Head of OSS @dosu_ai

Los Angeles, CA
Joined November 2008
Taylor Dolezal retweeted
This feels short-sighted. The goal shouldn't be to measure the productivity of your individual developers. The goal should be to build a system (i.e software factory) that minimizes the need for developers to be in the loop (i.e maximizes agent autonomy).
What if your AI budget went to the engineers who use it best? Blanket usage caps are a hiring freeze in disguise. Introducing efficiency-based auto-approvals for your most productive engineers, plus Devin Coach to help everyone get there. devin.ai/blog/efficiency-bas…
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Taylor Dolezal retweeted
One way @AmpCode and orbs feel like the future: in a new thread, said "audit the code base for this old API usage, group the code into areas, create linear issues for each area, and spin up a thread to fix each one" and I have a whole swarm of threads just ... doing it.
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Taylor Dolezal retweeted
In our @vercel AI SDK replays, agents learned the same build rule across 59 sessions and 40 issues. We traced the repeated discoveries via @anthropicAI's Claude Code and @openai's Codex logs. What do your agents keep relearning? go.dosu.dev/session-memory-x
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Taylor Dolezal retweeted
Lots of people asked about this and I don’t think it makes sense to publish as a built-in skill: github.com/docwriter-org/pla… It’s from @sh_reya — I also * highly recommend * her and @HamelHusain’s evals course
Replying to @rockatanescu
We have a skill called “plain writing” in our repo that is the single most used skill internally by a factor of 2
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Just Orb It 🪐
The things you see in Soho coffee shops
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Taylor Dolezal retweeted
WebMCP is awesome
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Taylor Dolezal retweeted
Looking for an open source leadership opportunity? Join me on the @todogroup steering committee! We’re writing a book to help organizations run open source programs and exploring how AI agents can help us automate tasks. Apply by Oct 20: todogroup.org/community/2027…
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Taylor Dolezal retweeted
great paper. saturation w.r.t self-learning is really interesting to measure for benchmarks, but it is hard to interpolate to agents at companies. at companies the underlying "game" is constantly changing. excited to see more research like this
🤖 How well do agents learn from experience? We study agents that amortize experience into reusable artifacts and introduce Agent Plasticity to measure how efficiently they improve on held-out environments. Top performer ≠ most efficient learner.
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Taylor Dolezal retweeted
Anthropic released Claude Haiku 5.5 today, so we ran the 5.5 family through our coding agent token usage benchmark. Haiku, Sonnet, and Opus each did 5 tasks, 3 times each, in Claude Code at its default medium effort. Haiku 5.5 spends a significant amount of time on reasoning and planning, which is typical for how smaller models increase intelligence.
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Taylor Dolezal retweeted
early results on Luna vs Jev vs Decisions API on a few internal classification tasks tldr; they are very comparable on performance and speed
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As you use @claudeai or @OpenAI, you can improve your outcomes by understanding how your tokens are used (e.g., whether they're for knowledge management, research, routine tasks, or more).
We replayed 49 @vercel AI PRs across two coding agents, with an estimated $44.00 on Claude Code (Opus 5.5) and $27.29 on Codex (GPT 6.1 Sol). Where did the gap come from? Spoiler: Low- and mid-scope work came out about even... go.dosu.dev/agent-cost-gap-x
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Hello, San Francisco!
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Taylor Dolezal retweeted
Just shipped new controls to help manage spam and slop in private vulnerability reporting: • Daily limits on new reports per account • Custom daily limits for your repo • Allow lists for trusted reporters
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Taylor Dolezal retweeted
A working test command becomes a reusable procedure when the next coding agent knows when to run it and how to confirm the suite ran. We walk through make test-int, shared repository instructions, and skills. dosu.dev/blog/procedural-mem…
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Can't wait to start plexing like it's 2099!
We like Rex, our new terminal multiplexer, so much that we wanted to share it with you. We’re admitting testers from our waitlist starting today. superlogical.com/updates/pub…
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Taylor Dolezal retweeted
that’s unfortunate, maybe @Cloudflare folks can help
This quoted post is unavailable.
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Taylor Dolezal retweeted
Does your coding agent still recommend a tool your team replaced? We found a Celery migration comment that survived the move to DBOS and the removal of Celery. Semantic memory needs to preserve when a fact no longer applies. dosu.dev/blog/semantic-memor…
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Taylor Dolezal retweeted
Introducing Conductor Mobile! Run a team of cloud agents from your iPhone, live now in the App Store.
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Taylor Dolezal retweeted
How much better would a coding agent actually perform if it had the right memories from the start? VibeMemBench tries to answer that before testing existing memory systems. Devin explains why that made the benchmark the best memory one so far.
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