals and unresolved decisions that produced the final output?

See how the same work changes by route

These are complete starting workflows, not prompt examples without preparation or review.

Workflow

Prepare a weekly operations report

Every Friday someone collects figures, incidents, staffing notes and project updates from several approved sources, then turns them into a report for Monday review.

ChatGPT Work route

  1. Create a Project containing the report template, definitions, audience guidance and a list of approved source connections.
  2. Run the report manually in Work for several weeks and require a source and timestamp beside each material figure or claim.
  3. Define how missing, delayed or conflicting data appears in the report instead of allowing the agent to fill the gap.
  4. Schedule the task only after the report structure, exceptions and reviewer handoff are stable, and keep all external communication outside the automation.

Starter brief

Prepare the weekly operations report for [audience] using only [approved sources]. Follow the attached template and definitions. Cover [sections]. For every figure or material statement, show the source and reporting date. Compare with the prior week only when both periods use the same definition. Mark unavailable, late or conflicting data as an exception and do not infer a replacement. Create the editable report for review by [owner]. Do not send, publish or update any system. Finish with a run log listing sources reached, sources unavailable, calculations performed and decisions that remain human.

Claude Cowork route

  1. Create a Cowork project or bounded folder with the report template, approved files and workflow instructions.
  2. Use connectors for recurring systems and keep local folder access limited to the report working area rather than a broader drive.
  3. Prove the task manually and inspect how Cowork handles stale files, missing fields and contradictory notes before scheduling it.
  4. Schedule a report only workflow, review every run from the Scheduled page and pause it whenever a source or definition changes.

Starter brief

Create the weekly operations report for [audience] from [approved connectors and files]. Use the supplied template and definitions. Each material figure, incident or conclusion must identify its source and date. Show missing, stale or conflicting information clearly and do not resolve it by guessing. Save the editable report for [reviewer]. Do not send messages, change source files or update external systems. Add a run summary naming every source used, each access problem, every transformation and the items that need a human decision.

Decision rule: Both routes can prepare a recurring report. Work is attractive when the sources and template already live in ChatGPT Projects and apps. Cowork fits a carefully bounded file and connector process. The safer first success is a reviewed report, not automated distribution or operational action.

The Human Bit checks

  • Own the metric definitions and confirm that comparisons use the same basis.
  • Review missing data and exceptions before reading the narrative conclusion.
  • Check the most consequential figures directly against the source system.
  • Name one reviewer and one condition that pauses the recurring task.
  • Keep sending, posting and system updates as separate approved actions.

Workflow

Build a board or leadership pack

A leadership pack must combine reports, financial extracts, project updates and narrative into a coherent document or presentation without losing evidence or exposing unnecessary detail.

ChatGPT Work route

  1. Provide the approved source pack, prior template, audience, meeting purpose and the decisions the pack must enable.
  2. Ask Work to propose the storyline, slide or section purpose and evidence map before creating the final files.
  3. Approve the structure and remove material that is interesting but does not support a decision or required oversight.
  4. Create the editable deliverable, then verify every figure, chart, source note, confidentiality label and requested decision in the final application.

Starter brief

Create an editable [board paper or presentation] for [meeting and audience] from the attached approved sources. The meeting must decide or oversee [outcomes]. First propose the narrative, section purpose and evidence map for approval. Keep provider claims, internal facts and interpretation distinct. After approval, create the file using the existing template. Do not invent missing figures or smooth over disagreement. Add source notes to material claims, preserve confidentiality markings and include a final review sheet for numbers, charts, risk statements, decisions requested and information that should be removed before circulation.

Claude Cowork route

  1. Create a dedicated project or folder containing copies of the approved source documents and final template only.
  2. Ask Cowork to read and organise the source pack, then create a narrative brief separating evidence, interpretation and open decisions.
  3. Approve the narrative before allowing file creation, and use Claude's document or presentation output for the editable pack.
  4. Inspect the final file and folder for unintended source copies, sensitive content, broken formatting and unsupported conclusions before circulation.

Starter brief

Use this bounded source folder to create an editable [board paper or presentation] for [audience]. The meeting purpose is [purpose] and the required decisions are [decisions]. First produce a narrative and evidence map that distinguishes direct facts, management interpretation and unresolved risk. Wait for approval before creating the final file. Use the supplied template, attach sources to material claims, mark gaps rather than filling them and finish with a handover covering factual checks, sensitivity review, file contents and every judgement that remains with the accountable executive.

Decision rule: Work offers a direct path from mixed inputs to polished deliverables inside ChatGPT. Cowork offers a strong bounded folder and source reading route. Choose by source governance, template fidelity and the quality of the final review handover, not by which agent creates more slides unaided.

The Human Bit checks

  • Approve the narrative and decision structure before file production.
  • Trace every financial, operational and risk statement to the approved source.
  • Remove personal, speculative or operational detail the audience should not receive.
  • Open the final file in PowerPoint, Word or the required application and test it there.
  • Ensure an accountable executive owns the recommendation and accepted risk.

Workflow

Create a client deliverable from a source folder

A consultant, agency or service team needs to turn approved client material into a report, proposal or presentation while keeping internal notes and unrelated client files out of scope.

ChatGPT Work route

  1. Create a client specific Project and upload only the approved material, template and instructions for the current engagement.
  2. Use Work to inventory the sources, identify gaps and propose the deliverable structure before drafting.
  3. Keep internal commercial notes and material from other clients outside the Project and disconnected from the task.
  4. Review the editable output for factual accuracy, contractual promises, client voice, source use and anything that creates an unintended commitment.

Starter brief

Create an editable [report, proposal or presentation] for [client] using only the material in this Project. The purpose is [outcome], the audience is [audience] and the approved scope is [scope]. First inventory the sources and identify gaps, conflicts and anything that appears internal rather than client facing. Propose the structure for approval. Then create the deliverable without importing outside assumptions or making commitments not supported by the brief. Mark every gap, keep claims traceable to the source and provide a final client sensitivity and commitment checklist.

Claude Cowork route

  1. Create a dedicated working folder with copies of approved client inputs, a clean output folder and no unrelated material.
  2. Grant Cowork access only to that folder and the exact connectors required for the engagement.
  3. Ask for a source inventory and content plan, then review what it intends to use before it writes or reorganises files.
  4. Inspect the output folder, final deliverable and any changed source file before sharing anything with the client.

Starter brief

Work only inside this dedicated client folder. Use the approved inputs to create [deliverable] for [audience] and [outcome]. Do not open, move, rename or use material outside the connected folder. First inventory the files, separate client facts from internal notes and propose the deliverable plan. Wait for approval before creating the final file. Preserve source traceability, mark missing information and finish with a list of files created or changed plus checks for facts, promises, pricing, tone, confidentiality and client suitability.

Decision rule: Use ChatGPT Work when a client Project is the clearest governed container. Use Cowork when a dedicated local folder and file level boundary make the process easier to understand. In either case, isolation between clients is a design requirement, not a final review task.

The Human Bit checks

  • Keep each client in a separate governed Project or folder.
  • Exclude internal pricing, blame, margin, negotiation and unrelated client material.
  • Check every promise, date, scope statement and price before sharing.
  • Review the deliverable through the client's likely interpretation and relationship context.
  • Share only after a person confirms the final file and output folder contain nothing unintended.

Workflow

Run a recurring research and change watch

A team wants a regular briefing on competitors, regulation, technology or market change without receiving a noisy list of links or allowing an agent to make decisions from weak signals.

ChatGPT Work route

  1. Define the topic, decision relevance, approved source classes, exclusions and threshold for what deserves reporting.
  2. Run Deep research or a Work task manually and review whether it distinguishes new evidence from repeated commentary.
  3. Create a Scheduled Task that monitors or researches at the required cadence and prepares a cited brief only when the threshold is met.
  4. Keep alerts, recommendations and external action separate so a human decides what the change means and who should be told.

Starter brief

Monitor [topic] every [cadence] for changes that could affect [decision or team]. Use [approved source classes] and exclude [sources or noise]. Report only developments that are new since the prior run and meet this materiality threshold: [threshold]. For each item, cite the original source, state what changed, distinguish fact from interpretation and explain why it may matter without recommending action as if the evidence were settled. If nothing meets the threshold, return no briefing. Save any briefing for [reviewer] and include a source and uncertainty log.

Claude Cowork route

  1. Create a research task with explicit source, novelty and materiality rules and test it manually against a period you already understand.
  2. Use approved web research, connectors and account files, keeping local computer folders out of a remote schedule.
  3. Schedule the task after the output reliably separates original reporting, repeated commentary and unresolved claims.
  4. Review past runs, pause when the source landscape changes and keep escalation or communication as a separate human decision.

Starter brief

Create a recurring [cadence] research brief on [topic] for [audience]. Use [approved web and connected sources]. Identify only material developments that are new since the previous run. Separate original evidence, company claims, independent analysis and repetition of the same origin. Cite each item, explain what changed and why it may matter, and state the uncertainty. Do not send messages or recommend a consequential action. If nothing crosses [materiality threshold], produce no brief. Save the output for [reviewer] with a run history of sources checked and sources unavailable.

Decision rule: Both can support recurring research. Work is attractive when Deep research, Projects and OpenAI app context are already part of the process. Cowork fits a recurring research task using Claude connectors and scheduled sessions. Quality depends more on novelty, source and materiality rules than on frequency.

The Human Bit checks

  • Define what is material enough to interrupt the team before scheduling anything.
  • Count repeated commentary from one origin once rather than mistaking volume for confirmation.
  • Open the original source behind any development that could change a decision.
  • Keep recommendation and communication with the accountable person.
  • Pause the schedule when sources, terminology or the decision being monitored changes.

Workflow

Turn a spreadsheet into a reviewed presentation

A recurring performance deck must use a spreadsheet, explain what changed and create charts and commentary without corrupting formulas or turning correlation into a confident story.

ChatGPT Work route

  1. Provide the approved workbook, metric definitions, prior deck and audience decision, then ask Work to inspect before editing or charting.
  2. Require a calculation and chart plan that states which worksheet and cells support each conclusion.
  3. Approve the analysis, then create the editable presentation and keep source notes with each chart or claim.
  4. Open both files in their final applications and compare figures, formulas, filters, scales and labels before accepting the narrative.

Starter brief

Use the attached workbook to create an editable performance presentation for [audience]. The audience needs to decide [decision]. First inspect the workbook and report its sheets, date coverage, definitions, formulas, filters, missing values and any inconsistency. Propose the analysis and chart plan with exact source ranges. Wait for approval. Then create the deck without altering the source workbook unless explicitly allowed. Keep every chart tied to its range, avoid causal language unless supported and finish with a reconciliation sheet for figures, formulas, chart scales and management interpretation.

Claude Cowork route

  1. Place an approved copy of the workbook, prior deck and output template in a dedicated folder or use the supported Office integrations.
  2. Ask Cowork to inspect structure, formulas and definitions, and to propose the story before moving data or charts between files.
  3. Use manual approval before any cross application transfer when the workbook contains sensitive or unrelated worksheets.
  4. Review the resulting workbook and presentation separately, including every value moved between them and the interpretation attached to it.

Starter brief

Work only with the approved workbook and presentation template in this folder. Prepare a performance deck for [audience] and [decision]. First inspect the workbook structure, formulas, definitions, date coverage, filters and missing data. Propose the calculations, chart sources and narrative for approval before creating or editing files. Do not move information from an unrelated worksheet. Preserve exact source ranges, distinguish observed movement from interpretation and provide a handover listing every file changed plus checks for values, formulas, chart scales, labels, confidentiality and unsupported causal claims.

Decision rule: Work offers a strong end to end deliverable route inside ChatGPT. Cowork can coordinate bounded files and Office workflows. Choose the route that makes data lineage, file changes and cross application movement easiest to inspect and restrict.

The Human Bit checks

  • Approve metric definitions and calculation logic before chart creation.
  • Reconcile every reported value with the workbook and confirm filters and dates.
  • Check chart scales and labels for visual exaggeration or accidental ambiguity.
  • Separate what changed from why it changed unless evidence supports causation.
  • Confirm no unrelated or sensitive worksheet data moved into the presentation.

A practical chooser

Start somewhere sensible, then move when the real work gives you evidence.

Start with ChatGPT Work

A deliverable inside an existing ChatGPT Project

Work can use the Project's related chats, files and instructions and then create a finished document, spreadsheet, presentation, report or Site.

Move when: Move to Cowork when a selected local folder or Claude centred file workflow provides a clearer and safer source boundary.

Human check: Review the Project for stale or unrelated context before letting a longer task inherit it.

Start with Claude Cowork

A bounded local file workflow

Cowork is a natural route when the job can be isolated to a dedicated folder and the user wants visibility over which files it can read or change.

Move when: Move to Work when the workflow depends more on cloud Projects, connected app context or OpenAI deliverable tools than on the local folder boundary.

Human check: Use copies, backups and a clean output folder so an unwanted change is visible and recoverable.

Either can fit

A recurring report from cloud sources

Both support scheduled preparation. The deciding factors are approved connectors, source availability, run history and where the reviewer can reliably inspect the result.

Move when: Switch or pause when a required source is unavailable, exceptions are hidden or permission behaviour is hard for the process owner to explain.

Human check: Keep the scheduled action to preparation and make communication or system updates separate approved steps.

Start with ChatGPT Work

Research followed by a polished file

Deep research, Projects and Work form a direct OpenAI route from source plan to cited report and finished deliverable.

Move when: Move to Claude when close reading, nuanced narrative or file centred source work repeatedly needs less correction there.

Human check: Approve the evidence and storyline before file polish makes the conclusion feel more settled than it is.

Start with Claude Cowork

Long source reading followed by document creation

Claude, file creation and Cowork create a coherent route when careful reading of a substantial source pack is the difficult part of the job.

Move when: Move to Work when the workflow needs broader OpenAI tools, mixed modalities or several connected outputs after the reading stage.

Human check: Require source locations for consequential findings and inspect the passages yourself before accepting the document.

Either can fit

Browser or computer action

Both ecosystems can support agentic interaction with digital tools on appropriate surfaces. Direct connectors are generally more precise and easier to govern than screen control.

Move when: Change route when the agent relies on brittle clicking, requests broad permission or cannot provide a clear account of the actions taken.

Human check: Use manual approval for sensitive systems and never let screen control inherit authority to purchase, delete, publish or commit without an explicit boundary.

Either can fit

A low risk first agent workflow

A report, draft, inventory or prepared file waiting for review is a safer learning task than an agent that communicates or changes an external system.

Move when: Add capability only after several runs show stable source handling, visible exceptions and predictable review effort.

Human check: Measure whether the workflow saves time after review, not only whether the agent completed many steps.

Delegate the steps. Keep the purpose, boundary and judgement human.

Agentic work changes the human role. The person should spend less time carrying every mechanical step and more time defining the outcome, governing access, spotting drift, reviewing exceptions and accepting responsibility for the result.

Bound the outcome

An agent needs a deliverable contract: audience, purpose, inputs, constraints, acceptance criteria and what must remain unresolved rather than guessed.

What exactly should exist at the end, and what evidence proves it is ready for use?

Minimise access

Every extra folder, connector, browser session or write permission expands what can be exposed or changed when the agent misunderstands or follows hostile content.

What is the smallest set of sources and actions that can complete this task?

Separate read from write

Reading and preparing work is easier to reverse than sending, deleting, publishing, purchasing or changing a system of record.

Can the workflow stop after producing a reviewed draft instead of taking the consequential action itself?

Design the interruption

A useful agent should know when to ask, stop or surface an exception instead of quietly choosing a path through missing or conflicting information.

Which uncertainty, conflict, permission or consequence must pause the task for a person?

Review at the right level

People cannot realistically validate every low level command in a long run, but they can review the plan, sources, scope changes, exceptions and final artifact.

Which checkpoints catch a wrong direction early and a wrong result before it is used?

Own the recurring task

A schedule without a reviewer, pause condition and source owner becomes unattended debt rather than dependable automation.

Who reviews each run, who maintains the instructions and what change pauses the task automatically?

Protect affected people

An efficient workflow can still be unfair, intrusive or damaging when it moves personal information, drafts communication or makes decisions about people without appropriate context and authority.

Who is affected by this output, what would they reasonably expect and what decision should never be delegated?

What this comparison does not prove

Useful guidance stays honest about access, testing and the conditions that can change the result.

  • ChatGPT Work is rolling out, while Cowork capabilities vary across web, desktop and mobile and some features remain beta or research preview. Confirm access in the actual account and device before promising a workflow.
  • The Human Bit has not run every workflow here head to head. The guidance combines reviewed product documentation, existing practitioner evidence and explicit safety principles rather than claiming a universal agent winner.
  • Local and cloud sessions can behave differently. A workflow that can reach a computer folder on desktop may lose that access remotely, and cloud chat or task history can follow different storage rules.
  • Connected apps, plugins, browser tools and computer use can move information between systems. Product safeguards reduce risk but do not replace permission design, backups, review and organisational policy.
  • Scheduled tasks can continue when the user is absent. Do not schedule sensitive data access or consequential actions until a bounded low risk version has been observed over several runs.
  • Agent output quality can change with model, effort, prompt, source state and product update. Keep the exact instructions, sources and acceptance checks versioned for important recurring workflows.

Continue with the real work

Work playbook

Research a topic with reliable sources

Turn a broad question into a bounded, source-linked briefing you can open up, check and argue with.

Work playbook

Understand a file or spreadsheet

Look inside an unfamiliar document or dataset, surface its quality problems, and check the number by hand before you rely on it.

Work playbook

Create a presentation from source material

Turn the notes, documents and data you already have into an editable first deck, while the argument and the evidence stay in your hands.

Work playbook

Organise recurring work

Keep the repeated context, inputs and review points in one place so a routine gets easier without quietly running itself.

Product comparison

ChatGPT or Claude: start with the work, not the brand

A practical comparison of the two products through real work, including research, writing, files, ongoing projects, finished deliverables and the judgement that still belongs to you.

Model comparison

GPT-5.6 Sol or Claude Opus 5: choose by the job and the review

A grounded comparison of two high capability models for difficult professional work, including effort controls, long context, coding, documents, tool use, cost and the human test that should decide.