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OpenWiki hands-on: building repository memory for coding agents

heise online tested LangChain's CLI tool OpenWiki, which analyzes a codebase and generates a linked local Markdown knowledge base, then updates it based on new diffs and commits in Git history, and makes the content retrievable through agent prompts and MCP tools. The article notes that AGENTS.md or CLAUDE.md are suitable for short rules such as install commands, tests, style conventions, and security boundaries, and in a monorepo can also be nested in subdirectory files, but they struggle to serve as a complete knowledge model for large, rapidly changing repositories.

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Cerebras summarizes five orchestration patterns for multi-agent workflows

Cerebras published a blog post summarizing five patterns for building multi-agent workflows: parallel generation followed by human selection, swarm parallelism, staged parallelism, sequential handoff, and separation of building from verification. Using Codex with Figma MCP to replicate a website as an example, the article states that a single agent averaged 36.5 minutes per run, 12 human interventions, and a 100% failure rate, while the multi-agent setup took 5.2 minutes, required 2 interventions, and succeeded on the first attempt; in internal testing, the sequential loop reduced human interventions by 84.3%. The author argues that multi-agent setups expand the effective context window from about 200K to over 25M, and notes that Codex Spark's speed of about 1,200 tokens/second makes parallel and verification steps feasible.

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Fireworks Evaluates DeepSeek V4 Pro Against Fable 5 and Kimi K3

Fireworks tested DeepSeek V4 Pro 0813 on four benchmarks: SWE-Bench Verified, LiveCodeBench v6, Aider Polyglot, and Terminal-Bench 2.1. It scored 95.2% on SWE-Bench Verified, higher than Kimi K3's 92.6% and Fable 5's 85.4%, and 92.0% on LiveCodeBench v6. On cost, DeepSeek V4 Pro spent $0.309 per task solved on SWE-bench, versus $0.808 for Fable 5; on LiveCodeBench the figures were $0.040 and $0.225, respectively. Its weakness is the multilingual breadth of Aider Polyglot, where it scored only 48.9% on Java, versus 74.5% for Fable 5. After oracle routing on a combined set of 409 tasks, accuracy was 92.4%, higher than the 86.6% achieved by Fable 5 alone, at a cost of $0.279 versus $4.510 per task, with 86.3% of tasks routed to V4 Pro.