SShortSingh.
Back to feed

Anthropic Launches Claude Fable 5.1 and Mythos 5.1: Same Model, Different Safety Guardrails

0
·1 views

Anthropic released Claude Fable 5.1 and Claude Mythos 5.1 on September 1, 2026, describing them as identical models that differ only in their safety guardrails. Both versions share the same weights, pricing ($10/$50), 1M token context window, and June 2026 knowledge cutoff. Fable 5.1 is available to all customers, while Mythos 5.1 is restricted to approved organizations under the Project Glasswing initiative, accessible via Cybersecurity or Life Sciences verification programs. The key distinction lies in safety classifiers: Mythos 5.1 allows approved users to explore exploitation paths for defensive research, whereas Fable 5.1 can identify vulnerabilities but not develop exploits. A published benchmark gap — 60.9% versus 55.8% on Terminal-Bench 4.0 — suggests a measurable performance cost associated with the stricter guardrails in Fable 5.1.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

Developer breaks down which AI tools speed up WordPress builds and where humans must stay in control

A WordPress developer using a Sage/Roots theme stack has detailed how AI tools like Cursor, ChatGPT, Claude, and n8n fit into a custom build workflow. The setup accelerates repetitive tasks such as scaffolding Blade templates, writing boilerplate PHP, and configuring GitHub Actions pipelines. However, the developer emphasizes that speed gains are limited to predictable, verifiable patterns — not creative or architectural decisions. Judgment calls around plugin selection, accessibility, and deployment remain entirely human responsibilities. The developer's rule is clear: if every line of generated code cannot be explained at handoff, it does not ship.

0
ProgrammingDEV Community ·

How to Build a JavaScript Event Calendar That Handles Thousands of Events Efficiently

Developing a high-performance JavaScript event calendar becomes complex when dealing with thousands of events, overlapping time ranges, and continuous navigation. A key architectural principle is separating the storage of a large event dataset from rendering only the currently visible portion, keeping DOM size bounded regardless of total data size. Continuous navigation should recycle off-screen calendar segments rather than appending indefinitely, maintaining only previous, current, and next views in memory. True virtualization goes beyond hiding elements with CSS and must limit mounted segments, rendered event nodes, listeners, and cached state. Efficient event lookup also requires indexed data structures so queries like 'which events fall in this date range' avoid full-array scans during every navigation or view change.

0
ProgrammingDEV Community ·

How a Voice AI Call Transfer Shipped Broken and Logged Success for Every Failed Call

A development team building AI voice agents discovered their first call-transfer implementation never delivered a single call to human agents, despite internal logs consistently recording the outcome as successful. The flawed approach used a SIP REFER method, which received a 200 OK acknowledgment from carrier Telnyx but silently dropped callers without ever ringing the destination. Investigation revealed REFER-based transfers only work on inbound calls to a registered number with a specific Diversion header — a configuration incompatible with the team's outbound call setup and unsupported by LiveKit's transfer API. The team rebuilt the feature using a bridged second call dialled directly into the same conversation, with a 45-second answer timeout and explicit agent silencing to prevent the AI from continuing to speak or transcribe after handover. The new system trades lower per-minute costs for reliability, and correctly handles edge cases such as unanswered transfers, non-phone channels, and unauthorized destination numbers.

0
ProgrammingDEV Community ·

Semantic Memory Stores Offer a Scalable Fix for AI Agent Skill Decay

Developers storing AI agent skills as flat files face a growing maintenance problem: skills become outdated, conflict with each other, or silently rot without any system to flag the issue. Common workarounds — editing files in place, creating versioned duplicates, or ignoring stale content — each introduce their own risks, from lost history to dead code. A proposed alternative involves storing each skill as a tagged document in a semantic memory store, where metadata such as topic, type, and date enables precise retrieval and automatic versioning. When a skill needs updating, a new document is added rather than the old one edited, preserving full audit history and enabling easy rollback. This approach also supports multi-agent setups through isolated workspaces and a shared layer for cross-agent knowledge, making long-term skill maintenance significantly more manageable.