Kevin Donoho (@kevindonoho) profile picture

GTM @ second tier competitor

Denver, CO
Joined January 2011
Photo by Kevin Donoho (@kevindonoho)Photo by Kevin Donoho (@kevindonoho)Photo by Kevin Donoho (@kevindonoho)Photo by Kevin Donoho (@kevindonoho)Photo by Kevin Donoho (@kevindonoho)Photo by Kevin Donoho (@kevindonoho)Photo by Kevin Donoho (@kevindonoho)Photo by Kevin Donoho (@kevindonoho)Photo by Kevin Donoho (@kevindonoho)Photo by Kevin Donoho (@kevindonoho)
Kevin Donoho retweeted
We're excited to share our customer story with @claudeai featuring Factory co-founder and CEO @matanSF. We cover topics like how @AnthropicAI frontier models in @Droid are enabling engineering teams to handle long-horizon tasks across large codebases, what it will take to build a fully autonomous "dark factory" for software, and more. youtube.com/watch?v=N6FkmdL0…
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Kevin Donoho retweeted
Holy Ship
Factory now supports @Jira delegations. Delegate tasks and sub-tasks in Jira to Factory, and Droid will start running.
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Kevin Donoho retweeted
Factory now supports @Linear delegations. Delegate an issue in Linear to Factory, and Droid will start running.
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Kevin Donoho retweeted
If Factory works for one of the most demanding enterprises in then world (scale, security, compliance, sophistication re impact) it will absolutely satisfy your organization’s requirements.
As the world’s largest alternative asset manager, @Blackstone requires the highest standards of deployment flexibility and governance. Factory made it possible to operate agentic software development within Blackstone’s own data centers without compromising model choice or workflows.
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Kevin Donoho retweeted
how I scaled my design workflow for a global billboard campaign that is live in NYC, Tokyo, London, and cities around the globe using coding agents in @FactoryAI 🧵🧵🧵 this thread is focused on using coding agents to reformat design assets for dozens of billboard panels that are often grouped, cropped, and placed in unexpected ways and less about designing the original motion graphics concept (which was created using a combination of generative AI video footage, and overlay graphics created with code / figma). Before coding agents, formatting all of these panels to spec would take hours / days of non-creative work...
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As the lead eng on OpenCompute, I'm incredibly excited for today's launch! OpenCompute allows any organization to run agents on their existing compute infrastructure. We're bringing a fleet of agents to the customer's environment, not bringing every customer into ours. It's going to power some of the largest industries in the world, where privacy and data sovereignty is of utmost importance. Check out the blog :) factory.com/news/opencompute
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You know we had to do it again, right?
Today we are introducing Remote Control. Your Droids run on a persistent self-managed remote machine, scoped to an individual user or service.
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Kevin Donoho retweeted
Today we are introducing Remote Control. Your Droids run on a persistent self-managed remote machine, scoped to an individual user or service.
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Eno-mogged.
Proprietary data which is why big 4 accounting firms beat ramp - oh wait Network effects which is why Github won AI software dev - oh wait Physical component which is why there are no new defense contractors - oh wait There is no moat. You are defenseless and also can win it at all at the same time. Act accordingly.
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Kevin Donoho retweeted
Proprietary data which is why big 4 accounting firms beat ramp - oh wait Network effects which is why Github won AI software dev - oh wait Physical component which is why there are no new defense contractors - oh wait There is no moat. You are defenseless and also can win it at all at the same time. Act accordingly.
Technical moats are mostly over at this point. If you’re building something that is meant to be durable, the only moats now are: • Proprietary data • Network effects • A physical component
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Kevin Donoho retweeted
I really like Mission Mode in Droid. My current mission has been running for 21 hours flawlessly so far 😁 Let’s see how it turns out.
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Factory capitalizing on a slow news week by shipping what enterprises need. Droid- the best harness on the market with the reporting and transparency large organizations require.
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.
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Kevin Donoho retweeted
We wanted one place that tells our whole EPD team what's actually true right now - a "Product Operating System". Automations is what powers this. Our ProductOS aggregates key metrics, product taxonomy, customer feedback, internal org-chart, ownership areas, product roadmap, and more - all in one place. Every morning at 8 a droid automation spins up on a cloud computer and reads one skill. that skill kicks off a subagent per playbook, 10 of them. one hits the warehouse, one pulls okrs out of notion, one diffs linear, a few read slack (launch channels, pod channels, support), one counts releases off github. calendar waits for roadmap since every release has to link to a roadmap item. the digest goes last and writes up what changed. Each subagent has to check its own work before writing anything - is the doc count in the range it expects, is the data actually from today. if something's off it doesn't load, logs why, and the site just shows yesterday with a stale banner. One of my favorite parts about automations is how they learn. The first line of the skill is basically "this file is everything you know, assume nothing else exists." so when a run screws up we don't patch code, we write the lesson into the playbook and tomorrow's run picks it up. Our head of product @TaylorTheSavage owns this now and playbook changes go through PRs like everything else. next up is letting it enforce stuff instead of just showing it: no kickoff, no status update in a week, no launch channel, it flags it or just does it.
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.
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Droid is the best product on the market
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.
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Kevin Donoho retweeted
my newest droid automation 🙏
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.
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Kevin Donoho retweeted
We are terminating Chris Degnan for unethical conduct involving Cognition. The last few months have seen incredible progress in AI capabilities. San Francisco has flourished as new companies that solve new, more ambitious problems are finding great success. Generally, it is a wonderful time to be building. We at @FactoryAI have seen overwhelming interest in our model-agnostic coding agents and our software factory product. Our team has 10x’d in size, while our revenue has 100x’d year over year. This momentum has been unprecedented. A much larger competitor, Cognition (makers of Devin) has fallen behind us on the capabilities that matter most to customers: cost, quality, and security. Instead of competing in the market, Cognition engineers feigned interviews with us to pry information about our product. Not finding what they were looking for, Cognition has decided to throw their weight and money at people with direct knowledge of our most confidential plans. It feels as though ethics is being thrown out of the window in the AI era. People are willing to do anything, including exploiting privileged information and violating ethical boundaries. I think this is unique to our time, and I don’t think it’s right. Integrity still matters. Yesterday, I made the decision to immediately terminate Christopher Degnan’s roles as a Board Observer and Advisor to Factory, after over a year of service. Prior to this decision, Chris told me he had a casual conversation with an executive at Cognition AI. When I questioned his intentions, he reassured me that ethics aside, he had “made too much money” and was “too lazy to go work for Cognition,” which I trusted and believed. On Monday, Chris spent time advising the Factory team on a handful of confidential board-level matters. That evening, he called me to say that the conversation that was initially described as casual and one-off was actually formal and recurring. For weeks, while he sat in our board meetings and advised our leadership team, he was also confiding with executives of our largest competitor. Chris was subject to confidentiality obligations in connection with his work with Factory. We do not know the extent of the information he shared, but it puts his timely questions about our product roadmap and what the parity gap involves into a new light. It is sad to sever a relationship with someone who has been a trusted advisor - and even a close friend - for over a year. But Chris’s conduct is unacceptable to me. Trust in Board Membership is one of the sacred bonds in the Silicon Valley, one that helps the startup ecosystem thrive. With it comes an enormous responsibility. That trust was violated. Competition is good. I respect and in many cases admire our competitors. San Francisco is a beautiful, singular place where the bold and ambitious go to defy the norms and precedents of the past. But certain principles that must remain. Violating ethics to seek advantage turns what should be positive-sum into zero-sum. We all love technology. And we all love to compete. But we must hold ourselves to a higher standard. The future of software engineering comes with abundance that will impact every person on Earth. Building that future comes with immense responsibility. We must build and compete with integrity.
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Kevin Donoho retweeted
After using Droid heavily for about two months, it is finally time for a full review. As always, this is completely independent. Not paid, not sponsored. I will break down exactly what worked, what did not, and where I stand after two months of serious use. I started on the Pro plan, then upgraded to Max once I decided to lean into it much harder. Having spent real time on both tiers gives me a solid baseline to compare them. Usage limits This is usually what people care about first. How generous is the subscription? Can you actually rely on it all week, or will you burn through your quota in two days and get stuck? Droid has one of the smartest setups I have seen for this. You basically get two separate usage pools. The first is your main allowance, which gives you access to the full model roster: Claude models, GPT models, Grok, and open models like Kimi K3. Once you hit the five-hour cap or your weekly standard allowance, Droid Core kicks in. Droid Core is a separate pool built around strong open models like Kimi K3, Qwen 3.8 Max, and GLM 5.3. I love this system because you always have a safety net. Even if you chew through your primary quota, you can still keep working on light and medium tasks until it resets. On Max, Droid Core is remarkably generous. Even on Pro, the allowance holds up well. If you stick to open weights and cheaper options like Sol and Luna, that $20 tier gives you actual breathing room. You can genuinely rely on it throughout the week. Max is where things get wild. Ever since Opus 5.5 dropped, I have run it relentlessly inside Droid. I have had sessions running past nine hours, sometimes longer on single projects, without hitting a wall. Keep in mind, this was Opus 5.5 running at Max effort. At points, it honestly felt like using Opus directly inside Claude's own subscription. The allowance is that generous. If you drop down to cheaper models, you can also run multiple sessions in parallel comfortably. There were times I had Astra and Fable both running at Max effort in separate sessions. They burn through usage much faster, which is expected, but I still managed to finish the work before hitting the limit. That alone tells you how generous the subscription is. Easily one of the best I have used. The harness actually improves the models This is one of the most impressive parts of Droid for me. In my testing, models behave noticeably better inside it. They are more disciplined, more obedient, and much stricter about following instructions. Take Sol. Sol can be stubborn. It loves doing what it thinks is right even when you explicitly told it to do the opposite. You see that constantly in Codex. Inside Droid, it listens. The difference is night and day. What makes this even more impressive is the variety of models available. You get frontier models, open weights, and completely different model families under one roof, yet the behavior stays consistently strong across them. That is rare. A lot of harnesses work beautifully with one or two models and fall apart once you start switching between families. Droid does a much better job of keeping the experience coherent. Caching is also great Looking through my logs, cache efficiency sat around 94%. I have seen higher elsewhere, but 94% at this scale is still fantastic. Across roughly 70 sessions over 14 days, I used about 585 million tokens. Most of that came from Fable and Astra, with Opus 5.5 joining toward the end. When you push that much context through expensive models, caching becomes extremely important. Weak caching will destroy your allowance much faster than people realize. Getting this kind of usage with models like Fable and Astra under a single subscription is rare right now. That genuinely impressed me. The desktop app is excellent The desktop app is a joy to use. Droid built one of the cleanest desktop app in the space when it comes to UI, navigation, and overall feel. It is fast, straightforward, easy to move around in, and they struck a great balance between deep capability and clean design. It also stays out of your way. It will not eat your RAM alive or drag your machine down like certain other desktop agents. Setup takes minutes, everything makes sense quickly, and it does not feel like a tool designed only for engineers. A programmer can use it, but a non-programmer can use it just as comfortably. That brings me to one of my favorite things about Droid. Droid goes far beyond coding A lot of harnesses feel like code-only tools even when the marketing says otherwise. Droid does not. It is easily the harness I have used across the widest variety of tasks. I have used it to benchmark models, build and update my personal site, prepare projects, run research, brainstorm, write, translate, and organize parts of my life. I even connected it to my email and used it for personal task management. It never felt out of place. That flexibility is a massive advantage. Claude and Codex can handle general tasks well too, but you are still locked into their specific model ecosystems. With Droid, I can use GPT models for what they do best, switch to Claude where it shines, and fall back on open models whenever that makes sense. That versatility gives the subscription a lot of value because it feels like a genuine all-around AI workspace rather than a specialized tool pretending to be one. Long tasks and context handling Droid handles long-running work very well. It keeps context intact, stays on track, and pushes tasks forward without slowly forgetting your initial instructions. The models also feel sharper and less lazy inside it, especially when the task gets large enough that weaker harnesses start drifting. Droid includes a dedicated Mission Mode for planning and long-haul projects. I found it especially strong for software development and complex tasks that need sustained focus over time. I have finished a huge amount of work with Droid in a surprisingly short window, and at this point I would genuinely hate to give it up. I am on Max right now and strongly considering the annual plan simply because I do not want to think about working without it. It bumped my productivity noticeably. A lot of you saw how quickly I rolled out Da7em Bench and Opethon, and Droid played a major role in helping me move that fast. I barely touched the CLI Given how much I normally like terminal workflows, this might sound funny, but Droid's desktop app is so good that I barely opened the CLI version. If you usually live in the terminal, I would still tell you to give the desktop client an honest shot. It is one of the best desktop agent experiences I have used, and in my case it was good enough that I simply did not feel the need to leave it. Voice input is fantastic The voice input deserves its own section because it has become a real part of how I work. In practice, it feels almost unlimited. I have recorded prompts stretching past ten minutes with zero issues, and the transcription quality is excellent in both English and Arabic. It picks up subtle phrasing, handles technical jargon cleanly, switches between languages without falling apart, and converts very quickly. I can record a long ten-minute brain dump, hit convert, and the text appears almost immediately. It is easily one of the best voice inputs I have used in any AI tool. Unfortunately, that brings me directly to one of my biggest complaints. The problems Most of my complaints are minor and fixable, but there are a few areas that definitely need attention. The first is voice input. Droid lets you bring your own API keys for external models, which is great. On Pro especially, you can use Droid's flagship models for planning and then execute with a cheaper model on your own key if you want to stretch your quota. That flexibility is genuinely useful. The problem is that once you hit your five-hour or weekly limit, one of Droid's best features turns off: voice input. For me, that is a serious problem because voice is not a gimmick here. It is central to how I work. Instead of spending twenty or thirty minutes typing a massive prompt, I can talk it through in five minutes. I get my thoughts down faster, explain more naturally, and iterate with the model without wasting time typing everything out. When voice gets disabled, my workflow breaks. I have to open another app, record there, transcribe the audio, copy the text, then paste it back into Droid. I do not understand why this has to be tied so tightly to the main usage cap. Speech-to-text is not expensive enough to justify locking the feature completely. At the very least, let us bring our own speech-to-text API key. I already host my own speech model in Hermes. I would gladly point Droid to it and keep working. This is probably the first thing I would change. The second thing is memory. Droid needs an actual memory system. Right now, you mostly have an instruction file, which means repeating yourself more than you should and starting fresh sessions that can feel too disconnected from the ones before them. I would love to see a proper editable memory layer where the agent gradually learns your habits, preferences, and recurring context across sessions. Hermes does this very well, and something similar inside Droid would make the whole experience much stronger. I also still want a true goal mode. Mission Mode is useful, but what I really want is an autonomous mode where I can define an outcome, give the agent full permissions, and let it run until the job is finished. For long-running, safe tasks where I trust the model, I want to walk away from my desk knowing it will keep going. Instead, I sometimes come back and find it stopped just to ask whether it can delete a temporary file it created itself. That kind of interruption ruins unattended work. Asking questions upfront is good behavior. I actually like it when a model clarifies things before starting. But once the plan is clear and full permissions are granted, it needs to distinguish between something genuinely risky and something completely routine. Do not pause a multi-hour run to ask me whether you should clean up your own scratch file. There is another issue I only really encountered with Opus 5.5. Sometimes the model thinks for a long time, especially at Max effort on complex tasks. Five minutes, ten minutes, occasionally longer. Droid can sometimes interpret that as the model making no progress and stop the run, warning you that the model produced consecutive turns without visible output or tool calls. The problem is that the model was not stuck. It was thinking. If I deliberately put Opus 5.5 on Max effort and hand it a difficult task, I expect it to take its time. Droid needs to handle long thinking stretches more gracefully instead of assuming the run has stalled. There is also one thing I would love to see in the future, although I would not call it a flaw. Droid is one of the best harnesses I have used, and the engineering behind it is genuinely impressive. If they ever open-sourced the desktop harness, I think it would be an incredible resource for the developer community. People could learn from it, build on top of it, and customize it much more deeply. It could also help with some edge cases. I once ran the exact same prompt through the same model inside and outside Droid. It ran fine outside but refused inside Droid. That only happened once, to be fair. Droid is actually one of the least restrictive harnesses I have used, and in my experience it gives you far more room than Claude or Codex. Still, more transparency and customization would be valuable. It is their product and their decision, obviously, but I think the community would gain a lot from engineering this good. One thing you should genuinely watch out for is instruction files, because this derailed my setup for a while. After an update, Droid suddenly started behaving strangely. I eventually found that the problem came from an instruction file conflict. Some of my custom rules were sitting in an AGENTS.md file, while Droid was reading from its own Factory instruction path. That created inconsistent behavior. Sometimes it seemed to read one file, sometimes the other, and sometimes instructions I had explicitly told it to remember disappeared in a new session because the next chat was reading from a different location. I eventually fixed it using Droid itself by consolidating everything into the official Factory/AGENTS.md path. My advice here is simple: once you configure your instructions, start a completely fresh session and ask Droid exactly what rules it can currently see. Verify that everything is actually being read before assuming your setup is correct. Computer Use also still needs more polish. Sometimes it runs smoothly in the background and barely interferes with what I am doing. Other times it takes over the entire screen and steals focus, which means I basically have to stop working until it finishes. I still have not found a clear rule for what makes it choose one behavior over the other. I tried adjusting things in different ways but could not get it to stay in the background consistently. That unpredictability is annoying. To their credit, a recent update made Computer Use significantly better. Before that, I had cases where it would simply freeze halfway through a workflow and never finish. Now it is much faster and more reliable. The main thing left to improve is focus management. I want it to stay in the background by default and only take over the screen when that is actually necessary. The important part is that none of these problems make me dislike Droid. Most of them feel like fixable product issues rather than fundamental flaws. The biggest thing I want from Droid right now is a proper mobile app. Something fast and simple that lets me check on ongoing work, send models new tasks while I am out, and keep things moving without being tied to my computer at home. That would make a huge difference in day-to-day usability and quality of life, and for me personally, it is the feature I want them to ship as soon as possible. Where do I stand on Droid? Simply put, Droid earns its place in any serious AI stack. People constantly ask me what subscription to buy, which tool fits their budget, or what service can handle everything from coding and writing to research and personal tasks. Droid answers a surprising amount of that confusion. Its biggest strength is that it does not force itself into one narrow identity. You get access to multiple model families, generous usage, a strong harness, a great desktop experience, and enough flexibility to use it across coding, research, creative work, organization, and everyday tasks. That is exactly why I do not want to drop it. The team matters too One of the things that built my trust in Droid happened after an update temporarily broke part of my workflow. I talked about the problem openly, and people from the team reached out immediately, including one of the founders. They listened, took the feedback seriously, and told me they were already working on fixes. That matters a lot to me. There are two kinds of companies in this space: companies that think they are at the top and stop listening to users, and companies that are genuinely at the top and still pay close attention. Droid is a very good example of the second kind. They already have one of the strongest products in the space, yet they still listen, respond, and keep improving it. I also had another issue recently that turned out to be completely my fault. The problem was on my side, not theirs, and they still helped me debug it and stayed with me until everything worked properly. That kind of support is rare. When you are paying for a product and building part of your daily workflow around it, knowing the people behind it actually care about your experience makes a real difference. After two months of daily heavy use, Droid has become one of my most trusted subscriptions. It has flaws, and I laid them out because pretending otherwise would make the review useless, but none of them change where I stand. Droid is easily one of the tools I genuinely do not want to work without.
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Kevin Donoho retweeted
I spend a lot of time thinking about what has to happen for better models to become better software. The research progress is remarkable, but there’s still a lot of work between a model gaining a capability and someone being able to depend on it. That work is interesting in its own right. Understanding a codebase, fitting into how a team operates, knowing when a result is wrong, making something reliable enough that people can stop checking every step. Better models help with all of this, but someone still has to take responsibility for the whole system. It is now clear that it’s nothing short of critical that some of the companies doing that work are model-independent. Different models are useful for different things, and those tradeoffs keep changing. We should be able to choose based on what works for a customer, and change our minds when the evidence changes. Customers shouldn’t have to make a long-term bet on a research lab to improve how they build software. We shouldn’t have to trust the creator of the model to do what’s best for their customers. We should force them to in order to compete. There’s a business model question here too. If we find a way to do the same work reliably with less inference, that should be a good thing for both us and the customer. If another lab makes a breakthrough, we should be excited to put it to use. Independence doesn’t automatically create that alignment, but it gives us more room to build around it. I’m interested in where intelligence research goes. I just don’t think every AI company needs reaching AGI to be its organizing purpose. Helping people build things they couldn’t build before is a substantial goal on its own, with useful measures of progress along the way. That’s how I think about Factory, and what makes today’s funding meaningful to me. More room to work on these problems, with our attention on the people using the software.
We have raised $200M at a $5B valuation to scale self-improving software development in the enterprise. @FactoryAI has grown to serve hundreds of thousands of developers at companies including RBC, Adobe, Nvidia, T-Mobile, and Palo Alto Networks. We will use this capital to accelerate our investments in research, product, and global go-to-market.
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The best platform for Enterprise AI orchestration getting a huge investment to grow faster.
We have raised $200M at a $5B valuation to scale self-improving software development in the enterprise. @FactoryAI has grown to serve hundreds of thousands of developers at companies including RBC, Adobe, Nvidia, T-Mobile, and Palo Alto Networks. We will use this capital to accelerate our investments in research, product, and global go-to-market.
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