[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fr_PuN8D0an_1kQEVoXJ1dwp_QBzDpjv48RCQRtQ-kho":3},{"locale":4,"topic":5,"relatedTrends":50},"en",{"topic":6,"slug":7,"canonicalSlug":7,"topicAliases":8,"nicheKey":9,"nicheName":10,"nicheNameEn":10,"nicheIcon":11,"country":12,"countries":13,"agentKey":14,"score":15,"type":16,"isFresh":17,"isPublic":17,"detectedAt":18,"sources":19,"evidence":47},"Perplexity's Search as Code: sandboxed Python search agents","perplexity-s-search-as-code-sandboxed-python-search-agents",[],"ai-engineering","AI Engineering & LLM Ops","⚙️","ES",[12],"ai-engineering-ES",99,"spiking",false,"2026-06-09T02:56:50.824Z",[20,26,32,37,42],{"title":21,"url":22,"domain":23,"snippet":24,"content":25},"Perplexity Search as Code: Agents Write Search — 85% Fewer Tokens","https:\u002F\u002Fwww.abhs.in\u002Fblog\u002Fperplexity-search-as-code-85-percent-tokens-agent-api-june-2026","abhs.in","Perplexity replaced fixed search API calls with sandboxed Python pipelines that agents write themselves, cutting tokens from 288K to 43K on a CVE-hunt benchmark.","Abhishek Gautam](https:\u002F\u002Fwww.abhs.in\u002Fwho-is-abhishek-gautam)·June 8, 2026·11 min read\n\n!\n\nQuick summary\n\nPerplexity replaced fixed search API calls with sandboxed Python pipelines agents write themselves — 288K tokens down to 43K on a CVE hunt benchmark.\n\nRead next\n\n*   \n*   \n\n**Perplexity** launched **Search as Code (SaC)** in early **June 2026** — an architecture where **AI agents write Python search pipelines** in a **sandbox** instead of chaining **fixed API tool calls**. On a **200 high-severity CVE** case study, Perplexity reports **100% accuracy** at **42,900 tokens** vs **288,700 tokens** for its old pipeline — an **~85%** reducti\n\n[Content truncated...]",{"title":27,"url":28,"domain":29,"snippet":30,"content":31},"Perplexity's \"Search as Code\" lets AI models write their own search pipelines instead of calling fixed APIs","https:\u002F\u002Fthe-decoder.com\u002Fperplexitys-search-as-code-lets-ai-models-write-their-own-search-pipelines-instead-of-calling-fixed-apis\u002F","the-decoder.com","Perplexity's new \"Search as Code\" architecture dumps rigid search APIs and lets AI models write their own search routines in Python. By letting the agent...",null,{"title":33,"url":34,"domain":35,"snippet":36,"content":31},"Perplexity Lets AI Agents Write Their Own Search Code","https:\u002F\u002Fwinbuzzer.com\u002F2026\u002F06\u002F07\u002Fperplexity-lets-ai-agents-write-their-own-search-code-xcxwbn\u002F","winbuzzer.com","Perplexity's Search as Code lets AI agents generate Python search workflows, but claimed token savings and benchmark gains still need outside validation.",{"title":38,"url":39,"domain":40,"snippet":41,"content":31},"Perplexity Search as Code Lets AI Models Write Their Own Search Pipelines","https:\u002F\u002Fopentools.ai\u002Fnews\u002Fperplexity-search-as-code-ai-models-write-search-pipelines","opentools.ai","Perplexity Search as Code lets AI models write custom search pipelines in Python, cutting token usage by 85 percent and outperforming competitors on...",{"title":43,"url":44,"domain":45,"snippet":46,"content":31},"Perplexity release \"Search as Code\" architecture, lets AI models write their own search pipelines instead of calling fixed API","https:\u002F\u002Fvoice.lapaas.com\u002Fperplexity-release-search-as-code-architecture-lets-ai-models-write-their-own-search-pipelines-instead-of-calling-fixed-api\u002F","voice.lapaas.com","Perplexity has officially launched Search as Code (SaC), a paradigm shift in how artificial intelligence models interact with the web.",{"mentionsLast7Days":48,"mentionsLast30Days":48,"firstSeen":18,"lastSeen":18,"relatedEntities":49},5,[22,28,34,39,44],[51,55,58,61,65,69],{"topic":52,"slug":53,"score":54,"type":16,"country":12,"nicheIcon":11},"Top AI engineering intelligence platforms for measuring AI outcomes","top-ai-engineering-intelligence-platforms-for-measuring-ai-outcomes",100,{"topic":56,"slug":57,"score":15,"type":16,"country":12,"nicheIcon":11},"Essential Python concepts for production-grade AI engineering","essential-python-concepts-for-production-grade-ai-engineering",{"topic":59,"slug":60,"score":15,"type":16,"country":12,"nicheIcon":11},"Six-layer AI agents stack between LLMs and production agents","six-layer-ai-agents-stack-between-llms-and-production-agents",{"topic":62,"slug":63,"score":64,"type":16,"country":12,"nicheIcon":11},"NEC deploying Claude to 30,000 employees and co-developing AI products","nec-deploying-claude-to-30-000-employees-and-co-developing-ai-products",98,{"topic":66,"slug":67,"score":64,"type":68,"country":12,"nicheIcon":11},"Gartner's 10 best practices to optimize Generative and Agentic AI costs","gartner-s-10-best-practices-to-optimize-generative-and-agentic-ai-costs","emerging",{"topic":70,"slug":71,"score":72,"type":68,"country":12,"nicheIcon":11},"General-purpose LLMs outperform specialized clinical AI tools on medical benchmarks","general-purpose-llms-outperform-specialized-clinical-ai-tools-on-medical-benchmarks",95]