从 Talkers 到 Doers 直击 AI 进化的下一个十年

C3P0 (C3P0) • 2026年02月04日 12:26
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<div class="poster-container">
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        <!-- Header -->
        <header class="header">
            <div class="tag">2026 · AI 进化论</div>
            <h1>从 Talkers 到 Doers<br>直击 AI 进化的下一个十年</h1>
            <p class="subtitle">深度拆解红杉资本 x LangChain 创始人 Harrison Chase 硬核对话</p>
        </header>

        <div class="main-layout">
            <!-- Card 1: Paradigm Shift -->
            <div class="card">
                <div class="card-title">
                    <svg width="24" height="24" viewBox="0 0 24 24"><path d="M12 2C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2zm-1 17.93c-3.95-.49-7-3.85-7-7.93 0-.62.08-1.21.21-1.79L9 15v1c0 1.1.9 2 2 2v1.93zm6.9-2.54c-.26-.81-1-1.39-1.9-1.39h-1v-3c0-.55-.45-1-1-1H8v-2h2c.55 0 1-.45 1-1V7h2c1.1 0 2-.9 2-2v-.41c2.93 1.19 5 4.06 5 7.41 0 2.08-.8 3.97-2.1 5.39z"/></svg>
                    范式转移：行动者的工业革命
                </div>
                <div class="card-content">
                    <p>如果你还在沉迷于 ChatGPT 的聊天框，那你可能正在错过一场关于<span class="highlight">“行动者”</span>的工业革命。2026年，AI 将彻底告别只会动嘴皮子的阶段，进化为能够持续执行、反复试错、自我修正的 <span class="emphasis">“长程 Agent” (Long-Horizon Agents)</span>。</p>
                </div>
            </div>

            <!-- Card 2: AutoGPT vs Agents -->
            <div class="card">
                <div class="card-title">
                    <svg width="24" height="24" viewBox="0 0 24 24"><path d="M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zm-7 0c.55 0 1 .45 1 1s-.45 1-1 1-1-.45-1-1 .45-1 1-1zm0 16c-3.31 0-6-2.69-6-6s2.69-6 6-6 6 2.69 6 6-2.69 6-6 6zm2-7h-3v3h-2v-3H6v-2h3V6h2v3h3v2z"/></svg>
                    为什么 AutoGPT 是先烈？
                </div>
                <div class="card-content">
                    <div class="comparison-box">
                        <div class="compare-col">
                            <h3><span class="status-badge status-fail">先烈</span> AutoGPT</h3>
                            <ul>
                                <li><strong>设想：</strong>让 LLM 在循环中自主运行、决策。</li>
                                <li><strong>短板：</strong>模型能力不足；缺乏成熟的 Scaffolding（支架）和 Harness（框架）。</li>
                                <li><strong>结局：</strong>容易死循环，无法长时间稳定运行。</li>
                            </ul>
                        </div>
                        <div class="compare-col">
                            <h3><span class="status-badge status-success">现在</span> 长程 Agent</h3>
                            <ul>
                                <li><strong>突破：</strong>推理模型 (Reasoning Models) 变强。</li>
                                <li><strong>关键：</strong>掌握了好的 Harness（架构）：规划、上下文压缩、文件系统交互。</li>
                                <li><strong>结果：</strong>能连续运行数小时，完成 Coding、SRE、Deep Research。</li>
                            </ul>
                        </div>
                    </div>
                </div>
            </div>

            <!-- Card 3: Harness Architecture -->
            <div class="card">
                <div class="card-title">
                    <svg width="24" height="24" viewBox="0 0 24 24"><path d="M22 11V3h-7v3H9V3H2v8h7V8h2v10h4v3h7v-8h-7v3h-2V8h2v3z"/></svg>
                    底层解密：Harness 架构
                </div>
                <div class="card-content">
                    <p>构建 Agent 不再只是“加一层 AI”，而是工程范式的根本改变。Harness 是包裹模型的“有主见”的外壳，而非简单的框架。</p>
                    <div class="harness-visual">
                        <div class="harness-step">
                            <div class="step-icon">1</div>
                            <span class="step-title">规划 (Planning)</span>
                            <span class="step-desc">内置规划工具<br>明确任务拆解</span>
                            <div class="arrow">→</div>
                        </div>
                        <div class="harness-step">
                            <div class="step-icon">2</div>
                            <span class="step-title">上下文管理</span>
                            <span class="step-desc">压缩、文件系统访问<br>突破 Token 限制</span>
                            <div class="arrow">→</div>
                        </div>
                        <div class="harness-step">
                            <div class="step-icon">3</div>
                            <span class="step-title">工具使用</span>
                            <span class="step-desc">Bash, Code<br>直接操作世界</span>
                        </div>
                    </div>
                    <p style="font-size: 13px; color: #aaa; margin-top: 15px;">💡 光读代码不够了，必须看它在真实输入下做了什么，Traces 成为新的 Source of Truth。</p>
                </div>
            </div>

            <!-- Card 4: Moat & Coding -->
            <div class="card" style="border-color: rgba(255, 111, 0, 0.2);">
                <div class="card-title">
                    <svg width="24" height="24" viewBox="0 0 24 24"><path d="M12 2C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2zm-2 15l-5-5 1.41-1.41L10 14.17l7.59-7.59L19 8l-9 9z"/></svg>
                    护城河：记忆与编程
                </div>
                <div class="card-content">
                    <p><strong>记忆是 AI 无法逾越的护城河：</strong><br>一个经过长时间磨合、内化了特定任务模式与背景记忆的 Agent，其价值远高于通用的超级模型。拥有长期记忆的 Agent 能够持续积累经验。</p>
                    
                    <div class="concept-box">
                        <strong>编程能力是 AGI 的终极形态：</strong><br>
                        代码是通用的语言。如果一个 Agent 能写代码，它就能调用任何 API，构建任何工具。未来的通用 Agent，本质上就是一个“Coding Agent”。
                    </div>
                </div>
            </div>
        </div>

        <!-- Quote Section -->
        <div class="quote-section">
            <div class="quote-text">
                “光读代码不够了，看它在真实输入下做了什么，才知道系统到底在干什么。”
            </div>
            <div class="quote-author">— Harrison Chase, LangChain Founder</div>
        </div>

        <!-- Footer -->
        <div class="footer">
            DESIGNED BASED ON SEQUOIA CAPITAL X LANGCHAIN CONVERSATION · 2026 FORECAST
        </div>
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从 Talkers 到 Doers 直击 AI 进化的下一个十年

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