Claude Sonnet 4.6 is Anthropic’s most capable Sonnet model yet, with upgrades across coding, long-context reasoning, agent planning, and ‘computer use’. It also introduces a 1M token context window (beta) so teams can work with entire codebases or long documents in one go—while keeping Sonnet pricing unchanged.

AI upgrades are easy to skim and forget. The useful question is: does this release change what your team can do day-to-day?

Anthropic’s Claude Sonnet 4.6 is positioned as a meaningful “capability jump” for the Sonnet line. It brings stronger coding, more reliable agent planning, and much better performance in tasks where the model has to handle messy real-world context — including using software through a graphical interface.

In practical terms, it makes “agentic” work (researching, planning, executing, checking) more achievable at a cost point many organisations can justify.

Updated as of 19/02/2026: Based on Anthropic’s 17 Feb 2026 announcement and the Sonnet 4.6 system card.

What’s new in Claude Sonnet 4.6

1) A 1M token context window (beta)

The headline feature is long context: a 1M token window in beta. For teams, that means you can load:

• large codebases

• lengthy contracts

• multiple research reports

…and ask for a plan, changes, or analysis without chunking everything into dozens of prompts.

Long context only matters if the model can reason across it. Anthropic claims Sonnet 4.6 is materially better at long-horizon planning — the kind of work where the model has to keep objectives, constraints and progress consistent over time.

2) Better ‘computer use’ for software without APIs

A lot of enterprise work happens in systems that are difficult to automate: older tools, bespoke internal apps, and workflows without clean APIs.

Anthropic’s “computer use” approach aims to bridge that gap. Rather than relying on purpose-built connectors, the model can interact with the screen the way a person does: click, type, navigate, and complete steps.

That opens up new possibilities (and new risks), especially for teams trying to standardise operations across multiple tools.

3) Stronger coding consistency at Sonnet pricing

Sonnet 4.6 is described as a full upgrade across coding and instruction-following, with developer testing indicating fewer false-success claims, fewer hallucinations, and less ‘overengineering’ compared with earlier models.

If you’re building internal tools, writing integrations, or supporting software teams, this is the sort of improvement that reduces iteration cycles — which is often where AI time and budget disappear.

4) Product and platform updates that support agents

Alongside the model release, Anthropic highlights platform features that make agents more practical:

• Adaptive thinking / extended thinking controls

• Context compaction (beta) to summarise older context as you approach limits

• Expanded tooling support (including code execution and tool-related capabilities)

These matter because most real enterprise workflows aren’t “one prompt”. They’re sequences: gather context → plan → act → verify → record.

What this means for enterprise teams

The biggest shift is moving from “AI that answers” to “AI that operates” — with appropriate controls.

Sonnet 4.6 is likely to be most valuable for:

• engineering teams working across large repos

• product and ops teams running repeatable, multi-step processes

• knowledge work that depends on reading long documents and extracting the right facts

• agentic workflows that involve planning and action across multiple tools

Practical steps: how to adopt Sonnet 4.6 without creating chaos

If you’re considering Sonnet 4.6 for internal use, treat it as a workflow change, not a feature.

Step 1: Pick one workflow with measurable friction

Good candidates:

• incident postmortems and follow-up task creation

• customer onboarding checklists and validation steps

• contract review support (summaries, clause comparisons, issue spotting)

• codebase changes that span multiple files and require consistency

Define 2–3 metrics: time-to-first-draft, rework loops, cycle time, and error rates.

Step 2: Decide where humans must approve

For anything high-stakes, “human-in-the-loop” needs to be explicit:

• final approvals

• customer-facing outputs

• data changes in core systems

• access, permissions, and compliance decisions

Step 3: Address prompt-injection and tool safety upfront

If you enable browsing or computer use, you need safeguards:

• restrict what the agent is allowed to click or submit

• separate read-only from write actions

• log actions and require confirmations for sensitive steps

Step 4: Start with a small group, then scale with templates

Adoption sticks when best practices are repeatable:

• standard prompts for common tasks

• checklists for review

• naming and documentation standards

How Generation Digital can help

If you’re exploring AI agents and long-context models, we can help you evaluate where they fit — and where they don’t.

• Pilot design: pick the right workflow and define measurable outcomes

• Governance: safe enablement for tool use, data handling and approvals

• Enablement: training, templates and adoption playbooks

Related links:

• Learn about Glean (enterprise search + agents): /glean/

• Explore Asana (work management): /asana/

• Discover Miro (visual collaboration): /miro/

• Learn about Notion (docs + knowledge): /notion/

Summary

Claude Sonnet 4.6 is a notable upgrade: better coding, stronger agents, improved computer use, and a 1M-token context window (beta) that makes ‘whole codebase’ and ‘whole dossier’ work more realistic. The teams that benefit most will treat it as a controlled workflow rollout — measured, governed, and scaled thoughtfully.

Next steps

• Identify one workflow to pilot.

• Set guardrails for tool use and approvals.

• Measure impact, then expand with templates.

FAQs

Q1: What is Claude Sonnet 4.6?
Claude Sonnet 4.6 is Anthropic’s latest Sonnet model, positioned as a major upgrade across coding, long-context reasoning, agent planning, and computer use.

Q2: What does ‘1M token context’ mean in practice?
It means the model can accept very large inputs (in beta), which can include entire codebases, long contracts, or multiple research documents in a single request.

Q3: What is ‘computer use’ and why does it matter?
Computer use refers to the model interacting with software via the screen (clicking and typing) rather than requiring bespoke APIs. It can help automate workflows in tools that are hard to integrate.

Q4: Is Sonnet 4.6 replacing earlier Sonnet models?
Anthropic states Sonnet 4.6 becomes the default model for some Claude plans, while pricing remains consistent with the prior Sonnet tier.

Q5: What’s the safest way to roll this out?
Start with a measurable pilot, define explicit human approvals for high-stakes actions, restrict what tools the agent can access, and scale using templates once results are consistent.