{"id":1290,"date":"2026-04-03T07:26:03","date_gmt":"2026-04-03T07:26:03","guid":{"rendered":"https:\/\/bbotech.vn\/website-humans-vs-agents\/"},"modified":"2026-04-03T07:28:33","modified_gmt":"2026-04-03T07:28:33","slug":"website-humans-vs-agents","status":"publish","type":"post","link":"https:\/\/bbotech.vn\/vi\/website-humans-vs-agents\/","title":{"rendered":"Website cho Ng\u01b0\u1eddi v\u00e0 Website cho Agent: Hai Thi\u1ebft K\u1ebf Song Song M\u00e0 Engineering Team Ph\u1ea3i Master"},"content":{"rendered":"

Website c\u1ee7a b\u1ea1n \u0111ang ph\u1ee5c v\u1ee5 ai \u2014 ng\u01b0\u1eddi d\u00f9ng hay AI agent?<\/h2>\n

N\u0103m 2025, m\u1ed9t nghi\u00ean c\u1ee9u tr\u00ean 3.000 website ph\u00e1t hi\u1ec7n ra \u0111i\u1ec1u \u0111\u00e1ng suy ngh\u0129: 63% trong s\u1ed1 \u0111\u00f3 \u0111\u00e3 nh\u1eadn l\u01b0\u1ee3t truy c\u1eadp t\u1eeb AI agent<\/strong> \u2014 kh\u00f4ng ph\u1ea3i t\u1eeb ng\u01b0\u1eddi d\u00f9ng ng\u1ed3i tr\u01b0\u1edbc m\u00e0n h\u00ecnh. Nh\u01b0ng c\u0169ng trong c\u00f9ng th\u1eddi \u0111i\u1ec3m \u0111\u00f3, ch\u1ec9 24% developer thi\u1ebft k\u1ebf API c\u00f3 t\u00ednh \u0111\u1ebfn AI agent<\/strong> nh\u01b0 m\u1ed9t lo\u1ea1i “ng\u01b0\u1eddi d\u00f9ng” h\u1ee3p l\u1ec7. (Ngu\u1ed3n: Postman State of the API Report 2025)<\/em><\/p>\n

Kho\u1ea3ng c\u00e1ch 39 \u0111i\u1ec3m ph\u1ea7n tr\u0103m \u0111\u00f3 l\u00e0 v\u1ea5n \u0111\u1ec1 th\u1ef1c s\u1ef1. V\u00e0 n\u00f3 \u0111ang t\u0103ng d\u1ea7n.<\/p>\n

N\u1ebfu b\u1ea1n l\u00e0 CTO ho\u1eb7c Engineering Lead \u0111ang l\u00ean k\u1ebf ho\u1ea1ch cho s\u1ea3n ph\u1ea9m trong 12-18 th\u00e1ng t\u1edbi, c\u00e2u h\u1ecfi “website c\u1ee7a m\u00ecnh c\u1ea7n serve ai?” kh\u00f4ng c\u00f2n c\u00f3 m\u1ed9t c\u00e2u tr\u1ea3 l\u1eddi duy nh\u1ea5t. Ng\u01b0\u1eddi d\u00f9ng v\u00e0 AI agent \u0111\u1ecdc, di\u1ec5n gi\u1ea3i, v\u00e0 t\u01b0\u01a1ng t\u00e1c v\u1edbi website theo hai c\u00e1ch ho\u00e0n to\u00e0n kh\u00e1c nhau \u2014 v\u00e0 engineering team c\u1ee7a b\u1ea1n ph\u1ea3i \u0111\u00e1p \u1ee9ng c\u1ea3 hai.<\/p>\n

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Ng\u01b0\u1eddi d\u00f9ng v\u00e0 AI agent “\u0111\u1ecdc” website theo hai ng\u00f4n ng\u1eef kh\u00e1c nhau<\/h2>\n

\u0110\u00e2y l\u00e0 \u0111i\u1ec3m xu\u1ea5t ph\u00e1t quan tr\u1ecdng nh\u1ea5t: con ng\u01b0\u1eddi v\u00e0 AI agent x\u1eed l\u00fd th\u00f4ng tin tr\u00ean web theo hai c\u00e1ch kh\u00f4ng t\u01b0\u01a1ng th\u00edch v\u1edbi nhau.<\/p>\n

Khi m\u1ed9t ng\u01b0\u1eddi d\u00f9ng truy c\u1eadp trang pricing c\u1ee7a b\u1ea1n, h\u1ecd nh\u00ecn v\u00e0o layout t\u1ed5ng th\u1ec3, so s\u00e1nh b\u1ea3ng gi\u00e1 b\u1eb1ng m\u1eaft, click v\u00e0o tooltip \u0111\u1ec3 hi\u1ec3u th\u00eam, r\u1ed3i \u0111\u1ecdc testimonial \u1edf cu\u1ed1i trang \u0111\u1ec3 c\u1ee7ng c\u1ed1 quy\u1ebft \u0111\u1ecbnh. Tr\u1ea3i nghi\u1ec7m n\u00e0y \u0111\u01b0\u1ee3c d\u1eabn d\u1eaft b\u1edfi visual hierarchy, UX copy, v\u00e0 c\u1ea3m gi\u00e1c t\u1ed5ng th\u1ec3 c\u1ee7a trang.<\/p>\n

Khi m\u1ed9t AI agent nh\u01b0 OpenAI Operator ho\u1eb7c Perplexity truy c\u1eadp c\u00f9ng trang \u0111\u00f3, n\u00f3 kh\u00f4ng “nh\u00ecn” g\u00ec c\u1ea3. N\u00f3 query structured data, parse HTML \u0111\u1ec3 t\u00ecm semantic tags, g\u1ecdi API n\u1ebfu c\u00f3, v\u00e0 \u0111\u01b0a ra quy\u1ebft \u0111\u1ecbnh d\u1ef1a tr\u00ean d\u1eef li\u1ec7u c\u00f3 th\u1ec3 \u0111\u1ecdc \u0111\u01b0\u1ee3c theo m\u00e1y \u2014 kh\u00f4ng ph\u1ea3i d\u1ef1a tr\u00ean thi\u1ebft k\u1ebf b\u1eaft m\u1eaft c\u1ee7a b\u1ea1n.<\/p>\n

AI agent kh\u00f4ng duy\u1ec7t web. Ch\u00fang query d\u1eef li\u1ec7u c\u00f3 c\u1ea5u tr\u00fac, semantic layer, v\u00e0 API \u0111\u1ec3 t\u00ecm c\u00e2u tr\u1ea3 l\u1eddi nhanh nh\u1ea5t v\u00e0 \u0111\u00e1ng tin c\u1eady nh\u1ea5t.<\/p><\/blockquote>\n

Jakob Nielsen \u2014 ng\u01b0\u1eddi \u0111\u1eb7t n\u1ec1n m\u00f3ng cho ng\u00e0nh UX hi\u1ec7n \u0111\u1ea1i \u2014 \u0111\u00e3 g\u1ecdi s\u1ef1 d\u1ecbch chuy\u1ec3n n\u00e0y l\u00e0 th\u1eddi \u0111i\u1ec3m “Goodbye UI Design”. Lu\u1eadn \u0111i\u1ec3m c\u1ee7a \u00f4ng: khi ng\u01b0\u1eddi d\u00f9ng kh\u00f4ng c\u00f2n tr\u1ef1c ti\u1ebfp t\u01b0\u01a1ng t\u00e1c v\u1edbi giao di\u1ec7n m\u00e0 thay v\u00e0o \u0111\u00f3 \u1ee7y quy\u1ec1n cho AI agent l\u00e0m thay, design target ph\u1ea3i thay \u0111\u1ed5i \u2014 t\u1eeb page flows v\u00e0 pixel decisions sang outcomes, policies, v\u00e0 intent orchestration<\/strong>.<\/p>\n

\u0110\u00e2y kh\u00f4ng ph\u1ea3i t\u00edn hi\u1ec7u \u0111\u1ec3 b\u1ecf qua UX. \u0110\u00e2y l\u00e0 t\u00edn hi\u1ec7u \u0111\u1ec3 thi\u1ebft k\u1ebf hai l\u1edbp song song.<\/p>\n

Ba s\u1ef1 kh\u00e1c bi\u1ec7t k\u1ef9 thu\u1eadt m\u00e0 engineering team c\u1ea7n n\u1eafm r\u00f5<\/h2>\n

1. N\u1ed9i dung vs. D\u1eef li\u1ec7u c\u00f3 c\u1ea5u tr\u00fac<\/h3>\n

Website cho ng\u01b0\u1eddi d\u00f9ng t\u1eadp trung v\u00e0o n\u1ed9i dung \u2014 copywriting, visual, narrative flow. Website cho agent t\u1eadp trung v\u00e0o structured data<\/strong>: Schema.org markup, JSON-LD, OpenGraph tags, v\u00e0 ng\u00e0y c\u00e0ng quan tr\u1ecdng h\u01a1n l\u00e0 llms.txt<\/code> \u2014 file h\u01b0\u1edbng d\u1eabn cho AI crawler v\u1ec1 c\u00e1ch truy c\u1eadp v\u00e0 \u01b0u ti\u00ean n\u1ed9i dung tr\u00ean site c\u1ee7a b\u1ea1n.<\/p>\n

S\u1ef1 kh\u00e1c bi\u1ec7t th\u1ef1c t\u1ebf: m\u1ed9t trang s\u1ea3n ph\u1ea9m \u0111\u01b0\u1ee3c vi\u1ebft t\u1ed1t cho ng\u01b0\u1eddi d\u00f9ng c\u00f3 th\u1ec3 ho\u00e0n to\u00e0n “v\u00f4 h\u00ecnh” v\u1edbi AI agent n\u1ebfu kh\u00f4ng c\u00f3 structured data \u0111\u00fang format. Agent s\u1ebd kh\u00f4ng infer \u00fd \u0111\u1ecbnh t\u1eeb copywriting \u2014 n\u00f3 c\u1ea7n d\u1eef li\u1ec7u r\u00f5 r\u00e0ng, c\u00f3 th\u1ec3 \u0111\u1ecdc \u0111\u01b0\u1ee3c theo m\u00e1y.<\/p>\n

2. Navigation vs. API endpoint<\/h3>\n

Ng\u01b0\u1eddi d\u00f9ng \u0111i\u1ec1u h\u01b0\u1edbng qua menu, breadcrumb, internal link. AI agent b\u1ecf qua to\u00e0n b\u1ed9 l\u1edbp navigation \u0111\u00f3 v\u00e0 t\u00ecm c\u00e1ch ng\u1eafn nh\u1ea5t \u0111\u1ec3 l\u1ea5y d\u1eef li\u1ec7u \u2014 th\u01b0\u1eddng l\u00e0 th\u00f4ng qua REST API, GraphQL, ho\u1eb7c sitemap.<\/p>\n

Postman 2025 ghi nh\u1eadn: AI agent \u0111ang tr\u1edf th\u00e0nh nh\u00f3m ti\u00eau th\u1ee5 API t\u0103ng tr\u01b0\u1edfng nhanh nh\u1ea5t<\/strong>. Nh\u01b0ng agent c\u1ea7n API \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf theo chu\u1ea9n kh\u00e1c \u2014 c\u1ee5 th\u1ec3 h\u01a1n, \u00edt ambiguity h\u01a1n, error handling r\u00f5 r\u00e0ng h\u01a1n so v\u1edbi API cho developer truy\u1ec1n th\u1ed1ng. Kh\u00f4ng gi\u1ed1ng human developer c\u00f3 th\u1ec3 \u0111\u1ecdc docs kh\u00f4ng \u0111\u1ea7y \u0111\u1ee7 v\u00e0 t\u1ef1 suy lu\u1eadn, agent c\u1ea7n machine-readable schema (OpenAPI 3.0+) v\u00e0 predictable response structure.<\/p>\n

3. Trust signal cho ng\u01b0\u1eddi vs. Trust signal cho m\u00e1y<\/h3>\n

Ng\u01b0\u1eddi d\u00f9ng \u0111\u00e1nh gi\u00e1 trust qua testimonial, badge, h\u00ecnh \u1ea3nh \u0111\u1ed9i ng\u0169, t\u1ed1c \u0111\u1ed9 load, v\u00e0 thi\u1ebft k\u1ebf t\u1ed5ng th\u1ec3. AI agent \u0111\u00e1nh gi\u00e1 trust qua completeness c\u1ee7a structured data, consistency c\u1ee7a th\u00f4ng tin qua c\u00e1c endpoint, freshness c\u1ee7a content, v\u00e0 whether domain c\u00f3 authority signal theo c\u00e1ch m\u00e1y c\u00f3 th\u1ec3 verify.<\/p>\n

Gartner d\u1ef1 b\u00e1o \u0111\u1ebfn n\u0103m 2026, 20% customer interaction s\u1ebd \u0111\u01b0\u1ee3c x\u1eed l\u00fd b\u1edfi AI agent thay v\u00ec con ng\u01b0\u1eddi<\/strong>. V\u1edbi t\u1ef7 l\u1ec7 n\u00e0y, trust signal cho m\u00e1y s\u1ebd quan tr\u1ecdng kh\u00f4ng k\u00e9m \u2014 v\u00e0 trong m\u1ed9t s\u1ed1 case c\u00f2n quan tr\u1ecdng h\u01a1n \u2014 trust signal cho ng\u01b0\u1eddi d\u00f9ng.<\/p>\n

T\u1ea1i sao vi\u1ec7c t\u1ed1i \u01b0u ch\u1ec9 cho m\u1ed9t ph\u00eda l\u00e0 r\u1ee7i ro chi\u1ebfn l\u01b0\u1ee3c<\/h2>\n

C\u00f3 m\u1ed9t nh\u00f3m engineering team \u0111ang t\u1ed1i \u01b0u website r\u1ea5t t\u1ed1t cho ng\u01b0\u1eddi d\u00f9ng nh\u01b0ng ho\u00e0n to\u00e0n b\u1ecf qua agent-readiness. Nh\u00f3m n\u00e0y s\u1ebd g\u1eb7p v\u1ea5n \u0111\u1ec1 khi AI-powered buyer journey tr\u1edf th\u00e0nh chu\u1ea9n m\u1ef1c \u2014 ng\u01b0\u1eddi d\u00f9ng h\u1ecfi ChatGPT ho\u1eb7c Perplexity v\u1ec1 vendor ph\u00f9 h\u1ee3p, v\u00e0 s\u1ea3n ph\u1ea9m c\u1ee7a h\u1ecd kh\u00f4ng xu\u1ea5t hi\u1ec7n trong k\u1ebft qu\u1ea3 v\u00ec kh\u00f4ng c\u00f3 structured data \u0111\u1ec3 AI parse.<\/p>\n

Nh\u00f3m ng\u01b0\u1ee3c l\u1ea1i \u2014 t\u1eadp trung v\u00e0o API v\u00e0 machine-readability nh\u01b0ng b\u1ecf qua human UX \u2014 c\u0169ng kh\u00f4ng \u1ed5n. Hi\u1ec7n t\u1ea1i, l\u01b0\u1ee3ng traffic t\u1eeb AI agent ch\u1ec9 chi\u1ebfm 0.2% trung b\u00ecnh tr\u00ean m\u1ed7i website<\/strong> (d\u1eef li\u1ec7u th\u00e1ng 2\/2025)<\/em>. Ph\u1ea7n l\u1edbn buyer journey B2B v\u1eabn c\u00f3 \u0111i\u1ec3m ti\u1ebfp x\u00fac tr\u1ef1c ti\u1ebfp v\u1edbi ng\u01b0\u1eddi d\u00f9ng th\u1eadt. B\u1ecf qua UX l\u00e0 sai l\u1ea7m v\u1ec1 th\u1ee9 t\u1ef1 \u01b0u ti\u00ean.<\/p>\n

V\u1ea5n \u0111\u1ec1 th\u1ef1c s\u1ef1 l\u00e0 hai lo\u1ea1i website n\u00e0y \u0111\u00f2i h\u1ecfi mindset thi\u1ebft k\u1ebf v\u00e0 ki\u1ec3m th\u1eed kh\u00e1c nhau, v\u00e0 h\u1ea7u h\u1ebft engineering team ch\u01b0a build process \u0111\u1ec3 \u0111\u1ea3m b\u1ea3o ch\u1ea5t l\u01b0\u1ee3ng cho c\u1ea3 hai.<\/p>\n

Framework quy\u1ebft \u0111\u1ecbnh: B\u1ea1n n\u00ean \u0111\u1ea7u t\u01b0 v\u00e0o \u0111\u00e2u v\u00e0 theo th\u1ee9 t\u1ef1 n\u00e0o?<\/h2>\n

Kh\u00f4ng c\u00f3 c\u00e2u tr\u1ea3 l\u1eddi “t\u00f9y” \u1edf \u0111\u00e2y. D\u01b0\u1edbi \u0111\u00e2y l\u00e0 decision framework d\u1ef1a tr\u00ean giai \u0111o\u1ea1n ph\u00e1t tri\u1ec3n c\u1ee7a s\u1ea3n ph\u1ea9m:<\/p>\n

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  • Pre-PMF (d\u01b0\u1edbi 1,000 user):<\/strong> 90% effort v\u00e0o human UX. Agent-readiness kh\u00f4ng ph\u1ea3i \u01b0u ti\u00ean khi b\u1ea1n ch\u01b0a validate product-market fit v\u1edbi ng\u01b0\u1eddi d\u00f9ng th\u1eadt. R\u1ee7i ro: vi\u1ebft code qu\u00e1 s\u1edbm cho m\u1ed9t audience ch\u01b0a c\u00f3.<\/li>\n
  • Post-PMF, \u0111ang scale (1,000 – 50,000 user):<\/strong> B\u1eaft \u0111\u1ea7u invest v\u00e0o structured data (Schema.org, JSON-LD), public API documentation chu\u1ea9n OpenAPI 3.0+, v\u00e0 llms.txt<\/code>. Budget g\u1ee3i \u00fd: 70% human UX, 30% machine-readability.<\/li>\n
  • Scale-up v\u1edbi enterprise buyer:<\/strong> Agent-readiness tr\u1edf th\u00e0nh competitive moat. Enterprise buyer ng\u00e0y c\u00e0ng d\u00f9ng AI tool \u0111\u1ec3 evaluate vendor \u2014 n\u1ebfu s\u1ea3n ph\u1ea9m c\u1ee7a b\u1ea1n kh\u00f4ng xu\u1ea5t hi\u1ec7n trong AI-generated shortlist, b\u1ea1n kh\u00f4ng t\u1ed3n t\u1ea1i trong deal. \u1ede giai \u0111o\u1ea1n n\u00e0y: 50\/50.<\/li>\n
  • API-first product ho\u1eb7c B2D (developer tool):<\/strong> \u0110\u1ea7u t\u01b0 60-70% v\u00e0o machine-readability ngay t\u1eeb \u0111\u1ea7u. \u0110\u00e2y l\u00e0 audience m\u00e0 agent s\u1ebd thay th\u1ebf workflow nhanh nh\u1ea5t.<\/li>\n<\/ul>\n

    Ph\u1ea3n bi\u1ec7n ph\u1ed5 bi\u1ebfn \u2014 v\u00e0 t\u1ea1i sao c\u1ea7n nh\u00ecn l\u1ea1i<\/h2>\n

    “AI agent traffic hi\u1ec7n t\u1ea1i qu\u00e1 nh\u1ecf \u0111\u1ec3 \u0111\u00e1ng \u0111\u1ea7u t\u01b0.”<\/strong><\/p>\n

    \u0110\u00fang v\u1ec1 con s\u1ed1 hi\u1ec7n t\u1ea1i (0.2%). Nh\u01b0ng \u0111\u00e2y l\u00e0 b\u1eaby c\u1ee7a lagging indicator. Web traffic t\u1eeb mobile c\u0169ng r\u1ea5t nh\u1ecf n\u0103m 2008 \u2014 v\u00e0 team n\u00e0o kh\u00f4ng chu\u1ea9n b\u1ecb tr\u01b0\u1edbc \u0111\u1ec1u ph\u1ea3i l\u00e0m l\u1ea1i to\u00e0n b\u1ed9 trong t\u00ecnh tr\u1ea1ng g\u1ea5p. Agent adoption \u0111ang \u0111i theo trajectory t\u01b0\u01a1ng t\u1ef1, v\u1edbi v\u1eadn t\u1ed1c nhanh h\u01a1n.<\/p>\n

    “Structured data v\u00e0 API \u0111\u00e3 c\u00f3 r\u1ed3i, c\u1ea7n g\u00ec l\u00e0m th\u00eam?”<\/strong><\/p>\n

    C\u00f3 API kh\u00f4ng c\u00f3 ngh\u0129a l\u00e0 API \u0111\u00f3 agent-ready. Agent c\u1ea7n predictable error handling, schema \u0111\u1ea7y \u0111\u1ee7, v\u00e0 kh\u00f4ng c\u00f3 ambiguity trong response. H\u1ea7u h\u1ebft API hi\u1ec7n t\u1ea1i \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf cho developer \u0111\u1ecdc docs v\u00e0 adapt \u2014 kh\u00f4ng ph\u1ea3i cho agent ho\u1ea1t \u0111\u1ed9ng fully autonomous. \u0110\u00e2y l\u00e0 gap c\u1ea7n \u0111\u00e1nh gi\u00e1 ri\u00eang.<\/p>\n

    Gi\u1edbi h\u1ea1n c\u1ee7a framework tr\u00ean:<\/strong> N\u00f3 kh\u00f4ng \u00e1p d\u1ee5ng cho safety-critical system (fintech infrastructure, healthcare platform) n\u01a1i AI agent kh\u00f4ng \u0111\u01b0\u1ee3c ph\u00e9p ra quy\u1ebft \u0111\u1ecbnh t\u1ef1 \u0111\u1ed9ng. Trong c\u00e1c context \u0111\u00f3, human UX v\u00e0 human oversight v\u1eabn l\u00e0 \u01b0u ti\u00ean tuy\u1ec7t \u0111\u1ed1i.<\/p>\n

    H\u00e0m \u00fd th\u1ef1c t\u1ebf cho engineering team<\/h2>\n

    N\u1ebfu b\u1ea1n \u0111ang \u1edf giai \u0111o\u1ea1n post-PMF v\u00e0 ch\u01b0a l\u00e0m g\u00ec v\u1edbi agent-readiness, \u0111\u00e2y l\u00e0 3 vi\u1ec7c c\u00f3 th\u1ec3 b\u1eaft \u0111\u1ea7u trong sprint ti\u1ebfp theo:<\/p>\n

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    1. Audit structured data hi\u1ec7n t\u1ea1i:<\/strong> D\u00f9ng Google Rich Results Test v\u00e0 Schema Validator \u0111\u1ec3 xem s\u1ea3n ph\u1ea9m c\u1ee7a b\u1ea1n \u0111ang expose g\u00ec cho AI crawler. Ph\u1ea7n l\u1edbn team s\u1ebd ng\u1ea1c nhi\u00ean v\u00ec kho\u1ea3ng c\u00e1ch gi\u1eefa nh\u1eefng g\u00ec h\u1ecd t\u01b0\u1edfng v\u00e0 th\u1ef1c t\u1ebf.<\/li>\n
    2. T\u1ea1o llms.txt c\u01a1 b\u1ea3n:<\/strong> File n\u00e0y h\u01b0\u1edbng d\u1eabn AI crawler v\u1ec1 c\u1ea5u tr\u00fac site v\u00e0 n\u1ed9i dung \u01b0u ti\u00ean. Hi\u1ec7n t\u1ea1i ch\u01b0a ph\u1ea3i t\u1ea5t c\u1ea3 LLM crawler \u0111\u1ecdc file n\u00e0y, nh\u01b0ng adoption \u0111ang t\u0103ng v\u00e0 chi ph\u00ed setup th\u1ea5p.<\/li>\n
    3. Review API documentation theo chu\u1ea9n OpenAPI 3.0+:<\/strong> \u0110\u1eb7t c\u00e2u h\u1ecfi: n\u1ebfu m\u1ed9t AI agent c\u1ea7n th\u1ef1c hi\u1ec7n m\u1ed9t task th\u00f4ng qua API c\u1ee7a b\u1ea1n m\u00e0 kh\u00f4ng c\u00f3 human intervention, n\u00f3 c\u00f3 th\u1ec3 kh\u00f4ng? T\u00ecm ch\u1ed7 n\u00e0o trong docs c\u1ea7n “common sense” \u0111\u1ec3 hi\u1ec3u \u2014 \u0111\u00f3 l\u00e0 nh\u1eefng ch\u1ed7 agent s\u1ebd fail.<\/li>\n<\/ol>\n

      Quan tr\u1ecdng h\u01a1n: nh\u1eefng thay \u0111\u1ed5i n\u00e0y c\u1ea7n \u0111\u01b0\u1ee3c ki\u1ec3m th\u1eed. Structured data sai c\u00f2n t\u1ec7 h\u01a1n kh\u00f4ng c\u00f3 \u2014 n\u00f3 c\u00f3 th\u1ec3 khi\u1ebfn AI tr\u00edch d\u1eabn th\u00f4ng tin sai v\u1ec1 s\u1ea3n ph\u1ea9m c\u1ee7a b\u1ea1n. Schema markup c\u1ea7n validation, API contract c\u1ea7n contract testing, v\u00e0 behavior khi agent truy c\u1eadp c\u1ea7n \u0111\u01b0\u1ee3c test v\u1edbi agent simulator ho\u1eb7c headless browser tr\u01b0\u1edbc khi release.<\/p>\n

      Ch\u00fang t\u00f4i ngh\u0129 g\u00ec v\u1ec1 h\u01b0\u1edbng \u0111i c\u1ee7a ng\u00e0nh<\/h2>\n

      Ranh gi\u1edbi gi\u1eefa “website cho ng\u01b0\u1eddi” v\u00e0 “website cho agent” s\u1ebd kh\u00f4ng bi\u1ebfn m\u1ea5t \u2014 n\u00f3 s\u1ebd tr\u1edf n\u00ean r\u00f5 h\u01a1n, kh\u00f4ng m\u1edd h\u01a1n. Trong 2-3 n\u0103m t\u1edbi, s\u1ea3n ph\u1ea9m t\u1ed1t nh\u1ea5t kh\u00f4ng ph\u1ea3i s\u1ea3n ph\u1ea9m ch\u1ecdn m\u1ed9t trong hai, m\u00e0 l\u00e0 s\u1ea3n ph\u1ea9m x\u00e2y hai l\u1edbp tr\u1ea3i nghi\u1ec7m song song: human layer t\u1eadp trung v\u00e0o narrative v\u00e0 trust, machine layer t\u1eadp trung v\u00e0o accuracy v\u00e0 queryability.<\/p>\n

      Engineering team n\u00e0o nh\u1eadn ra \u0111i\u1ec1u n\u00e0y s\u1edbm \u2014 v\u00e0 build testing pipeline \u0111\u1ec3 \u0111\u1ea3m b\u1ea3o ch\u1ea5t l\u01b0\u1ee3ng cho c\u1ea3 hai l\u1edbp \u2014 s\u1ebd c\u00f3 l\u1ee3i th\u1ebf th\u1ef1c s\u1ef1 khi AI-driven buyer journey tr\u1edf th\u00e0nh chu\u1ea9n m\u1edbi. Kh\u00f4ng ph\u1ea3i v\u00ec h\u1ecd bi\u1ebft AI \u0111ang thay \u0111\u1ed5i m\u1ecdi th\u1ee9, m\u00e0 v\u00ec h\u1ecd \u0111\u00e3 chu\u1ea9n b\u1ecb tr\u01b0\u1edbc khi s\u1ed1 li\u1ec7u y\u00eau c\u1ea7u h\u1ecd l\u00e0m v\u1eady.<\/p>\n","protected":false},"excerpt":{"rendered":"

      Website c\u1ee7a b\u1ea1n \u0111ang ph\u1ee5c v\u1ee5 ai \u2014 ng\u01b0\u1eddi d\u00f9ng hay AI agent? N\u0103m 2025, m\u1ed9t nghi\u00ean c\u1ee9u tr\u00ean 3.000 website ph\u00e1t hi\u1ec7n ra \u0111i\u1ec1u \u0111\u00e1ng suy ngh\u0129: 63% trong s\u1ed1 \u0111\u00f3 \u0111\u00e3 nh\u1eadn l\u01b0\u1ee3t truy c\u1eadp t\u1eeb AI agent \u2014 kh\u00f4ng ph\u1ea3i t\u1eeb ng\u01b0\u1eddi d\u00f9ng ng\u1ed3i tr\u01b0\u1edbc m\u00e0n h\u00ecnh. Nh\u01b0ng c\u0169ng trong c\u00f9ng th\u1eddi […]<\/p>\n","protected":false},"author":3,"featured_media":1291,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[30],"tags":[35,39,40],"class_list":["post-1290","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-insights","tag-agentic-ai","tag-website-agent","tag-website-humans"],"acf":[],"_links":{"self":[{"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/posts\/1290","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/comments?post=1290"}],"version-history":[{"count":1,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/posts\/1290\/revisions"}],"predecessor-version":[{"id":1292,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/posts\/1290\/revisions\/1292"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/media\/1291"}],"wp:attachment":[{"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/media?parent=1290"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/categories?post=1290"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/tags?post=1290"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}