Andrey Risukhin

Factory is a product company. In a year when a lot of smart money is betting on neoservices that is starting to sound contrarian.

The AI wave makes it tempting to sell outcomes and deliver them with people. We think the bigger opportunity is software that gets better every time it's used. That's what we build for our customers, and it's how we run Factory.

The products we build should help our customers build their own capacity to ship better software, faster. We think of the product as everything from the first time you hear about Factory through your Nth renewal.

Building the right product starts with the old advice: listen to your customers' problems, not their solutions. In 2023, many people believed we should have built autocomplete. We understood that we instead had to build toward self-improving software and software factories, since that is what would come next.

That is our product goal: self-improving software, which continuously improves from the data feedback loop of its users. Self-improving software doesn't happen on its own. You have to be data-backed and optimize the signal → deploy loop. That requires a software factory operating continuously and evolving alongside the software it produces.

The factory also has to know what good looks like. It has to help the organization extract its tacit knowledge and embed it into the software that operates the business. Taste is not sufficient. You must enforce the unique decisions that define your product. And it doesn't stop at the product. The entire company is going to be defined by software that listens to the rhythm of the business and enforces it. The clear goal of a leader is to ensure the quality and correctness of these systems.

We run Factory this way. Our unique product and technical decisions are codified as customizations to our harness, automations, CI/CD, lint rules, etc. Factory agents sit in our shared Slack channels, where they build context and execute tactical work on demand.

It also changes how we organize. Your Engineering, Product, and Design team will ship your org chart, so you must design an organization where incentives are maximally aligned. Our pod structure maps directly to our product taxonomy, which gives each pod deep expertise and agency. We work carefully to make sure the product feels cohesive and not like multiple disconnected teams. This is not easy, and we still haven't perfected it. We keep the minimal number of layers between leaders and the organizational lines. 1:25 is not unreasonable for a true people manager.

Our product operating system is itself self-improving software. It aggregates feedback, tracks launches across the team, and organizes our work. With it, our Head of Product @TaylorTheSavage runs a product surface that would otherwise require an army of PMs with just a handful of high-ownership, high-leverage ones.

When an org is designed this way, its impact scales with software, not headcount. That is the real difference between a product company and a services company. Selling outcomes is right. Delivering them with people is services. Neoservices arbitrage the gap between how fast the technology moves and how fast buyers adopt it, and some will become large businesses. But that gap closes every time a product company sells the same buyer a better long-term solution. The market already knows how to value services: Infosys does about $20B in revenue and trades at roughly 2x, not 50x, and it's down about 40% this year.

Being a product company is harder. @danlovesproofs once told me something I very much agree with. Product companies are like movie studios. You have to keep producing blockbusters, and that helps you build talent, brand, and resources. Gone are the days when you could coast on one hit. Do that, and you'll be acquired by Bending Spoons at a fraction of your value. The war is always being waged, and no winner is ever truly ahead by much. And demand for the movies is up.

That's true even against the model labs. There is a value gap between the models and outcomes for users. Anyone can close that gap, and there's no reason to believe any company has an automatic right to win the products that matter most. If anything, access to the full pareto frontier of cost and quality gives model-independent, product-focused companies a focus, cost, and quality advantage.

If someone asked me what to build today, I'd say go build a product company. It is harder, but the biggest outcomes are only possible through product.

Announcing our new and improved Analytics, giving engineering leaders transparency into consumption, model efficiency, and adoption, broken down by model and by user across every session in the organization.

Custom Automations are now GA in Factory.

Describe a recurring workflow, pick a schedule or event trigger, and Droid runs it to the intended result. You choose the model, the machine, and Connectors for each automation.

This actually improved my sleep so much

"Inclined Bed Therapy"

Fixed my acid reflux issues and solved the headaches I was getting when waking

🌉 Excited to announce the awesome speaker lineup 🔥 for the Code Engineering event in San Francisco 🌁

Previous Agent Engineering HQ @AgentEngHQ Harness Engineering event in June pulled more than 300 people (1100+ registered) and flooded the Loft. Code Engineering is the next and you cannot find a better lineup than this. The speakers from the coding agent labs itself who know the ropes.

💻 Code Engineering: From Coding Agents to Software Factories
🗓️ Tuesday, October 27 · 6:00–8:30 PM
📍 AWS Builder Loft, San Francisco 🌁

🎙️ Speakers
• Seth Karten (@sethkarten) - Prime Intellect @PrimeIntellect
Prime Agent: a self-improving RLM harness with swarm communication
• Ben Holmes @BHolmesDev - Warp @warpdotdev
Building a self-improving software factory

• Sydney Runkle @sydneyrunkle - LangChain (@LangChain)
Building agents that work like coding agents and generalizing those primitives beyond coding

• Andrey Risukhin (@AndreyRisuka - Factory @FactoryAI)
Reducing coding harness latency with the Software Factory

If you are in San Francisco 🌉 on 27th October, you shouldn't miss this event.

🙏 RSVP Now as we have limited seats. Checkout the detailed talk and abstract:

👉 luma.com/cico2dxy

Factory for @SlackHQ Code is now in beta for select users.

Bring a software task into the channel, collaborate with your team, and Factory gets to work. The result comes back where the conversation started.

I joined after talking to Factory made 3 things clear:

(1) this team is ego-free and obsessed with accelerating engineering, for us and customers. Kudos @EnoReyes for claiming this and then demonstrating it daily.

(2) software should be a utility. Electricity doesn't make the beer better but is necessary to produce it (first @AcquiredFM lesson I internalized in 2020). Code doesn't make people trust banks or buy from a given company, but reusing best software patterns helps enterprises produce great products.

(3) everyone wins (except providers) by avoiding vendor intelligence lock in.

This is the work of our lives, and the way I do the work is so different than January. Join us! factory.com/company#careers

We've raised $200M at a $5B valuation to scale self-improving software development in the enterprise.

The round brings our total funding to over $400M and more than triples our $1.5B valuation from April.

Designers are doing the best work of their lives at @FactoryAI

Join us: factory.ai

Droid now works everywhere you do.

Connect @Google, @linear, @databricks, @NotionHQ, @Snowflake, @figma, @datadoghq and over 50 additional tools. Introducing Connectors and Personas.

很喜欢这种把旅行照片收进田野笔记里的方式。
照片留住现场，旁边那枚略微缺墨的彩色橡皮章，只刻下最值得记住的轮廓。
树、穹顶、海岸都没有被讲满，反而像旅途中随手盖下的一页，安静，又很有地方感。

prompt：
请将我上传的每一张照片分别制作成一张独立的「橡皮章旅行田野笔记海报」，每张照片单独输出，不要多图拼贴。

整体采用4:3横版构图，将画面划分为左右两个区域，但不要绘制明显的分隔线。

左侧约占画面58%，忠实保留原始照片。准确保持主体身份、地形、建筑、植物、人物、空间关系、自然光影、真实质感和原有色彩氛围，仅进行克制的艺术出版物级摄影调色，并加入极轻微的细腻胶片颗粒。为适配版式可以自然裁切，但不得拉伸、扭曲、移动、替换或重新绘制主体。

右侧约占画面42%，使用温暖的米白色旧纸作为背景。纸张具有细微纤维、天然颗粒、轻微使用痕迹和哑光触感，同时保留大面积未经印刷的纸张留白，让空白成为版式的重要组成部分。

分析原始照片，从中提取最具地点辨识度的主体轮廓、建筑结构、地形走势、植物姿态、道路、水岸线或其他关键视觉关系，将其压缩成一枚小型多色橡皮章图像。

不要逐项复制照片中的全部内容。只保留能够让人一眼认出原始地点、主体和场景关系所必需的最少信息。删除人群、车辆、密集窗户、重复建筑、细碎植被、装饰构件和无关背景。

章印位于右侧纸张区域的中下部，整体只占右侧区域高度的约30%—38%，周围必须保留充足留白。章印不能放大成普通插画、完整风景画或品牌Logo。

根据原图构图决定章印的组织方式：

- 标志性建筑：保留最有辨识度的外轮廓、屋顶、穹顶、拱门、塔楼或主要结构。
- 山地聚落：将建筑压缩成沿地形排列的少量阶梯状色块。
- 海岸风景：保留山体走势、聚落层级、岸线和少量断续水纹。
- 城市远景：保留主要天际线、一个标志性建筑及一两层远山。
- 自然景观：保留主要山体、树木、水岸或道路的方向关系。
- 近景遮挡物：如果其对原图叙事重要，可作为前景章印轮廓保留。

从原始照片中提取2—4种专色油墨。优先使用炭黑、深绿、砖红、赭黄、灰蓝、灰褐等经过降低饱和度的颜色，但不得强行套用固定色盘。保留原照片最有辨识度的色彩性格，仅允许一个小面积颜色作为视觉强调。

每一种颜色都要呈现为分别手工盖印的效果：

真实橡皮章雕刻纹理、手工刻痕、粗细不均的排线、轮廓缺口、断裂边缘、干燥缺墨、纸张透底、颗粒状油墨、压力不均、局部重影，以及约1—2毫米的轻微套色偏移。

不同色层之间允许出现自然错位，边缘不能数字化平滑。印迹应像真正刻制后压在旧纸上的橡皮章，而不是套用滤镜的照片、平滑矢量插画或线稿Logo。

根据照片中的地点、主题和视觉意象生成文字：

地点英文名称
No. 编号
三个简短英文关键词
西元年份

文字放在章印下方或邻近留白处，使用小型、克制、略带机械误差的打字机字体。排版应像旅行者的田野记录，而不是广告标题。确保所有文字拼写准确，不添加无关标语、品牌或装饰性文案。

整体气质像建筑师、旅行作家或自然观察者保存的田野笔记：安静、克制、触感真实、地域明确、带有手工误差和收藏感。照片负责记录现场，章印负责留下记忆中最值得辨认的部分。

Avoid：明显的中央分隔线、圆形印章、中文红色印章、邮票齿孔、蜡封、贴纸拼贴、旅游纪念品模板、平滑矢量Logo、通用城市图标、完整复制所有建筑、密集刻画、儿童手工感、卡通风格、3D渲染、塑料质感、光滑数字渐变、过度饱和、过多文字、装饰堆积，以及重绘或改变左侧原始照片。

🫵 Do you live in SF as an engineer/founder?
🫵 Do you use agents and AI?
🫵 Can you do a pushup? (optional)

@vercel is renting out a gym for a night of hacking + lifting

There will be prompting AND strength challenges (building an app while planking)

Respond/DM for the link