Theory 2026 AI 调研发布,安全治理跃升为落地第一痛点
The Theory 2026 AI Survey Results
- 1Theory 2026 AI 调研中 43% 的技术从业者将安全与治理列为头号痛点,一年内从第六位跃升。
- 245% 的团队在多个模型间路由查询,其中 23.7% 用自训路由器,成本优化已成标准做法。
- 3259 个让智能体写代码的团队中,62% 将沙箱托管在 Cloudflare,约为最接近对手的三倍。
- 456% 的受访者用 BI 工具分析智能体表现,48% 借助编码智能体,41% 用专门可观测性工具。
AI 落地的主要障碍已从模型能力与上下文限制转向安全治理,智能体基础设施同时出现了集中化的主流选型。
- 影响:安全与治理成为采购的前置门槛,相关工具预算需提前安排;查询路由已覆盖 45% 的团队,成本结构可重新测算;沙箱等环节供应商高度集中,依赖风险随之上升。
- 参考:可考虑先盘点自家智能体场景的安全与治理缺口再定预算;值得用查询路由做小规模成本对比;选沙箱方案时可把 Cloudflare、Vercel、Modal 等一并纳入评估。
- 依据:口径为 Theory VC 自有调查,2026 年 9 月 22 日调研 455 名资深技术从业者;部分指标为当年新增题目,无同比数据可比。
The 2026 Theory AI Survey surprised us, just as the 2025 edition did. In 2025, we found that context, limited AI performance. In 2026, that seems to be solved.
455 senior technical builders replied to give us a cross-section of the AI ecosystem today.1
Security is the biggest barrier to adoption
Security rose from sixth to first among pain points in twelve months. 43% of respondents rate security & governance the most important pain point, & evals come in second at less than half, 22%.
Only 10% say security tooling delivers the most value today. 18% expect it to lead in the future, the largest expected gain of any area.
Nearly half of teams route queries
Cost optimisation as well as model selection have become standard.
45% of teams now route queries across models, 23.7% on a router they trained & 21.5% on a proprietary one, while 54.7% send every query to a single model.
Cloudflare dominates sandboxes
Of the 259 teams writing code with agents, 62% host their sandboxes on Cloudflare, three times the closest competitor. Then Other at 17%, Vercel at 17%, Modal at 16%, E2B at 12%, Daytona at 9% & Sail at 7%. The one control a builder cannot fake is concentrated in a single utility, & it is billed as compute rather than as security.
BI performs more than half of agent analysis
56% of respondents use business intelligence tools to analyse the performance of their agents. The surprising statistic is not far behind : coding agents also perform some of the work, at 48%. Both systems are excellent at parsing agent behaviour. A roughly equivalent number use dedicated observability tools, at 41%, which does suggest a convergence of the category, at least for this one use case. Spreadsheets, that tardigrade2 of enterprise software, continue to survive at 30%.
There is a lot more to unpack within the full survey, including open versus closed source model adoption, the rise of MCP despite doubts last year, & the still early adoption of evals. Overall, it is clear how quickly the ecosystem is evolving, & how much sophistication has permeated the enterprise, more quickly than any wave we have seen.
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Theory’s AI in Practice Survey 2026 fielded 455 senior technical builders on 22 September 2026, the second annual edition, written up by Lauren DeMeuse. The 2025 comparison is a different sample of 413, from the 2025 edition & its own post. Percentages are rounded & multi-select questions sum above 100%, & where 2025 allowed one answer & 2026 allowed several, every 2026 share is lifted. The pain comparison holds each area’s place by average rather than its score, because 2025 asked for a ranking & 2026 asked for a 1-7 rating of each area, so context moving from first to fourth is a comparison of place, not of score. Q9 routing & Q12 sandbox hosting are new in 2026 & have no prior-year comparison ; Q12 was asked only of the 259 teams whose agents write & execute code. The 10% & 18% are shares of 455 builders, not dollars. Full data, all 27 questions : theoryvc.com/surveys/ai-in-practice-2026. The published write-up : AI in Practice Survey 2026. ↩︎
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Tardigrades are microscopic animals known for surviving extremes that kill almost everything else, including desiccation, radiation & the vacuum of space. The comparison casts the spreadsheet as the enterprise software equivalent : unglamorous, near-impossible to eliminate, & present in almost every environment, just like spreadsheets. See Tardigrade. ↩︎
来源:Tomasz Tunguz 博客 · tomtunguz.com
