{"id":1722,"date":"2026-05-06T04:40:00","date_gmt":"2026-05-06T04:40:00","guid":{"rendered":"https:\/\/bbotech.vn\/?p=1722"},"modified":"2026-05-11T03:14:07","modified_gmt":"2026-05-11T03:14:07","slug":"tu-prompt-engineer-sang-agent-engineering-khi-ai-tu-kiem-tra-lan-nhau-de-tao-ket-qua-dang-tin","status":"publish","type":"post","link":"https:\/\/bbotech.vn\/vi\/tu-prompt-engineer-sang-agent-engineering-khi-ai-tu-kiem-tra-lan-nhau-de-tao-ket-qua-dang-tin\/","title":{"rendered":"T\u1eeb Prompt Engineer Sang Agent Engineering"},"content":{"rendered":"<h2>Prompt kh\u00f4ng bi\u1ebfn m\u1ea5t, nh\u01b0ng n\u00f3 kh\u00f4ng c\u00f2n l\u00e0 trung t\u00e2m c\u1ee7a h\u1ec7 th\u1ed1ng AI hi\u1ec7n \u0111\u1ea1i<\/h2>\n<p>Trong giai \u0111o\u1ea1n \u0111\u1ea7u c\u1ee7a AI t\u1ea1o sinh, nhi\u1ec1u t\u1ed5 ch\u1ee9c xem n\u0103ng l\u1ef1c AI l\u00e0 n\u0103ng l\u1ef1c vi\u1ebft prompt. Ai m\u00f4 t\u1ea3 y\u00eau c\u1ea7u r\u00f5 h\u01a1n th\u00ec nh\u1eadn \u0111\u01b0\u1ee3c c\u00e2u tr\u1ea3 l\u1eddi t\u1ed1t h\u01a1n. C\u00e1ch nh\u00ecn \u0111\u00f3 \u0111\u00fang v\u1edbi th\u1eed nghi\u1ec7m c\u00e1 nh\u00e2n, nh\u01b0ng b\u1eaft \u0111\u1ea7u thi\u1ebfu khi doanh nghi\u1ec7p mu\u1ed1n AI x\u1eed l\u00fd c\u00f4ng vi\u1ec7c th\u1eadt: \u0111\u1ecdc d\u1eef li\u1ec7u, g\u1ecdi c\u00f4ng c\u1ee5, t\u1ef1 ki\u1ec3m tra, s\u1eeda l\u1ed7i, l\u01b0u v\u1ebft v\u00e0 bi\u1ebft khi n\u00e0o ph\u1ea3i d\u1eebng.<\/p>\n<p>\u0110i\u1ec3m chuy\u1ec3n d\u1ecbch quan tr\u1ecdng c\u1ee7a n\u0103m 2025-2026 l\u00e0 t\u1eeb <strong>prompt engineering<\/strong> sang <strong>agent engineering<\/strong>. Prompt v\u1eabn quan tr\u1ecdng, nh\u01b0ng ch\u1ec9 l\u00e0 m\u1ed9t ph\u1ea7n trong ki\u1ebfn tr\u00fac l\u1edbn h\u01a1n g\u1ed3m:<\/p>\n<ul>\n<li>Reasoning loop (V\u00f2ng l\u1eb7p suy lu\u1eadn)<\/li>\n<li>Autonomous agent (T\u00e1c nh\u00e2n t\u1ef1 ch\u1ee7)<\/li>\n<li>Multi-agent system (H\u1ec7 th\u1ed1ng \u0111a t\u00e1c nh\u00e2n)<\/li>\n<li>Orchestration. (Ph\u1ed1i h\u1ee3p v\u1eadn h\u00e0nh)<\/li>\n<\/ul>\n<p>Theo McKinsey, <strong>62% t\u1ed5 ch\u1ee9c \u0111\u01b0\u1ee3c kh\u1ea3o s\u00e1t \u0111\u00e3 \u00edt nh\u1ea5t th\u1eed nghi\u1ec7m AI agent<\/strong>, trong \u0111\u00f3 <strong>23% \u0111ang m\u1edf r\u1ed9ng agentic AI \u1edf m\u1ed9t ph\u1ea7n doanh nghi\u1ec7p<\/strong>. <em>(Ngu\u1ed3n: <a href=\"https:\/\/www.mckinsey.com\/capabilities\/quantumblack\/our-insights\/the-state-of-ai\" target=\"_blank\" rel=\"noopener\">McKinsey, The State of AI 2025<\/a>)<\/em><\/p>\n<blockquote><p>Agent engineering kh\u00f4ng thay prompt engineering. N\u00f3 \u0111\u1eb7t prompt v\u00e0o \u0111\u00fang v\u1ecb tr\u00ed: m\u1ed9t giao di\u1ec7n \u0111i\u1ec1u khi\u1ec3n trong h\u1ec7 th\u1ed1ng c\u00f3 v\u00f2ng l\u1eb7p, c\u00f4ng c\u1ee5, ki\u1ec3m tra, b\u1ed9 nh\u1edb v\u00e0 gi\u00e1m s\u00e1t.<\/p><\/blockquote>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1726 size-full\" src=\"https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/4.webp\" alt=\"\" width=\"1536\" height=\"1024\" srcset=\"https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/4.webp 1536w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/4-300x200.webp 300w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/4-1024x683.webp 1024w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/4-768x512.webp 768w\" sizes=\"auto, (max-width: 1536px) 100vw, 1536px\" \/><\/p>\n<p>&nbsp;<\/p>\n<h2>Agent engineering kh\u00e1c g\u00ec v\u1edbi Prompt engineering?<\/h2>\n<p><strong>Agent engineering<\/strong> l\u00e0 c\u00e1ch thi\u1ebft k\u1ebf h\u1ec7 th\u1ed1ng AI c\u00f3 th\u1ec3 nh\u1eadn m\u1ee5c ti\u00eau, chia vi\u1ec7c, d\u00f9ng c\u00f4ng c\u1ee5, quan s\u00e1t k\u1ebft qu\u1ea3, \u0111\u00e1nh gi\u00e1 \u0111\u1ea7u ra v\u00e0 \u0111i\u1ec1u ch\u1ec9nh h\u00e0nh \u0111\u1ed9ng qua nhi\u1ec1u b\u01b0\u1edbc. N\u1ebfu prompt engineering t\u1ed1i \u01b0u m\u1ed9t l\u1ea7n g\u1ecdi m\u00f4 h\u00ecnh, agent engineering t\u1ed1i \u01b0u to\u00e0n b\u1ed9 chu\u1ed7i ra quy\u1ebft \u0111\u1ecbnh.<\/p>\n<p>Anthropic ph\u00e2n bi\u1ec7t workflow v\u00e0 agent kh\u00e1 r\u00f5: workflow d\u00f9ng m\u00f4 h\u00ecnh v\u00e0 c\u00f4ng c\u1ee5 theo \u0111\u01b0\u1eddng \u0111i \u0111\u1ecbnh ngh\u0129a s\u1eb5n; agent l\u00e0 h\u1ec7 th\u1ed1ng trong \u0111\u00f3 m\u00f4 h\u00ecnh t\u1ef1 \u0111i\u1ec1u h\u01b0\u1edbng quy tr\u00ecnh v\u00e0 c\u00e1ch d\u00f9ng c\u00f4ng c\u1ee5 \u0111\u1ec3 ho\u00e0n th\u00e0nh nhi\u1ec7m v\u1ee5. <em>(Ngu\u1ed3n: <a href=\"https:\/\/www.anthropic.com\/research\/building-effective-agents\/\" target=\"_blank\" rel=\"noopener\">Anthropic, Building Effective Agents, 2024<\/a>)<\/em><\/p>\n<p>M\u1ed9t prompt c\u00f3 th\u1ec3 y\u00eau c\u1ea7u AI \u201ch\u00e3y vi\u1ebft test case cho t\u00ednh n\u0103ng thanh to\u00e1n\u201d. M\u1ed9t agent c\u00f3 th\u1ec3 \u0111\u1ecdc y\u00eau c\u1ea7u s\u1ea3n ph\u1ea9m, xem code diff, ch\u1ecdn b\u1ed9 ki\u1ec3m th\u1eed h\u1ed3i quy li\u00ean quan, t\u1ea1o test case, ch\u1ea1y ki\u1ec3m tra, ghi nh\u1eadn l\u1ed7i v\u00e0 chuy\u1ec3n tr\u01b0\u1eddng h\u1ee3p ch\u01b0a ch\u1eafc ch\u1eafn cho QA Lead.<\/p>\n<table>\n<thead>\n<tr>\n<th>Kh\u00eda c\u1ea1nh<\/th>\n<th>Prompt engineering<\/th>\n<th>Agent engineering<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Tr\u1ecdng t\u00e2m<\/td>\n<td style=\"border-style: solid; border-color: #000000;\">C\u00e1ch h\u1ecfi, ng\u1eef c\u1ea3nh, \u0111\u1ecbnh d\u1ea1ng \u0111\u1ea7u ra v\u00e0 r\u00e0ng bu\u1ed9c c\u00e2u tr\u1ea3 l\u1eddi.<\/td>\n<td>Vai tr\u00f2 agent, c\u00f4ng c\u1ee5 \u0111\u01b0\u1ee3c d\u00f9ng, ti\u00eau ch\u00ed \u0111\u00e1nh gi\u00e1, quy\u1ec1n h\u1ea1n v\u00e0 \u0111i\u1ec3m d\u1eebng.<\/td>\n<\/tr>\n<tr>\n<td>\u0110\u01a1n v\u1ecb t\u1ed1i \u01b0u<\/td>\n<td>M\u1ed9t l\u1ea7n g\u1ecdi m\u00f4 h\u00ecnh ho\u1eb7c m\u1ed9t \u0111o\u1ea1n h\u1ed9i tho\u1ea1i ng\u1eafn.<\/td>\n<td>To\u00e0n b\u1ed9 workflow g\u1ed3m l\u1eadp k\u1ebf ho\u1ea1ch, th\u1ef1c thi, ki\u1ec3m tra, s\u1eeda v\u00e0 b\u00e0n giao.<\/td>\n<\/tr>\n<tr>\n<td>C\u00e1ch x\u1eed l\u00fd l\u1ed7i<\/td>\n<td>S\u1eeda prompt r\u1ed3i ch\u1ea1y l\u1ea1i th\u1ee7 c\u00f4ng.<\/td>\n<td>D\u00f9ng reasoning loop, evaluator v\u00e0 verifier \u0111\u1ec3 ph\u00e1t hi\u1ec7n l\u1ed7i trong qu\u00e1 tr\u00ecnh ch\u1ea1y.<\/td>\n<\/tr>\n<tr>\n<td>Vai tr\u00f2 c\u1ee7a con ng\u01b0\u1eddi<\/td>\n<td>Ng\u01b0\u1eddi nh\u1eadp y\u00eau c\u1ea7u v\u00e0 \u0111\u00e1nh gi\u00e1 k\u1ebft qu\u1ea3 cu\u1ed1i.<\/td>\n<td>Ng\u01b0\u1eddi thi\u1ebft k\u1ebf policy, ph\u00ea duy\u1ec7t ngo\u1ea1i l\u1ec7 v\u00e0 gi\u00e1m s\u00e1t trace.<\/td>\n<\/tr>\n<tr>\n<td>Orchestration<\/td>\n<td>Th\u01b0\u1eddng kh\u00f4ng c\u1ea7n, ho\u1eb7c ch\u1ec9 \u1edf m\u1ee9c chu\u1ed7i prompt \u0111\u01a1n gi\u1ea3n.<\/td>\n<td>\u0110i\u1ec1u ph\u1ed1i th\u1ee9 t\u1ef1, v\u00f2ng l\u1eb7p, handoff v\u00e0 \u0111i\u1ec3m ph\u00ea duy\u1ec7t gi\u1eefa c\u00e1c agent.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<p>OpenAI c\u0169ng \u0111\u1eb7t tr\u1ecdng t\u00e2m v\u00e0o orchestration, handoff, guardrail v\u00e0 tracing khi gi\u1edbi thi\u1ec7u Responses API v\u00e0 Agents SDK. <em>(Ngu\u1ed3n: <a href=\"https:\/\/openai.com\/index\/new-tools-for-building-agents\/\" target=\"_blank\" rel=\"noopener\">OpenAI, New tools for building agents, 2025<\/a>)<\/em><\/p>\n<p><!-- IMAGE: reasoning loop feedback correction software agents --><\/p>\n<h2>Reasoning loop bi\u1ebfn l\u1ed7i th\u00e0nh t\u00edn hi\u1ec7u s\u1eeda l\u1ed7i nh\u01b0 th\u1ebf n\u00e0o?<\/h2>\n<p><strong>Reasoning loop<\/strong> l\u00e0 v\u00f2ng l\u1eb7p trong \u0111\u00f3 agent kh\u00f4ng ch\u1ec9 t\u1ea1o \u0111\u1ea7u ra, m\u00e0 c\u00f2n quan s\u00e1t ph\u1ea3n h\u1ed3i t\u1eeb m\u00f4i tr\u01b0\u1eddng, ki\u1ec3m tra k\u1ebft qu\u1ea3, ph\u00e1t hi\u1ec7n \u0111i\u1ec3m sai v\u00e0 th\u1eed l\u1ea1i. M\u1ed9t v\u00f2ng l\u1eb7p t\u1ed1i thi\u1ec3u th\u01b0\u1eddng c\u00f3 n\u0103m b\u01b0\u1edbc: nh\u1eadn m\u1ee5c ti\u00eau, l\u1eadp k\u1ebf ho\u1ea1ch, th\u1ef1c thi, \u0111\u00e1nh gi\u00e1, r\u1ed3i s\u1eeda ho\u1eb7c d\u1eebng.<\/p>\n<p>Trong coding agent, b\u01b0\u1edbc \u0111\u00e1nh gi\u00e1 c\u00f3 th\u1ec3 l\u00e0 ch\u1ea1y test. Trong QA agent, \u0111\u00f3 c\u00f3 th\u1ec3 l\u00e0 ki\u1ec3m tra coverage, so s\u00e1nh y\u00eau c\u1ea7u v\u1edbi test case, ho\u1eb7c ph\u00e1t hi\u1ec7n v\u00f9ng r\u1ee7i ro ch\u01b0a \u0111\u01b0\u1ee3c ki\u1ec3m th\u1eed.<\/p>\n<p>C\u01a1 ch\u1ebf n\u00e0y c\u00f3 c\u01a1 s\u1edf nghi\u00ean c\u1ee9u. Paper <em>Self-Refine<\/em> cho th\u1ea5y vi\u1ec7c \u0111\u1ec3 m\u00f4 h\u00ecnh t\u1ef1 t\u1ea1o ph\u1ea3n h\u1ed3i v\u00e0 tinh ch\u1ec9nh l\u1eb7p c\u00f3 th\u1ec3 c\u1ea3i thi\u1ec7n trung b\u00ecnh kho\u1ea3ng <strong>20 \u0111i\u1ec3m ph\u1ea7n tr\u0103m tuy\u1ec7t \u0111\u1ed1i<\/strong> tr\u00ean nhi\u1ec1u t\u00e1c v\u1ee5 so v\u1edbi sinh m\u1ed9t l\u1ea7n. <em>(Ngu\u1ed3n: <a href=\"https:\/\/arxiv.org\/abs\/2303.17651\" target=\"_blank\" rel=\"noopener\">Self-Refine, 2023<\/a>)<\/em> Paper <em>Reflexion<\/em> c\u0169ng cho th\u1ea5y language agent c\u00f3 th\u1ec3 c\u1ea3i thi\u1ec7n b\u1eb1ng ph\u1ea3n h\u1ed3i ng\u00f4n ng\u1eef v\u00e0 b\u1ed9 nh\u1edb kinh nghi\u1ec7m, kh\u00f4ng c\u1ea7n c\u1eadp nh\u1eadt tr\u1ecdng s\u1ed1 m\u00f4 h\u00ecnh; tr\u00ean HumanEval, Reflexion b\u00e1o c\u00e1o <strong>91% pass@1<\/strong> trong thi\u1ebft l\u1eadp c\u1ee7a paper. <em>(Ngu\u1ed3n: <a href=\"https:\/\/papers.nips.cc\/paper_files\/paper\/2023\/hash\/1b44b878bb782e6954cd888628510e90-Abstract-Conference.html\" target=\"_blank\" rel=\"noopener\">Reflexion, NeurIPS 2023<\/a>)<\/em><\/p>\n<blockquote><p>L\u1ed7i c\u1ee7a agent kh\u00f4ng n\u00ean b\u1ecb xem l\u00e0 s\u1ef1 c\u1ed1 cu\u1ed1i c\u00f9ng. Trong thi\u1ebft k\u1ebf t\u1ed1t, l\u1ed7i l\u00e0 d\u1eef li\u1ec7u \u0111\u1ea7u v\u00e0o cho v\u00f2ng s\u1eeda ti\u1ebfp theo.<\/p><\/blockquote>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1725 size-full\" src=\"https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/1-scaled.jpg\" alt=\"\" width=\"2560\" height=\"1707\" srcset=\"https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/1-scaled.jpg 2560w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/1-300x200.jpg 300w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/1-1024x683.jpg 1024w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/1-768x512.jpg 768w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/1-1536x1024.jpg 1536w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/1-2048x1365.jpg 2048w\" sizes=\"auto, (max-width: 2560px) 100vw, 2560px\" \/><\/p>\n<p>&nbsp;<\/p>\n<h2>Multi-agent system t\u1ef1 s\u1eeda l\u1ed7i cho nhau b\u1eb1ng c\u00e1ch ph\u00e2n vai<\/h2>\n<p>Trong h\u1ec7 th\u1ed1ng \u0111\u01a1n agent, c\u00f9ng m\u1ed9t m\u00f4 h\u00ecnh th\u01b0\u1eddng ph\u1ea3i hi\u1ec3u y\u00eau c\u1ea7u, l\u1eadp k\u1ebf ho\u1ea1ch, vi\u1ebft k\u1ebft qu\u1ea3, ki\u1ec3m tra, s\u1eeda v\u00e0 quy\u1ebft \u0111\u1ecbnh d\u1eebng. V\u1ea5n \u0111\u1ec1 l\u00e0 m\u1ed7i vai tr\u00f2 \u0111\u00f2i h\u1ecfi m\u1ed9t ki\u1ec3u ch\u00fa \u00fd kh\u00e1c nhau. Ng\u01b0\u1eddi vi\u1ebft th\u01b0\u1eddng d\u1ec5 b\u1ecf s\u00f3t l\u1ed7i c\u1ee7a ch\u00ednh m\u00ecnh; m\u00f4 h\u00ecnh c\u0169ng v\u1eady.<\/p>\n<p>Multi-agent system gi\u1ea3i b\u00e0i to\u00e1n n\u00e0y b\u1eb1ng c\u00e1ch ph\u00e2n t\u00e1ch tr\u00e1ch nhi\u1ec7m. M\u1ed9t agent t\u1ea1o ph\u01b0\u01a1ng \u00e1n. Agent kh\u00e1c ki\u1ec3m tra logic. Agent th\u1ee9 ba ki\u1ec3m tra d\u1eef li\u1ec7u v\u00e0 ngu\u1ed3n. Agent th\u1ee9 t\u01b0 \u0111\u00e1nh gi\u00e1 r\u1ee7i ro. Orchestrator t\u1ed5ng h\u1ee3p ph\u1ea3n h\u1ed3i v\u00e0 quy\u1ebft \u0111\u1ecbnh v\u00f2ng ti\u1ebfp theo.<\/p>\n<p>Anthropic g\u1ecdi pattern n\u00e0y l\u00e0 <strong>evaluator-optimizer<\/strong>: m\u1ed9t l\u1eddi g\u1ecdi m\u00f4 h\u00ecnh t\u1ea1o \u0111\u1ea7u ra, l\u1eddi g\u1ecdi kh\u00e1c \u0111\u00e1nh gi\u00e1 v\u00e0 \u0111\u01b0a ph\u1ea3n h\u1ed3i. Microsoft AutoGen c\u0169ng ti\u1ebfp c\u1eadn theo h\u01b0\u1edbng nhi\u1ec1u agent tr\u00f2 chuy\u1ec7n v\u1edbi nhau \u0111\u1ec3 x\u1eed l\u00fd t\u00e1c v\u1ee5 ph\u1ee9c t\u1ea1p. <em>(Ngu\u1ed3n: <a href=\"https:\/\/www.microsoft.com\/en-us\/research\/?p=962712\" target=\"_blank\" rel=\"noopener\">Microsoft Research, AutoGen<\/a>)<\/em><\/p>\n<ul>\n<li><strong>Planner agent:<\/strong> chia m\u1ee5c ti\u00eau th\u00e0nh c\u00e1c b\u01b0\u1edbc nh\u1ecf, x\u00e1c \u0111\u1ecbnh c\u00f4ng c\u1ee5 v\u00e0 d\u1eef li\u1ec7u c\u1ea7n d\u00f9ng.<\/li>\n<li><strong>Executor agent:<\/strong> th\u1ef1c thi t\u1eebng b\u01b0\u1edbc, g\u1ecdi API, vi\u1ebft code, t\u1ea1o test ho\u1eb7c sinh n\u1ed9i dung.<\/li>\n<li><strong>Critic agent:<\/strong> t\u00ecm l\u1ed7 h\u1ed5ng logic, thi\u1ebfu ngu\u1ed3n, thi\u1ebfu test ho\u1eb7c gi\u1ea3 \u0111\u1ecbnh ch\u01b0a ki\u1ec3m ch\u1ee9ng.<\/li>\n<li><strong>Verifier agent:<\/strong> ki\u1ec3m tra \u0111\u1ea7u ra b\u1eb1ng d\u1eef li\u1ec7u, test suite, schema, rule engine ho\u1eb7c checklist.<\/li>\n<li><strong>Orchestrator:<\/strong> quy\u1ebft \u0111\u1ecbnh agent n\u00e0o ch\u1ea1y ti\u1ebfp, khi n\u00e0o s\u1eeda, khi n\u00e0o d\u1eebng, khi n\u00e0o c\u1ea7n con ng\u01b0\u1eddi ph\u00ea duy\u1ec7t.<\/li>\n<\/ul>\n<p>C\u00e1ch n\u00e0y kh\u00f4ng b\u1ea3o \u0111\u1ea3m ho\u00e0n h\u1ea3o tuy\u1ec7t \u0111\u1ed1i. N\u00f3 t\u1ea1o k\u1ebft qu\u1ea3 g\u1ea7n ho\u00e0n h\u1ea3o theo b\u1ed9 ti\u00eau ch\u00ed \u0111\u00e3 \u0111\u1ecbnh: \u0111\u1ee7 ngu\u1ed3n, \u0111\u00fang schema, pass test, kh\u00f4ng vi ph\u1ea1m policy, c\u00f3 log v\u00e0 c\u00f3 \u0111i\u1ec3m d\u1eebng r\u00f5 r\u00e0ng.<\/p>\n<p>&nbsp;<\/p>\n<p><!-- IMAGE: autonomous agents reviewing code and QA test results --><\/p>\n<h2>Orchestration quy\u1ebft \u0111\u1ecbnh h\u1ec7 \u0111a agent \u0111\u00e1ng tin hay ch\u1ec9 \u1ed3n h\u01a1n<\/h2>\n<p>Khi c\u00f3 nhi\u1ec1u agent, r\u1ee7i ro kh\u00f4ng gi\u1ea3m t\u1ef1 \u0111\u1ed9ng. N\u1ebfu orchestration k\u00e9m, nhi\u1ec1u agent ch\u1ec9 t\u1ea1o ra nhi\u1ec1u \u00fd ki\u1ebfn h\u01a1n, nhi\u1ec1u chi ph\u00ed h\u01a1n v\u00e0 nhi\u1ec1u v\u00f2ng l\u1eb7p h\u01a1n. Orchestration t\u1ed1t ph\u1ea3i tr\u1ea3 l\u1eddi b\u1ed1n c\u00e2u h\u1ecfi: ai \u0111\u01b0\u1ee3c l\u00e0m g\u00ec, d\u1ef1a tr\u00ean d\u1eef li\u1ec7u n\u00e0o, khi n\u00e0o ph\u1ea3i d\u1eebng, v\u00e0 ai ch\u1ecbu tr\u00e1ch nhi\u1ec7m khi k\u1ebft qu\u1ea3 sai.<\/p>\n<p>Gartner c\u1ea3nh b\u00e1o h\u01a1n <strong>40% d\u1ef1 \u00e1n agentic AI c\u00f3 th\u1ec3 b\u1ecb h\u1ee7y tr\u01b0\u1edbc cu\u1ed1i n\u0103m 2027<\/strong> v\u00ec chi ph\u00ed t\u0103ng, gi\u00e1 tr\u1ecb kinh doanh kh\u00f4ng r\u00f5 ho\u1eb7c ki\u1ec3m so\u00e1t r\u1ee7i ro kh\u00f4ng \u0111\u1ee7. C\u00f9ng b\u00e1o c\u00e1o d\u1ef1 b\u00e1o \u0111\u1ebfn n\u0103m 2028, <strong>15% quy\u1ebft \u0111\u1ecbnh c\u00f4ng vi\u1ec7c h\u1eb1ng ng\u00e0y<\/strong> c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c th\u1ef1c hi\u1ec7n t\u1ef1 ch\u1ee7 qua agentic AI, v\u00e0 <strong>33% \u1ee9ng d\u1ee5ng doanh nghi\u1ec7p<\/strong> s\u1ebd c\u00f3 agentic AI. <em>(Ngu\u1ed3n: <a href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2025-06-25-gartner-predicts-over-40-percent-of-agentic-ai-projects-will-be-canceled-by-end-of-2027\" target=\"_blank\" rel=\"noopener\">Gartner, June 2025<\/a>)<\/em><\/p>\n<p>V\u1edbi QA v\u00e0 software engineering, orchestration n\u00ean c\u00f3 t\u1ed1i thi\u1ec3u: ph\u1ea1m vi nhi\u1ec7m v\u1ee5, qu\u1ea3n l\u00fd tr\u1ea1ng th\u00e1i, evaluation gate, rule chuy\u1ec3n ng\u01b0\u1eddi th\u1eadt v\u00e0 trace \u0111\u1ee7 \u0111\u1ec3 audit. Agent b\u00e1o \u201c\u0111\u00e3 xong\u201d nh\u01b0ng kh\u00f4ng c\u00f3 trace th\u00ec ch\u01b0a th\u1ec3 \u0111\u01b0a v\u00e0o s\u1ea3n xu\u1ea5t.<\/p>\n<p>&nbsp;<\/p>\n<h2>Autonomous agent kh\u00f4ng c\u00f3 ngh\u0129a l\u00e0 b\u1ecf gi\u00e1m s\u00e1t<\/h2>\n<p>T\u1eeb \u201cautonomous agent\u201d d\u1ec5 t\u1ea1o c\u1ea3m gi\u00e1c AI c\u00f3 th\u1ec3 t\u1ef1 l\u00e0m h\u1ebft. Trong doanh nghi\u1ec7p, c\u00e1ch hi\u1ec3u \u0111\u00f3 nguy hi\u1ec3m. T\u1ef1 ch\u1ee7 n\u00ean \u0111\u01b0\u1ee3c hi\u1ec3u l\u00e0 t\u1ef1 ch\u1ee7 trong m\u1ed9t ph\u1ea1m vi \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf, kh\u00f4ng ph\u1ea3i t\u1ef1 do tuy\u1ec7t \u0111\u1ed1i.<\/p>\n<p>Gartner kh\u1ea3o s\u00e1t IT application leaders v\u00e0 ghi nh\u1eadn ch\u1ec9 <strong>15%<\/strong> \u0111ang c\u00e2n nh\u1eafc, th\u1eed nghi\u1ec7m ho\u1eb7c tri\u1ec3n khai fully autonomous AI agents. D\u00f9 <strong>75%<\/strong> \u0111\u00e3 tri\u1ec3n khai ho\u1eb7c th\u1eed nghi\u1ec7m m\u1ed9t s\u1ed1 d\u1ea1ng AI agent, m\u1ed1i lo v\u1ec1 governance, maturity v\u00e0 agent sprawl v\u1eabn c\u1ea3n tr\u1edf c\u00e1c h\u1ec7 th\u1ef1c s\u1ef1 t\u1ef1 ch\u1ee7. Ch\u1ec9 <strong>13%<\/strong> \u0111\u1ed3ng \u00fd m\u1ea1nh r\u1eb1ng h\u1ecd c\u00f3 c\u1ea5u tr\u00fac governance ph\u00f9 h\u1ee3p \u0111\u1ec3 qu\u1ea3n l\u00fd agent. <em>(Ngu\u1ed3n: <a href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2025-09-30-gartner-survey-finds-just-15-percent-of-it-application-leaders-are-considering-piloting-or-deploying-fully-autonomous-ai-agents\" target=\"_blank\" rel=\"noopener\">Gartner, September 2025<\/a>)<\/em><\/p>\n<p>B\u01b0\u1edbc tr\u01b0\u1edfng th\u00e0nh kh\u00f4ng ph\u1ea3i l\u00e0 \u0111\u01b0a con ng\u01b0\u1eddi ra kh\u1ecfi v\u00f2ng l\u1eb7p. B\u01b0\u1edbc tr\u01b0\u1edfng th\u00e0nh l\u00e0 \u0111\u1eb7t con ng\u01b0\u1eddi \u1edf \u0111\u00fang \u0111i\u1ec3m: \u0111\u1ecbnh ngh\u0129a m\u1ee5c ti\u00eau, thi\u1ebft k\u1ebf ti\u00eau ch\u00ed, ph\u00ea duy\u1ec7t ngo\u1ea1i l\u1ec7 v\u00e0 c\u1ea3i ti\u1ebfn h\u1ec7 th\u1ed1ng sau khi quan s\u00e1t log.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1724 size-full\" src=\"https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/2-scaled.jpg\" alt=\"\" width=\"2560\" height=\"1709\" srcset=\"https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/2-scaled.jpg 2560w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/2-300x200.jpg 300w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/2-1024x684.jpg 1024w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/2-768x513.jpg 768w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/2-1536x1025.jpg 1536w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/2-2048x1367.jpg 2048w\" sizes=\"auto, (max-width: 2560px) 100vw, 2560px\" \/><\/p>\n<p>&nbsp;<\/p>\n<h2>Th\u1ebf gi\u1edbi n\u00f3i chung, Vi\u1ec7t Nam n\u00f3i ri\u00eang: t\u00e1c \u0111\u1ed9ng n\u1eb1m \u1edf n\u0103ng l\u1ef1c thi\u1ebft k\u1ebf workflow<\/h2>\n<p>Tr\u00ean th\u1ebf gi\u1edbi, agentic AI \u0111ang chuy\u1ec3n t\u1eeb demo sang workflow th\u1eadt, nh\u01b0ng ph\u1ea7n l\u1edbn doanh nghi\u1ec7p v\u1eabn \u1edf giai \u0111o\u1ea1n th\u1eed nghi\u1ec7m. McKinsey ghi nh\u1eadn g\u1ea7n <strong>88% t\u1ed5 ch\u1ee9c<\/strong> s\u1eed d\u1ee5ng AI th\u01b0\u1eddng xuy\u00ean \u1edf \u00edt nh\u1ea5t m\u1ed9t ch\u1ee9c n\u0103ng kinh doanh, nh\u01b0ng \u0111a s\u1ed1 ch\u01b0a scale \u1edf c\u1ea5p to\u00e0n doanh nghi\u1ec7p. V\u1edbi AI agent, ch\u1ec9 <strong>23%<\/strong> \u0111ang m\u1edf r\u1ed9ng agentic AI \u1edf m\u1ed9t ph\u1ea7n t\u1ed5 ch\u1ee9c. <em>(Ngu\u1ed3n: <a href=\"https:\/\/www.mckinsey.com\/capabilities\/quantumblack\/our-insights\/the-state-of-ai\" target=\"_blank\" rel=\"noopener\">McKinsey, 2025<\/a>)<\/em><\/p>\n<p>L\u1ee3i th\u1ebf v\u00ec v\u1eady kh\u00f4ng thu\u1ed9c v\u1ec1 \u0111\u1ed9i \u201cbi\u1ebft prompt hay\u201d nh\u1ea5t, m\u00e0 thu\u1ed9c v\u1ec1 \u0111\u1ed9i bi\u1ebft ch\u1ecdn workflow ph\u00f9 h\u1ee3p: x\u1eed l\u00fd ticket, QA regression, review t\u00e0i li\u1ec7u k\u1ef9 thu\u1eadt, ph\u00e2n t\u00edch log, ki\u1ec3m tra tu\u00e2n th\u1ee7 v\u00e0 t\u1ed5ng h\u1ee3p tri th\u1ee9c n\u1ed9i b\u1ed9.<\/p>\n<p>\u1ede Vi\u1ec7t Nam, AWS v\u00e0 Strand Partners kh\u1ea3o s\u00e1t n\u0103m 2025 cho bi\u1ebft <strong>18% doanh nghi\u1ec7p Vi\u1ec7t Nam \u0111\u00e3 \u00e1p d\u1ee5ng AI<\/strong>, t\u0103ng t\u1eeb <strong>13%<\/strong> n\u0103m tr\u01b0\u1edbc; tuy nhi\u00ean <strong>74%<\/strong> v\u1eabn t\u1eadp trung v\u00e0o c\u00e1c \u1ee9ng d\u1ee5ng c\u01a1 b\u1ea3n, v\u00e0 <strong>55%<\/strong> xem thi\u1ebfu k\u1ef9 n\u0103ng s\u1ed1 l\u00e0 r\u00e0o c\u1ea3n ch\u00ednh \u0111\u1ec3 m\u1edf r\u1ed9ng AI. <em>(Ngu\u1ed3n: <a href=\"https:\/\/press.aboutamazon.com\/sg\/aws\/2025\/9\/new-aws-research-shows-strong-ai-adoption-momentum-in-vietnam\" target=\"_blank\" rel=\"noopener\">AWS, Unlocking Vietnam&#8217;s AI Potential, 2025<\/a>)<\/em><\/p>\n<p>Doanh nghi\u1ec7p Vi\u1ec7t Nam ch\u01b0a c\u1ea7n lao ngay v\u00e0o h\u1ec7 autonomous agent ph\u1ee9c t\u1ea1p. Nh\u01b0ng n\u00ean x\u00e2y n\u0103ng l\u1ef1c agent engineering t\u1eeb b\u00e2y gi\u1edd, v\u00ec kho\u1ea3ng c\u00e1ch th\u1eadt s\u1ef1 s\u1ebd n\u1eb1m \u1edf d\u1eef li\u1ec7u s\u1ea1ch, workflow r\u00f5, ti\u00eau ch\u00ed \u0111o \u0111\u01b0\u1ee3c v\u00e0 \u0111\u1ed9i ng\u0169 bi\u1ebft ki\u1ec3m so\u00e1t agent.<\/p>\n<p>&nbsp;<\/p>\n<h2>L\u1ed9 tr\u00ecnh 90 ng\u00e0y \u0111\u1ec3 chuy\u1ec3n t\u1eeb prompt sang agent engineering<\/h2>\n<p>L\u1ed9 tr\u00ecnh kh\u1ea3 thi kh\u00f4ng b\u1eaft \u0111\u1ea7u b\u1eb1ng vi\u1ec7c mua framework l\u1edbn nh\u1ea5t. Anthropic khuy\u1ebfn ngh\u1ecb t\u00ecm gi\u1ea3i ph\u00e1p \u0111\u01a1n gi\u1ea3n nh\u1ea5t tr\u01b0\u1edbc, ch\u1ec9 t\u0103ng \u0111\u1ed9 ph\u1ee9c t\u1ea1p khi c\u1ea7n v\u00ec agentic system th\u01b0\u1eddng \u0111\u00e1nh \u0111\u1ed5i chi ph\u00ed v\u00e0 \u0111\u1ed9 tr\u1ec5 \u0111\u1ec3 l\u1ea5y hi\u1ec7u n\u0103ng t\u1ed1t h\u01a1n. <em>(Ngu\u1ed3n: <a href=\"https:\/\/www.anthropic.com\/research\/building-effective-agents\/\" target=\"_blank\" rel=\"noopener\">Anthropic, 2024<\/a>)<\/em><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1723 size-full\" src=\"https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/3-scaled.jpg\" alt=\"\" width=\"2560\" height=\"1920\" srcset=\"https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/3-scaled.jpg 2560w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/3-300x225.jpg 300w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/3-1024x768.jpg 1024w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/3-768x576.jpg 768w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/3-1536x1152.jpg 1536w, https:\/\/bbotech.vn\/wp-content\/uploads\/2026\/05\/3-2048x1536.jpg 2048w\" sizes=\"auto, (max-width: 2560px) 100vw, 2560px\" \/><\/p>\n<h3>Ng\u00e0y 1-30: ch\u1ecdn m\u1ed9t workflow nh\u1ecf v\u00e0 \u0111o baseline<\/h3>\n<p>Ch\u1ecdn m\u1ed9t workflow c\u00f3 \u0111\u1ea7u v\u00e0o r\u00f5, \u0111\u1ea7u ra \u0111o \u0111\u01b0\u1ee3c v\u00e0 r\u1ee7i ro v\u1eeba ph\u1ea3i: ph\u00e2n lo\u1ea1i bug report, t\u1ea1o test case t\u1eeb user story ho\u1eb7c ki\u1ec3m tra t\u00e0i li\u1ec7u release. Tr\u01b0\u1edbc khi d\u00f9ng agent, \u0111o baseline: th\u1eddi gian x\u1eed l\u00fd, t\u1ef7 l\u1ec7 l\u1ed7i, s\u1ed1 l\u1ea7n c\u1ea7n con ng\u01b0\u1eddi s\u1eeda, chi ph\u00ed v\u00e0 SLA.<\/p>\n<h3>Ng\u00e0y 31-60: thi\u1ebft k\u1ebf reasoning loop v\u00e0 evaluator<\/h3>\n<p>B\u1eaft \u0111\u1ea7u b\u1eb1ng m\u00f4 h\u00ecnh generator-evaluator: m\u1ed9t agent t\u1ea1o k\u1ebft qu\u1ea3, agent kh\u00e1c ki\u1ec3m tra theo rubric. V\u1edbi QA, rubric c\u00f3 th\u1ec3 g\u1ed3m: y\u00eau c\u1ea7u n\u00e0o ch\u01b0a c\u00f3 test, test n\u00e0o tr\u00f9ng, v\u00f9ng r\u1ee7i ro n\u00e0o ch\u01b0a ch\u1ea1m v\u00e0 k\u1ebft qu\u1ea3 c\u00f3 c\u1ea7n human approval kh\u00f4ng. H\u00e3y l\u01b0u trace cho t\u1eebng v\u00f2ng.<\/p>\n<h3>Ng\u00e0y 61-90: th\u00eam orchestration v\u00e0 \u0111i\u1ec3m d\u1eebng<\/h3>\n<p>Th\u00eam rule \u0111\u1ec3 gi\u1edbi h\u1ea1n s\u1ed1 v\u00f2ng l\u1eb7p, gi\u1edbi h\u1ea1n chi ph\u00ed, \u0111i\u1ec1u ki\u1ec7n chuy\u1ec3n ng\u01b0\u1eddi th\u1eadt v\u00e0 ti\u00eau ch\u00ed \u201c\u0111\u1ee7 t\u1ed1t \u0111\u1ec3 b\u00e0n giao\u201d. N\u1ebfu workflow li\u00ean quan code, b\u1eaft bu\u1ed9c ch\u1ea1y test. N\u1ebfu li\u00ean quan d\u1eef li\u1ec7u kh\u00e1ch h\u00e0ng, b\u1eaft bu\u1ed9c ki\u1ec3m tra quy\u1ec1n truy c\u1eadp v\u00e0 masking.<\/p>\n<p>Sau 90 ng\u00e0y, \u0111\u00e1nh gi\u00e1 b\u1eb1ng ch\u1ec9 s\u1ed1 v\u1eadn h\u00e0nh: cycle time gi\u1ea3m bao nhi\u00eau, l\u1ed7i l\u1ecdt gi\u1ea3m bao nhi\u00eau, t\u1ef7 l\u1ec7 output b\u1ecb tr\u1ea3 l\u1ea1i l\u00e0 bao nhi\u00eau, chi ph\u00ed m\u1ed7i workflow l\u00e0 bao nhi\u00eau v\u00e0 con ng\u01b0\u1eddi can thi\u1ec7p \u1edf \u0111i\u1ec3m n\u00e0o.<\/p>\n<p>&nbsp;<\/p>\n<h2>K\u1ebft lu\u1eadn: t\u01b0\u01a1ng lai kh\u00f4ng thu\u1ed9c v\u1ec1 prompt d\u00e0i h\u01a1n, m\u00e0 thu\u1ed9c v\u1ec1 h\u1ec7 th\u1ed1ng bi\u1ebft t\u1ef1 ki\u1ec3m tra<\/h2>\n<p>Prompt engineering t\u1eebng l\u00e0 k\u1ef9 n\u0103ng c\u1eeda ng\u00f5 c\u1ee7a AI. Nh\u01b0ng khi AI b\u01b0\u1edbc v\u00e0o quy tr\u00ecnh s\u1ea3n xu\u1ea5t, prompt kh\u00f4ng \u0111\u1ee7 \u0111\u1ec3 b\u1ea3o \u0111\u1ea3m ch\u1ea5t l\u01b0\u1ee3ng. Doanh nghi\u1ec7p c\u1ea7n agent engineering: thi\u1ebft k\u1ebf agent, reasoning loop, multi-agent system, orchestration, guardrail, evaluation v\u00e0 trace.<\/p>\n<p>Multi-agent system t\u1ea1o ra gi\u00e1 tr\u1ecb kh\u00f4ng ph\u1ea3i v\u00ec nhi\u1ec1u agent \u201cth\u00f4ng minh\u201d h\u01a1n m\u1ed9t agent. Gi\u00e1 tr\u1ecb n\u1eb1m \u1edf ph\u00e2n vai v\u00e0 ki\u1ec3m tra ch\u00e9o. M\u1ed9t agent l\u00e0m, m\u1ed9t agent ph\u1ea3n bi\u1ec7n, m\u1ed9t agent ki\u1ec3m ch\u1ee9ng, orchestrator quy\u1ebft \u0111\u1ecbnh v\u00f2ng ti\u1ebfp theo. H\u1ec7 th\u1ed1ng t\u1ed1t kh\u00f4ng gi\u1ea3 \u0111\u1ecbnh AI lu\u00f4n \u0111\u00fang. N\u00f3 gi\u1ea3 \u0111\u1ecbnh AI c\u00f3 th\u1ec3 sai, r\u1ed3i x\u00e2y c\u01a1 ch\u1ebf \u0111\u1ec3 ph\u00e1t hi\u1ec7n, s\u1eeda v\u00e0 d\u1eebng \u0111\u00fang l\u00fac.<\/p>\n<hr \/>\n<p><strong>3 \u0111i\u1ec3m ch\u00ednh c\u1ea7n nh\u1edb:<\/strong><\/p>\n<ul>\n<li>Prompt v\u1eabn quan tr\u1ecdng, nh\u01b0ng trong h\u1ec7 th\u1ed1ng hi\u1ec7n \u0111\u1ea1i n\u00f3 l\u00e0 m\u1ed9t ph\u1ea7n c\u1ee7a agent architecture, kh\u00f4ng ph\u1ea3i to\u00e0n b\u1ed9 n\u0103ng l\u1ef1c AI.<\/li>\n<li>Reasoning loop v\u00e0 evaluator-optimizer gi\u00fap AI t\u1ef1 s\u1eeda theo ti\u00eau ch\u00ed r\u00f5, thay v\u00ec ch\u1ec9 sinh m\u1ed9t l\u1ea7n r\u1ed3i hy v\u1ecdng \u0111\u00fang.<\/li>\n<li>Th\u1ebf gi\u1edbi \u0111ang th\u1eed nghi\u1ec7m agentic AI r\u1ea5t nhanh; Vi\u1ec7t Nam n\u00ean b\u1eaft \u0111\u1ea7u t\u1eeb workflow nh\u1ecf, \u0111o \u0111\u01b0\u1ee3c, c\u00f3 guardrail v\u00e0 human approval.<\/li>\n<\/ul>\n<p><strong>Ngu\u1ed3n tham kh\u1ea3o:<\/strong><\/p>\n<ul>\n<li><a href=\"https:\/\/www.mckinsey.com\/capabilities\/quantumblack\/our-insights\/the-state-of-ai\" target=\"_blank\" rel=\"noopener\">McKinsey, The State of AI in 2025: Agents, innovation, and transformation<\/a><\/li>\n<li><a href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2025-06-25-gartner-predicts-over-40-percent-of-agentic-ai-projects-will-be-canceled-by-end-of-2027\" target=\"_blank\" rel=\"noopener\">Gartner, Over 40% of Agentic AI Projects Will Be Canceled by End of 2027<\/a><\/li>\n<li><a href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2025-09-30-gartner-survey-finds-just-15-percent-of-it-application-leaders-are-considering-piloting-or-deploying-fully-autonomous-ai-agents\" target=\"_blank\" rel=\"noopener\">Gartner, Fully Autonomous AI Agents Survey, 2025<\/a><\/li>\n<li><a href=\"https:\/\/openai.com\/index\/new-tools-for-building-agents\/\" target=\"_blank\" rel=\"noopener\">OpenAI, New tools for building agents<\/a><\/li>\n<li><a href=\"https:\/\/www.anthropic.com\/research\/building-effective-agents\/\" target=\"_blank\" rel=\"noopener\">Anthropic, Building Effective Agents<\/a><\/li>\n<li><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/?p=962712\" target=\"_blank\" rel=\"noopener\">Microsoft Research, AutoGen<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2303.17651\" target=\"_blank\" rel=\"noopener\">Self-Refine: Iterative Refinement with Self-Feedback<\/a><\/li>\n<li><a href=\"https:\/\/papers.nips.cc\/paper_files\/paper\/2023\/hash\/1b44b878bb782e6954cd888628510e90-Abstract-Conference.html\" target=\"_blank\" rel=\"noopener\">Reflexion: Language Agents with Verbal Reinforcement Learning<\/a><\/li>\n<li><a href=\"https:\/\/press.aboutamazon.com\/sg\/aws\/2025\/9\/new-aws-research-shows-strong-ai-adoption-momentum-in-vietnam\" target=\"_blank\" rel=\"noopener\">AWS, Unlocking Vietnam&#8217;s AI Potential, 2025<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Prompt kh\u00f4ng bi\u1ebfn m\u1ea5t, nh\u01b0ng n\u00f3 kh\u00f4ng c\u00f2n l\u00e0 trung t\u00e2m c\u1ee7a h\u1ec7 th\u1ed1ng AI hi\u1ec7n \u0111\u1ea1i Trong giai \u0111o\u1ea1n \u0111\u1ea7u c\u1ee7a AI t\u1ea1o sinh, nhi\u1ec1u t\u1ed5 ch\u1ee9c xem n\u0103ng l\u1ef1c AI l\u00e0 n\u0103ng l\u1ef1c vi\u1ebft prompt. Ai m\u00f4 t\u1ea3 y\u00eau c\u1ea7u r\u00f5 h\u01a1n th\u00ec nh\u1eadn \u0111\u01b0\u1ee3c c\u00e2u tr\u1ea3 l\u1eddi t\u1ed1t h\u01a1n. C\u00e1ch nh\u00ecn \u0111\u00f3 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":1727,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[23],"tags":[124,35,123,128,126,125,127,105],"class_list":["post-1722","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tin-tuc","tag-agent-engineering","tag-agentic-ai","tag-ai","tag-ai-workflow","tag-multi-agent-system","tag-prompt-engineering","tag-software-engineering","tag-tin-cong-nghe"],"acf":[],"_links":{"self":[{"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/posts\/1722","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\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/comments?post=1722"}],"version-history":[{"count":6,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/posts\/1722\/revisions"}],"predecessor-version":[{"id":1745,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/posts\/1722\/revisions\/1745"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/media\/1727"}],"wp:attachment":[{"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/media?parent=1722"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/categories?post=1722"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bbotech.vn\/vi\/wp-json\/wp\/v2\/tags?post=1722"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}